Methods, apparatus, equipment, dielectrics, and products for determining battery cell models

Abstract

This application provides a method, apparatus, device, medium, and product for determining a battery cell model. The method includes: acquiring target information of the battery cell; the target information of the battery cell includes the size information of the battery cell, multiple sets of extrusion test information, and model information of an initial battery cell model; determining the mesh information of a mesh model of the battery cell based on the size information of the battery cell; the mesh information of the mesh model includes first mesh information of the battery cell shell and second mesh information of the battery cell core; performing preprocessing operations on the multiple sets of extrusion test information to determine target extrusion test information; the preprocessing operations include at least one of the following: duplicate data removal operation, data filtering operation, and data optimization operation; updating the model information of the initial battery cell model based on the first mesh information, the second mesh information, and the target extrusion test information to obtain the target battery cell model, so that the obtained target battery cell model can more accurately reflect the mechanical behavior of the battery cell.

Description

Technical Field

[0001] This application relates to the field of automotive technology, specifically to a method, apparatus, equipment, medium, and product for determining a battery cell model. Background Technology

[0002] In the automotive industry, the battery pack, as a key energy storage unit, directly impacts the overall vehicle safety performance. As the fundamental building block of the battery pack, the accurate modeling of the cell's mechanical behavior is crucial for assessing the battery pack's safety under extreme conditions such as collisions. Therefore, establishing a cell model that accurately reflects the cell's mechanical behavior is an important engineering design challenge. Summary of the Invention

[0003] One objective of this application is to provide a method for determining a battery cell model, so as to establish a battery cell model that can accurately reflect the mechanical behavior of the battery cell. A second objective of this application is to provide a device for determining a battery cell model. A third objective of this application is to provide an electronic device. A fourth objective of this application is to provide a computer-readable storage medium. A fifth objective of this application is to provide a computer program product.

[0004] To achieve the above objectives, the technical solution adopted in this application is as follows:

[0005] This application provides a method for determining a battery cell model, including: acquiring target information of the battery cell; the target information of the battery cell includes the size information of the battery cell, multiple sets of extrusion test information, and model information of an initial battery cell model; determining the mesh information of a grid model of the battery cell based on the size information of the battery cell; the mesh information of the grid model includes first mesh information of the battery cell shell and second mesh information of the battery cell core; performing preprocessing operations on multiple sets of extrusion test information to determine target extrusion test information; the preprocessing operations include at least one of the following: duplicate data removal operation, data filtering operation, and data optimization operation; updating the model information of the initial battery cell model based on the first mesh information, the second mesh information, and the target extrusion test information to obtain the target battery cell model; wherein, the step of updating the model information of the initial battery cell model based on the first mesh information, the second mesh information, and the target extrusion test information to obtain the target battery cell model includes: updating the model information of the initial battery cell model based on the first mesh information, the second mesh information, and the target extrusion test information to determine the model information of the first battery cell model; and then... xyz The target parameters corresponding to each direction are updated in the model information of the first cell model to obtain the target cell model.

[0006] Based on the aforementioned technical methods, firstly, the grid information of the battery cell's mesh model is determined using the cell's size information from the target information. This mesh model includes first grid information describing the battery cell's casing and second grid information describing the battery cell's core. This parameterizes the battery cell's mesh model, ensuring that the node order, cell orientation, and node position are uniquely determined, preventing variations in the mesh model due to human error. This improves the standardization and generation speed of the mesh model, effectively reducing manual intervention and enhancing modeling efficiency. Secondly, by preprocessing multiple sets of extrusion test information, redundant data is removed, and only the data closest to the actual test results is retained, improving the accuracy and reliability of subsequent modeling processes. Finally, based on the first and second mesh information of the mesh model and the target extrusion test information, the model information of the initial cell model is updated to generate an intermediate first cell model. Subsequently, by updating the target parameters corresponding to all directions into the first cell model, on the one hand, each direction has independent target parameters to describe the mechanical performance of the cell under different extrusion rates, enabling the target cell model to reflect the anisotropy and dynamic effects of the cell, and accurately reflect the mechanical behavior of the cell under different extrusion scenarios, thereby improving the credibility of the simulation results of the target cell model; on the other hand, by iteratively approaching the simulation results of the first cell model, the experimental measurement results are gradually approximated, and the target cell model is finally obtained. This can improve the model accuracy of the target cell model and provide strong support for the safe design of the battery pack.

[0007] Furthermore, the target information includes multiple sets of shell material information. The above method also includes: determining the target shell material information based on the multiple sets of shell material information; minimizing the root mean square error value corresponding to the force information in the target shell material information; determining the curve information of the target stress-strain curve based on the target shell material information; updating the model information of the initial cell model based on the first grid information, the second grid information, and the target extrusion test information, and determining the model information of the first cell model, including: updating the model information of the initial cell model based on the curve information of the target stress-strain curve, the first grid information, the second grid information, and the target extrusion test information, to obtain the model information of the first cell model.

[0008] Based on the aforementioned technical means, firstly, by screening multiple sets of shell material information, the set with the smallest mean square error value corresponding to the force information is selected as the target shell material information, thereby effectively improving the accuracy of the target cell model. Then, based on the target shell material information, the corresponding target stress-strain curve is generated and updated to the model information of the first cell model, so that the final generated target cell model can more accurately describe the deformation characteristics of the cell shell under stress, thereby improving the credibility of the simulation results of the target cell model, providing a scientific basis for the collision safety design of the battery pack, and reducing the risk of misjudgment caused by material parameter errors.

[0009] Furthermore, based on multiple sets of shell material information, the target shell material information is determined, including: determining a first type of shell material information and multiple second type shell material information in the multiple sets of shell material information; the data volume of the first type shell material information is greater than the data volume corresponding to each of the multiple second type shell material information; based on the first type shell material information, interpolation processing is performed on the multiple second type shell material information to obtain multiple third type shell material information; the data volume of the first type shell material information is equal to the data volume corresponding to each of the multiple third type shell material information; based on the first type shell material information and the multiple third type shell material information, the target shell material information is determined.

[0010] Based on the aforementioned technical methods, firstly, by using the large amount of data on the first type of shell material as a benchmark, interpolation is performed on the smaller amount of data on the second type of shell material to generate multiple third type shell material information sets. This ensures that the number of third type shell material information sets is consistent with that of the first type, facilitating unified processing. Then, based on the first type shell material information set and the multiple third type shell material information sets, the optimal target shell material information is determined. This method effectively supplements the low-data-quantity shell material information with the high-data-quantity information, improving overall data quality. Furthermore, the interpolation method fills data gaps, making the shell material information more complete. This improves the accuracy of simulation results of the target cell model under different operating conditions, thereby enhancing the accuracy and reliability of battery pack collision safety assessment.

[0011] Furthermore, based on the target shell material information, the curve information of the target stress-strain curve is determined, including: determining the curve information of the first stress-strain curve based on multiple deformation and force information in the target shell material information; determining the first elastic strain information based on the curve information of the first stress-strain curve; determining the curve information of the first stress-plastic strain curve based on the first elastic strain information and the curve information of the first stress-strain curve; and determining the curve information of the target stress-strain curve based on the curve information of the first stress-plastic strain curve.

[0012] Based on the aforementioned technical methods, firstly, multiple deformation and force information from the target casing material information are used to determine the first stress-strain curve and the first elastic strain information to distinguish the response characteristics of the cell casing material in the elastic and plastic stages. Next, based on the first elastic strain information and the first stress-strain curve, a first stress-plastic strain curve is constructed to describe the behavior of the cell casing material under permanent deformation. Finally, combining the maximum stress information and the curve information of the first stress-plastic strain curve, the final target stress-strain curve is generated. In this way, on the one hand, by analyzing the material properties of the cell casing in stages, the model's ability to characterize complex mechanical behaviors can be improved; on the other hand, the target stress-strain curve can accurately describe the mechanical response of the cell casing under different loading conditions, enhancing the predictive ability of the target cell model, thereby effectively supporting the collision safety assessment of the battery pack during the design phase.

[0013] Furthermore, the target parameters include target strain-stress information; xyz The target parameters corresponding to each direction are updated in the model information of the first cell model to obtain the target cell model, including: [details about the target cell model]. xyz In each direction, within each iteration, multiple sets of first-iteration strain-stress information are determined; wherein, the multiple sets of first-iteration strain-stress information include multiple preset sets of first strain-stress information, the first strain-stress information includes multiple preset first strain information, and multiple first stress information determined based on a first range; the first strain information corresponds to the first stress information; for... xyz In each direction, multiple sets of first-iteration strain-stress information are updated into the model information of the first cell model. Multiple sets of first-deformation-force information are obtained by running the first cell model. xyz For each direction, based on multiple sets of preset first strain-stress information corresponding to the next iteration round, and multiple sets of first deformation-force information and multiple sets of first iteration strain-stress information corresponding to the current iteration round, multiple sets of first iteration strain-stress information corresponding to the next iteration round are determined until the first iteration termination condition is met; for xyz In each direction, based on multiple sets of first deformation-force information and fourth deformation-force information corresponding to all iteration rounds, the target strain-stress information is determined from multiple sets of first iteration strain-stress information corresponding to all iteration rounds; the mean square error between the first deformation-force information and the fourth deformation-force information corresponding to the target strain-stress information is minimized, and the fourth deformation-force information is obtained from the extrusion experiment of the battery cell at the second type of extrusion rate; xyzThe target strain-stress information corresponding to each direction is updated into the model information of the first cell model to obtain the target cell model.

[0014] Based on the aforementioned technical means, targeting xyz In each direction, multiple sets of first-iteration strain-stress information are generated in each iteration and applied to the first cell model. Simulation of the first cell model yields the first deformation-force information corresponding to each direction. When a set termination condition is met, the target strain-stress information with the highest fit to the experimental data is selected as the target parameter by comparing the differences between the simulation results of the first cell model across all iterations. xyz The target strain-stress information corresponding to each direction is updated in the first cell model to form the final target cell model. In this way, on the one hand, automatic parameter optimization can be achieved, reducing the time cost of human trial and error; on the other hand, by iteratively approaching the optimal solution, the accuracy and stability of the target cell model are improved.

[0015] Furthermore, based on the preset multiple sets of first strain-stress information corresponding to the next iteration round, and the multiple sets of first deformation-force information and multiple sets of first iterative strain-stress information corresponding to the current iteration round, the multiple sets of first iterative strain-stress information corresponding to the next iteration round are determined, including: determining the third strain-stress information based on the multiple sets of first deformation-force information, the multiple sets of first iterative strain-stress information, and multiple preset first approximation models; and determining the preset multiple sets of first strain-stress information corresponding to the next iteration round and the third strain-stress information corresponding to the current iteration round as the multiple sets of first iterative strain-stress information corresponding to the next iteration round.

[0016] Based on the above technical means, multiple first approximation models are introduced to predict multiple sets of first-iteration strain-stress information in the current iteration, and the third strain-stress information is determined based on the predicted multiple sets of second-deformation-force information and multiple sets of first-deformation-force information, and applied to the next iteration. This method can accelerate the optimization process, reduce unnecessary computation, and thus improve the computational efficiency of the target strain-stress information.

[0017] Furthermore, based on multiple sets of first deformation-force information, multiple sets of first iterative strain-stress information, and multiple preset first approximation models, the third strain-stress information is determined, including: inputting multiple sets of first iterative strain-stress information into multiple preset first approximation models respectively, and determining multiple sets of second deformation-force information corresponding to each of the multiple first approximation models; based on the multiple sets of second deformation-force information corresponding to each of the multiple first approximation models, and the multiple sets of first deformation-force information, determining a first target approximation model from the multiple first approximation models; minimizing the mean square error between the multiple sets of second deformation-force information and the multiple sets of first deformation-force information corresponding to the first target approximation model; and using the multiple sets of second iterative strain-stress information as the first target approximation model. The input is used for iterative calculation, and multiple sets of third deformation-force information are obtained through the first objective approximation model until the second iteration termination condition of the first objective approximation model is met. Among them, the multiple sets of second iteration strain-stress information include multiple sets of second strain-stress information, which include multiple preset first strain information and multiple second stress information determined based on a second range. Based on the multiple sets of third deformation-force information and fourth deformation-force information corresponding to all iteration rounds, the third strain-stress information is determined from the multiple sets of second iteration strain-stress information corresponding to all iteration rounds. The mean square error between the third deformation-force information and the fourth deformation-force information corresponding to the third strain-stress information is minimized.

[0018] Based on the above technical means, firstly, the strain-stress information of the first iteration of the current iteration is input into multiple first approximation models to generate corresponding second deformation-force information; then, by comparing the difference between the second deformation-force information output by each approximation model and the actual simulation results (first deformation-force information), the best-performing first target approximation model is selected for parameter optimization of strain-stress information; finally, the third strain-stress information is determined based on the first target approximation model. By gradually approaching the optimal solution through this iterative method, the accuracy and efficiency of strain-stress information parameter optimization are improved.

[0019] Furthermore, the target parameters include target strain rate-scaling factor information; xyz The target parameters corresponding to each direction are updated in the model information of the first cell model to obtain the target cell model, including: [details about the target cell model]. xyz In each direction, within each iteration, multiple sets of first-iteration strain rate-scaling coefficient information are determined; wherein, the multiple sets of first-iteration strain rate-scaling coefficient information include multiple preset sets of first strain rate-scaling coefficient information, the first strain rate-scaling coefficient information includes multiple preset first strain rate information, and multiple first scaling coefficient information determined based on a third range; the first scaling coefficient information corresponds to the first strain rate information; for... xyzIn each direction, multiple sets of first-iteration strain rate-scaling factor information are updated to the model information of the first cell model. Through the first cell model, multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates are obtained; for xyz For each direction, based on the preset multiple sets of first strain rate-scaling coefficient information corresponding to the next iteration round, as well as the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the current iteration round and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the next iteration round are determined until the third iteration termination condition is met; for xyz In each direction, based on multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates in all iteration rounds, the target strain rate-scaling coefficient information is determined from multiple sets of first-iteration strain rate-scaling coefficient information corresponding to all iteration rounds; the sum of the mean square errors between the multiple fifth deformation-force information under multiple first-type extrusion rates corresponding to the target strain rate-scaling coefficient information and the multiple sixth deformation-force information under multiple first-type extrusion rates is minimized; the multiple sixth deformation-force information is obtained by extruding the battery cell through extrusion experiments at multiple first-type extrusion rates; xyz The target strain rate-scaling factor information corresponding to each direction is updated into the model information of the first cell model to obtain the target cell model.

[0020] Based on the aforementioned technical methods, multiple sets of first-iteration target strain rate-scaling coefficient information are generated in each iteration round and applied to the first cell model. Simulation using the first cell model yields fifth deformation-force information corresponding to multiple first-type extrusion rates. When the set termination condition is met, the target strain rate-scaling coefficient information with the highest fit to the experimental data is selected as the target parameter by comparing the differences between the simulation results of the first cell model across all iteration rounds. xyz The target strain rate-scaling factor information corresponding to each direction is updated in the first cell model to form the final target cell model. In this way, on the one hand, automatic parameter optimization can be achieved, reducing the time cost of human trial and error; on the other hand, by iteratively approaching the optimal solution, the accuracy and stability of the target cell model are improved.

[0021] Furthermore, based on the preset multiple sets of first strain rate-scaling coefficient information corresponding to the next iteration round, and the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the current iteration round and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the next iteration round are determined, including: based on the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, the multiple sets of first iteration strain rate-scaling coefficient information, and the preset multiple second approximation models, the third strain rate-scaling coefficient information is determined; the preset multiple sets of first strain rate-scaling coefficient information corresponding to the next iteration round and the third strain rate-scaling coefficient information corresponding to the current iteration round are determined as the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the next iteration round.

[0022] Based on the above technical means, by introducing multiple second approximation models to predict multiple sets of first iteration strain rate-scaling factor information in the current iteration, and applying the predicted third strain rate-scaling factor information to the next iteration, the optimization process can be accelerated, unnecessary computation can be reduced, and thus the computational efficiency of target strain-stress information can be improved.

[0023] Furthermore, based on multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, multiple sets of first-iteration strain rate-scaling coefficient information, and multiple preset second approximation models, the third strain rate-scaling coefficient information is determined, including: inputting multiple sets of first-iteration strain rate-scaling coefficient information into multiple preset second approximation models to determine multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates; based on the multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates under multiple second approximation models, and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, determining a second target approximation model from the multiple second approximation models; the sum of the mean square errors between the multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates in the second target approximation model is minimized; and using multiple sets of second-iteration strain rate-scaling coefficient information as input to the second target approximation model. Iterative calculations are performed to obtain multiple sets of eighth deformation-force information corresponding to multiple first-type extrusion rates through the second objective approximation model, until the fourth iteration termination condition of the second objective approximation model is met. The multiple sets of second-iteration strain rate-scaling coefficient information include multiple sets of second strain rate-scaling coefficient information, which in turn include multiple preset first strain rate information and multiple second scaling coefficient information determined based on the fourth range. Based on the multiple sets of eighth deformation-force information corresponding to multiple first-type extrusion rates in all iteration rounds, and the multiple sixth deformation-force information under multiple first-type extrusion rates, a third strain rate-scaling coefficient information is determined from the multiple sets of second-iteration strain rate-scaling coefficient information corresponding to all iteration rounds. The sum of the root mean square errors between the multiple eighth deformation-force information under multiple first-type extrusion rates corresponding to the third strain rate-scaling coefficient information and the multiple sixth deformation-force information under multiple first-type extrusion rates is minimized.

[0024] Based on the aforementioned technical means, firstly, the strain rate-scaling coefficient information of the first iteration of the current iteration is input into multiple second approximation models to generate multiple seventh deformation-force information under multiple first-type extrusion rates; then, by comparing the differences between the seventh deformation-force information under multiple first-type extrusion rates output by each second approximation model and the actual simulation results (fifth deformation-force information under multiple first-type extrusion rates), the second target approximation model with the best performance is selected for parameter optimization of the strain rate-scaling coefficient information; finally, the third strain rate-scaling coefficient information is determined based on the second target approximation model. By gradually approximating the optimal solution through this iterative method, the accuracy and efficiency of strain rate-scaling coefficient information parameter optimization are improved.

[0025] Furthermore, the mesh information includes node information and element information; the size information includes cell shell information, expected size information of the shell mesh, thickness information corresponding to multiple faces of the shell, expected size information of the core mesh, and core information; based on the size information of the cell, the mesh information of the cell mesh model is determined, including: based on the cell shell information, expected size information of the shell mesh, and thickness information corresponding to multiple faces, determining the first node information of each node in multiple faces, and the first element information of each element in multiple faces; based on the expected size information of the core mesh, core shell information, and first node information of each node in multiple faces, determining the second node information of each node in the core, and the second element information of each element in the core; based on the first node information corresponding to all nodes in multiple faces, the first element information corresponding to all elements in multiple faces, the second node information corresponding to all nodes in the core, and the second element information corresponding to all elements in the core, the mesh information of the mesh model is determined.

[0026] Based on the aforementioned technical methods, firstly, based on the cell casing information, the expected dimensions of the casing mesh, and the thickness information corresponding to each of the multiple faces, the first node information and the first element information of each face of the casing are generated. Then, based on the core information and the expected dimensions of the core mesh, the second node information and the second element information inside the core are generated. Finally, the mesh information of the casing and the core are integrated to form the complete mesh information of the cell's mesh model. This approach ensures the accuracy of the mesh model's structure, avoiding modeling deviations caused by human design errors. Furthermore, the standardized mesh generation process improves the modeling efficiency and consistency of the mesh model.

[0027] Furthermore, the node information includes node number information and node location information; the element information includes element number information; based on the cell casing information, the expected size information of the casing mesh, and the thickness information corresponding to multiple faces, the first node information of each node in multiple faces and the first element information of each element in multiple faces are determined, including: based on the cell casing information, the expected size information of the casing mesh, and the thickness information corresponding to multiple faces, the first node number information of each node in multiple faces is determined; based on the cell casing information, the expected size information of the casing mesh, the thickness information corresponding to multiple faces, and the first node number information corresponding to all nodes in multiple faces, the first element number information of each element in multiple faces is determined; the first element number information includes the first sub-number information used to identify the element, and the first node number information corresponding to the nodes constituting the element.

[0028] Based on the above technical means, by defining the first node information of each node and the first cell information of each cell in the shell mesh, the parameterization of the shell mesh is improved and the management of the shell mesh is simplified. On the one hand, this facilitates the subsequent modification and expansion of the shell mesh; on the other hand, by establishing the first node information and the first cell information of the shell mesh, it helps to improve the readability and maintainability of the shell mesh.

[0029] Furthermore, the target extrusion test data includes xyz The target time-deformation-force information for each direction, and the target deformation-force information for each direction; xyz Directions include x direction, y direction and z Direction; Extrusion test information includes xyz The first time-deformation-force information for each direction; preprocessing multiple sets of extrusion test information to determine the target extrusion test information, including: for each set of first time-deformation-force information in each direction, performing duplicate data removal based on the deformation information in the first time-deformation-force information to obtain second time-deformation-force information; for each direction, performing data filtering based on the force information in multiple sets of second time-deformation-force information to determine the target time-deformation-force information; the mean square error value corresponding to the force information in the target time-deformation-force information is minimized; for each direction, performing data optimization on the target time-deformation-force information to determine the target deformation-force information; based on xyz The target time-deformation-force information and target deformation-force information corresponding to each direction are used to determine the target extrusion test information.

[0030] Based on the above technical means, by deduplicating, filtering and optimizing multiple sets of extrusion test information, the final target extrusion test information used is ensured to have high representativeness and stability. On the one hand, this can reduce the impact of invalid or noisy data on the establishment process of the target cell model. On the other hand, by using the optimized data as the input for training the target cell model, the accuracy and reliability of the target cell model are improved.

[0031] Furthermore, the target time-deformation-force information includes first sub-target time-deformation-force information corresponding to multiple first-type extrusion rates, and second sub-target time-deformation-force information corresponding to second-type extrusion rates; the first-type extrusion rate is much larger than the second-type extrusion rate; data optimization operations are performed on the target time-deformation-force information to determine the target deformation-force information, including: for each first-type extrusion rate, based on the maximum force information in the first sub-target time-deformation-force information corresponding to the first-type extrusion rate, normalizing the first sub-target time-deformation-force information to determine the ninth deformation-force information; based on the ninth deformation-force information and a first preset quantity, determining the first range sum; based on the maximum force information in the second sub-target time-deformation-force information, normalizing the second sub-target time-deformation-force information to determine the tenth deformation-force information; based on the tenth deformation-force information and the first preset quantity, determining the second range sum; based on multiple first range sums, multiple ninth deformation-force information, tenth deformation-force information, and second range sums, determining the target deformation-force information.

[0032] Based on the aforementioned technical means, by normalizing and performing range analysis on the extrusion test information, the extrusion test information under different extrusion rates is quantitatively evaluated, thereby determining the target deformation-force information under different extrusion rates. On the one hand, normalization can eliminate the scale differences between data under different test conditions and improve the comparability of data; on the other hand, range analysis can identify areas with large data fluctuations, thereby taking targeted optimization measures to improve the quality and stability of the data.

[0033] Furthermore, based on multiple sums of first ranges, multiple ninth and tenth deformation-force information, and a sum of second ranges, the target deformation-force information is determined, including: determining the data stability of multiple ninth deformation-force information based on multiple sums of first ranges and second ranges; if the data stability of multiple ninth deformation-force information meets the target condition, the target deformation-force information is determined based on a second preset quantity, multiple ninth deformation-force information, and tenth deformation-force information; if the data stability of multiple ninth deformation-force information does not meet the target condition, the multiple ninth deformation-force information is smoothed to obtain multiple eleventh deformation-force information; for each eleventh deformation-force information, the twelfth deformation-force information is determined based on the maximum deformation information in the eleventh deformation-force information, the second preset quantity, and the eleventh deformation-force information; the thirteenth deformation-force information is determined based on the maximum deformation information in the tenth deformation-force information, the second preset quantity, and the tenth deformation-force information; and the target deformation-force information is determined based on multiple twelfth and thirteenth deformation-force information.

[0034] Based on the aforementioned technical means, by evaluating data stability based on multiple first range sums and second range sums, and selecting different data processing strategies according to the stability results, unreliable data can be effectively filtered out, thereby improving the model accuracy of the target cell model.

[0035] Furthermore, based on the ninth deformation-force information and the first preset quantity, the first range sum is determined, including: selecting multiple fourteenth deformation-force information from the ninth deformation-force information according to the first preset quantity, and determining the range of force information in each fourteenth deformation-force information; summing all the ranges to determine the first range sum.

[0036] Based on the above technical means, by setting a fixed sampling interval, samples are extracted from the ninth deformation-force information and its range is calculated to evaluate the data fluctuation. In this way, on the one hand, the data stability of the ninth deformation-force information can be quantitatively measured; on the other hand, by sampling at a fixed interval, the consistency and comparability of the analysis of the ninth deformation-force information are ensured.

[0037] Furthermore, based on the first grid information, the second grid information, and the target extrusion test information, the model information of the initial cell model is updated, and the model information of the first cell model is determined, including: determining target stop information based on the first grid information, cell casing information, and target extrusion test information; the target stop information is used to control the stopping operation of the target cell model; determining pressure head position information based on the first grid information; the pressure head position information is used to characterize the position of the pressure head used for extruding the cell on the cell; and based on the first grid information, the second grid information, the pressure head position information, the target stop information, and the target extrusion test information... xyz The target deformation-force information in each direction is used to update the model information of the initial cell model, thus obtaining the model information of the first cell model.

[0038] Based on the above technical means, by setting target stop information and pressure head position information and updating them in the model information of the initial cell model, the model accuracy of the target cell model can be improved, thereby improving the simulation efficiency and reliability of the target cell model, and further supporting the safety assessment and optimization of the battery pack in the design stage.

[0039] Furthermore, based on the first grid information, cell casing information, and target extrusion test information, target stopping information is determined, including: based on the first grid information and cell casing information, determining... xyz The information includes the third node number for each direction; the cell casing information includes the cell's length, height, and thickness; the third node number is related to the cell's position within the specified range. xyzThe numbers of the nearest nodes at the center points of the surfaces corresponding to the directions; based on the cell thickness information in the cell casing information, and the target extrusion test information... x The maximum deformation value in the target deformation-force information in the direction is used to determine the first difference; based on the length information of the battery cell in the battery cell casing information, and the target extrusion test information... y The second difference is determined by the maximum deformation value in the target deformation-force information in the direction; the cell height information in the cell casing information is compared with the target compression test information. z The maximum deformation value in the target deformation-force information in the direction is used to determine the third difference; based on the first difference, second difference, third difference, and... xyz The third node number information corresponding to each direction is used to determine the target stopping information.

[0040] Based on the above technical means, target stopping information is generated by multi-directional difference calculation based on the first grid information, cell shell information and target extrusion test information. This can effectively determine the running stopping conditions of the target cell model in different directions and avoid excessive extrusion of the cell, which could cause excessive deformation of the cell.

[0041] Furthermore, based on the first grid information, the pressure head position information is determined, including: based on the first grid information, determining the pressure head's position within the grid. xyz The position information of the target nodes on the surface of the shell corresponding to each direction; the target nodes are used to represent the center of the surface; the position information of the pressure head is determined based on the position information of the target nodes corresponding to all directions.

[0042] Based on the above technical means, the position of the pressure head is determined by defining the target node and combining the position information of the target node from multiple directions. This operation method can improve the simulation accuracy of the cell model when it is subjected to external forces in multiple directions, thereby making the evaluation of the mechanical performance of the cell model more reliable.

[0043] A device for determining a battery cell model includes: an acquisition module for acquiring target information of the battery cell; the target information of the battery cell includes the size information of the battery cell, multiple sets of extrusion test information, and model information of an initial battery cell model; a first determination module for determining the mesh information of a mesh model of the battery cell based on the size information of the battery cell; the mesh information of the mesh model includes first mesh information of the battery cell shell and second mesh information of the battery cell core; a second determination module for performing preprocessing operations on the multiple sets of extrusion test information to determine target extrusion test information; the preprocessing operations include at least one of the following: duplicate data removal operation, data filtering operation, and data optimization operation; an update module for updating the model information of the initial battery cell model based on the first mesh information, the second mesh information, and the target extrusion test information to obtain the target battery cell model; wherein, a first update unit is used for updating the model information of the initial battery cell model based on the first mesh information, the second mesh information, and the target extrusion test information to determine the model information of the first battery cell model; a second obtaining unit is used for... xyz The target parameters corresponding to each direction are updated in the model information of the first cell model to obtain the target cell model.

[0044] An electronic device includes a memory and a processor, the memory storing a computer program that can run on the processor, the processor executing the program to implement some or all of the steps in the above method.

[0045] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements some or all of the steps in the above-described method.

[0046] A computer program product comprising a computer program or instructions, wherein when the computer program or instructions are executed by a processor, some or all of the steps in the above method are performed.

[0047] The beneficial effects of this application are:

[0048] (1) First, the grid information of the battery cell's mesh model is determined by using the cell's size information in the target information. This mesh model includes first grid information describing the cell's shell and second grid information describing the cell's core. This parameterizes the battery cell's mesh model, ensuring that the node order, element direction, and node position of the mesh model are uniquely determined. This prevents differences in the mesh model due to human error, improving the standardization of the mesh model and its generation speed. Second, by preprocessing multiple sets of extrusion test information, redundant data is removed and the data closest to the actual test results is retained, thereby improving the accuracy and reliability of subsequent modeling processes. Finally, based on the first grid information, second grid information, and target extrusion test information, the model information of the initial battery cell model is updated, generating a target battery cell model that more closely reflects the actual mechanical response. This effectively reduces human intervention and improves modeling efficiency, while also significantly improving the accuracy and applicability of the target battery cell model, providing strong support for the safety design of electric vehicle battery packs.

[0049] (2) Improve the credibility of the simulation results of the target cell model so as to provide a scientific basis for the collision safety design of the battery pack and reduce the risk of misjudgment caused by material parameter errors.

[0050] (3) By defining the first node information of each node and the first element information of each element in the shell mesh, the parameterization of the shell mesh is improved and the management of the shell mesh is simplified. This makes it easier to modify and extend the shell mesh in the future. On the other hand, by establishing the first node information and the first element information of the shell mesh, the readability and maintainability of the shell mesh are improved.

[0051] (4) First, the model information of the initial cell model is updated based on the first grid information, the second grid information, and the target extrusion test information to generate an intermediate state first cell model. Then, by updating the target parameters in the first cell model, on the one hand, each direction has independent material parameters to reflect the mechanical properties of the cell under different extrusion rates, so that the target cell model can reflect the anisotropy and dynamic effects of the cell; on the other hand, the simulation results of the first cell model are gradually approximated to the experimental measurement results through iteration, and finally the target cell model is obtained, which can improve the model accuracy of the target cell model. Attached Figure Description

[0052] Figure 1 A schematic diagram of the implementation process of the method for determining a battery cell model provided in this application. Figure 1 ;

[0053] Figure 2 A schematic diagram of a battery cell casing provided in this application. Figure 1 ;

[0054] Figure 3 A schematic diagram of a battery cell casing provided in this application. Figure 2 ;

[0055] Figure 4 A schematic diagram of a battery cell casing provided in this application. Figure 3 ;

[0056] Figure 5 A schematic diagram of a battery cell casing provided in this application. Figure 4 ;

[0057] Figure 6 A schematic diagram of a battery cell casing provided in this application. Figure 5 ;

[0058] Figure 7 A schematic diagram of a battery cell casing provided in this application. Figure 6 ;

[0059] Figure 8 A schematic diagram of a battery cell casing provided in this application. Figure 7 ;

[0060] Figure 9 A schematic diagram of a battery cell core provided in this application;

[0061] Figure 10 A schematic diagram of the implementation process of the method for determining a battery cell model provided in this application. Figure 2 ;

[0062] Figure 11 A schematic diagram of the implementation process of the method for determining a battery cell model provided in this application. Figure 3 ;

[0063] Figure 12 A schematic diagram of the implementation process of the method for determining a battery cell model provided in this application. Figure 4 ;

[0064] Figure 13 A schematic diagram of the implementation process of the method for determining a battery cell model provided in this application. Figure 5 ;

[0065] Figure 14 A schematic diagram of the implementation process of the method for determining a battery cell model provided in this application. Figure 6 ;

[0066] Figure 15 A schematic diagram of the implementation process of the method for determining a battery cell model provided in this application. Figure 7 ;

[0067] Figure 16A schematic diagram of the implementation process of the method for determining a battery cell model provided in this application. Figure 8 ;

[0068] Figure 17 A schematic diagram of the implementation process of the method for determining a battery cell model provided in this application. Figure 9 ;

[0069] Figure 18 This is a schematic diagram of the structural composition of a device for determining a battery cell model as proposed in this application.

[0070] It should be noted that the terms "first" and "second" mentioned above are only used to distinguish between different options and do not represent the degree of superiority or inferiority of the options or their priority in the implementation process. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0072] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. Therefore, the illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0073] This application proposes a method for determining a battery cell model. This method can be executed by an electronic device, such as a computer or server, and this application does not limit the scope of the method. Figure 1 As shown, the method may include steps S100 to S130:

[0074] Step S100: Obtain the target information of the battery cell; the target information of the battery cell includes the size information of the battery cell, multiple sets of extrusion test information and the model information of the initial battery cell model;

[0075] In some implementations, the target information for a battery cell may refer to the size information of a single battery cell, multiple sets of extrusion test information for a single battery cell, and model information of an initial battery cell model for a single battery cell. The size information of a single battery cell can be obtained by measuring the physical structure of that single battery cell; the multiple sets of extrusion test information for a single battery cell can be obtained by... x direction, y direction and z The direction was measured when the individual cell was subjected to a compression test.

[0076] In some implementations, the cell size information, multiple sets of extrusion test information, and the model information of the initial cell model are stored in different files. By performing a read operation on all files, the target information of the cell can be obtained.

[0077] For example, the size information of the battery cell can be pre-stored in a cell size location table, and the cell size information can be obtained by reading the cell size location table. Similarly, multiple sets of compression test information can be pre-stored in a compression test data table, and multiple sets of compression test information can be obtained by reading the compression test data table.

[0078] In some implementations, the cell's dimensions, multiple sets of extrusion test data, and the initial cell model information are stored in the same file. By reading this file, the target information of the cell can be obtained. The cell's dimensions are used to define its geometry and may include key parameters describing the cell's overall shape and internal structure.

[0079] In some implementations, the cell's dimensional information includes cell length, cell thickness, cell height, front thickness of the cell casing, back thickness of the cell casing, left side thickness of the cell casing, right side thickness of the cell casing, top thickness of the cell casing, bottom thickness of the cell casing, length of the internal coil, thickness of the internal coil, height of the internal coil, desired size of the cell casing mesh, desired size of the internal coil mesh, and the first node of the cell mesh. x , y , z Coordinate values.

[0080] Multiple sets of extrusion test information refer to the information on the battery cell under pressure. x , y , z Experimental data recorded after applying extrusion loads at different extrusion rates (quasi-static and dynamic) in three directions are used to characterize the mechanical response characteristics of the battery cell under different extrusion directions and rates. In some embodiments, multiple sets of extrusion test information can be determined based on repeated experiments. Each set of extrusion test information includes multiple ninth data pairs corresponding to each direction, and each ninth data pair consists of time information, deformation information, and force information. For example, multiple sets of extrusion test information may refer to three sets of extrusion test information. x Multiple sets of extrusion test information in different directions can be characterized as Multiple sets of extrusion test information in the y direction can be characterized as , z Multiple sets of extrusion test information in different directions can be characterized as ,in, o=1，2，3 , indicating 3 sets of repeated trials; k=1，2，3, indicating three different extrusion rates; g This indicates that there are g data points in each test.

[0081] The model information of the initial cell model refers to the preliminary cell model built based on experience or existing data before optimization.

[0082] Step S110: Based on the size information of the battery cell, determine the mesh information of the battery cell's mesh model; the mesh information of the mesh model includes the first mesh information of the battery cell's casing and the second mesh information of the battery cell's core.

[0083] Here, a mesh model is a digital representation consisting of a continuous geometric space divided into a finite number of discrete units (such as triangles, tetrahedrons, etc.) and nodes (vertices of the units). Nodes are the basic points in the mesh model, and units are geometric shapes (such as triangles, quadrilaterals, hexahedrons, etc.) formed by connecting nodes.

[0084] In some implementations, the mesh information may include, but is not limited to, node information and cell information. Node information may include node numbering and node location information, while cell information may include cell numbering and the node numbering of the nodes constituting that cell. For example, if the battery cell casing is modeled using quadrilateral cells, the nodes constituting that cell may be N1, N2, N3, and N4. If the battery cell core is modeled using hexahedral cells, the nodes constituting that hexahedral cell may be N1, N2, N3, N4, N5, N6, N7, and N8.

[0085] In some implementations, the grid model of the battery cell includes a first grid model of the casing (i.e., casing grid) and a second grid model of the core (i.e., core grid). It is understood that the first grid information is used to describe the first grid model and the second grid information is used to describe the second grid model.

[0086] It should be noted that the meshing method of the first mesh model can affect the stability and computational efficiency of the cell model. A reasonable mesh density can ensure simulation accuracy without wasting computational resources. Since the structure of the core has a certain hierarchy and continuity, when constructing the second mesh model, it is necessary to ensure that the number of mesh nodes on each page is consistent and that the nodes on the left and right sides correspond one-to-one, so as to prevent mesh distortion or discontinuity during the mesh construction process.

[0087] Step S120: Perform preprocessing operations on multiple sets of extrusion test information to determine the target extrusion test information; the preprocessing operations include at least one of the following: duplicate data removal, data filtering, and data optimization.

[0088] Understandably, multiple sets of extrusion test data may contain duplicates, outliers, or low-correlation data points. Therefore, preprocessing of these multiple sets of extrusion test data is necessary to obtain high-quality target extrusion test data, thereby improving the accuracy of the cell model. Specifically, the duplicate data removal operation removes redundant data generated from multiple measurements at the same time point, retaining only one valid data point. The data filtering operation selects the set of data that best approximates the actual physical behavior based on the root mean square error or other statistical indicators, serving as the benchmark for subsequent analysis. The data optimization operation interpolates and smooths the filtered data, making it more consistent with the mechanical response characteristics of the material and reducing the impact of test errors.

[0089] Step S130: Based on the first grid information, the second grid information, and the target extrusion test information, update the model information of the initial cell model to obtain the target cell model.

[0090] In some implementations, the target cell model is obtained by updating the first grid information, the second grid information, and the target extrusion test information to the corresponding positions in the model information of the initial cell model.

[0091] Understandably, the target cell model not only contains accurate geometric mesh information, but also integrates optimized material parameters (such as target extrusion test information), which can more accurately predict the mechanical response of the cell under various working conditions. This allows the target cell model to be used in fields such as battery pack collision safety design, structural optimization, and performance evaluation. In turn, the application of the target cell model can improve design efficiency and reduce experimental costs.

[0092] In this embodiment, firstly, the grid information of the battery cell's mesh model is determined using the cell's size information from the target information. This mesh model includes first grid information describing the cell's casing and second grid information describing the cell's core, thus parameterizing the cell's mesh model. This ensures that the node order, cell orientation, and node position of the mesh model are uniquely determined, preventing variations due to human error and improving the standardization and generation speed of the mesh model. Secondly, by preprocessing multiple sets of extrusion test information, redundant data is removed, and only the data closest to the actual test results is retained, improving the accuracy and reliability of subsequent modeling processes. Finally, based on the first grid information, the second grid information, and the target extrusion test information, the initial cell model's model information is updated, generating a target cell model that more closely reflects the actual mechanical response. This effectively reduces manual intervention and improves modeling efficiency, while also significantly enhancing the accuracy and applicability of the target cell model, providing strong support for the safe design of battery packs.

[0093] In some embodiments, the target information includes multiple sets of shell material information for the shell. Before step S130, the method further includes steps S140 and S150:

[0094] Step S140: Based on multiple sets of shell material information, determine the target shell material information; the root mean square error value corresponding to the force information in the target shell material information is minimized;

[0095] Here, multiple sets of casing material information refer to the mechanical property data of different materials used in the battery cell casing. In some embodiments, the multiple sets of casing material information can be determined based on multiple repeated tests. Each repeated test generates a set of casing material information, and each set of casing material information includes multiple first data pairs. Each data pair consists of deformation information and force information, and the amount of data in the multiple first data pairs is related to the number of data points in each repeated test. For example, multiple sets of casing material information can refer to 3 sets of casing material information, which are represented as follows: Where o=1, 2, 3, representing 3 sets of repeated trials, and g represents that there are g data points in each test.

[0096] In some embodiments, the shell material information may also include sample size data and the unit system of the sample size data, wherein the sample size data may include, but is not limited to, width, gauge length and thickness.

[0097] In some implementations, multiple sets of housing material information can be obtained by performing multiple tensile tests on the housing of a single cell, with reference to metal material tensile testing standards.

[0098] In some implementations, multiple sets of casing material information are pre-stored in a file. By performing a file read operation, the multiple sets of casing material information for the battery cell can be obtained. For example, multiple sets of casing material information are pre-stored in a battery cell casing material test data table. By reading the battery cell casing material test data table, the multiple sets of casing material information can be obtained.

[0099] It is understandable that each set of shell material information includes multiple first data pairs, and each data pair includes force information and the deformation information corresponding to that force information. The target shell material information is a set of optimal material parameters selected from multiple sets of shell material information. Since the mean square error value corresponding to the force information in the multiple first data pairs of the target shell material information is the smallest, it can be deduced that the data in the target shell material information is compactly distributed, reflecting the stability of the shell material corresponding to the target shell material information.

[0100] Step S150: Based on the target shell material information, determine the curve information of the target stress-strain curve;

[0101] Here, the target stress-strain curve is used to describe the dynamic relationship between stress (internal force per unit area) and strain (deformation per unit length) of the battery cell casing during the stress process. It visually demonstrates the entire process of the casing from elastic deformation to plastic deformation and finally fracture, and is a key basis for evaluating the mechanical properties of the battery cell casing. The curve information of the target stress-strain curve can refer to the data used to plot the target stress-strain curve.

[0102] Understandably, determining the target stress-strain curve information can provide important information for modeling the mechanical behavior of the battery cell. For example, in simulations, the target stress-strain curve will be used to calculate the deformation response of the battery cell in different directions, thereby evaluating the cell's compressive strength and safety.

[0103] Correspondingly, step S130 above can be implemented as follows: based on the curve information of the target stress-strain curve, the first grid information, the second grid information and the target extrusion test information, update the model information of the initial cell model and determine the model information of the first cell model.

[0104] In some implementations, the model information of the first cell model is obtained by updating the curve information of the target stress-strain curve, the first grid information, the second grid information, and the target extrusion test information to the corresponding positions in the model information of the initial cell model.

[0105] It should be noted that, depending on the simplification level of the cell model, it can be determined whether to update the target stress-strain curve information into the initial cell model's model information, thereby obtaining the model information of the first cell model. For example, if the cell model is simplified to consist of multiple parts such as the cell shell and the internal winding core, then multiple sets of extrusion test information need to be obtained; if the cell model is simplified to consist of only one part, then it is not necessary to conduct multiple tensile tests on the cell shell, that is, it is not necessary to determine the target stress-strain curve of the shell.

[0106] In this embodiment, firstly, by filtering multiple sets of shell material information, the set with the smallest mean square error corresponding to the output information is selected as the target shell material information, thereby effectively improving the accuracy of the target cell model. Then, based on the target shell material information, the corresponding target stress-strain curve is generated and updated to the model information of the first cell model, so that the final generated target cell model can more accurately describe the deformation characteristics of the cell shell under stress, thereby improving the credibility of the simulation results of the target cell model, providing a scientific basis for the collision safety design of the battery pack, and reducing the risk of misjudgment caused by material parameter errors.

[0107] In some embodiments, step S140 may further include steps S141 to S143:

[0108] Step S141: Determine the first type of shell material information and multiple second type shell material information from multiple sets of shell material information; the data volume of the first type of shell material information is greater than the data volume corresponding to each of the multiple second type shell material information.

[0109] In some implementations, multiple sets of shell material information may refer to at least two sets of shell material information, wherein each set of shell material information includes multiple first data pairs, and the data amounts of the multiple first data pairs corresponding to the multiple sets of shell material information are different. The shell material information corresponding to the largest data amount is determined as the first type of shell material information. Therefore, the data amount of the multiple first data pairs in the first type of shell material information is greater than the data amount of the multiple first data pairs in the second type of shell material information.

[0110] For example, let's take multiple sets of shell material information as three sets of shell material information for explanation. These three sets of shell material information include first shell material information (multiple first data pairs in the first shell material information include: A1-B1, A2-B2, A3-B3), second shell material information (multiple first data pairs in the second shell material information include: A11-B11, A12-B12, A13-B13, A14-B14), and third shell material information (multiple first data pairs in the third shell material information include: A111-B111, A112-B112, A113-B113, A114-B114, A115-B115). It can be seen that the first type of shell material information can be the third type of shell material information, and multiple second type of shell material information can be the first shell material information and the second shell material information.

[0111] Step S142: Based on the first type of shell material information, interpolate the multiple second type of shell material information to obtain multiple third type of shell material information; the data volume of the first type of shell material information is equal to the data volume corresponding to each of the multiple third type of shell material information.

[0112] Here, interpolation is a numerical method used to estimate the values ​​of unknown data points among known data points to generate a continuous function or data sequence. Understandably, in this application, using the information on the first type of shell material as a reference, interpolation is performed on each piece of information on the second type of shell material, expanding the originally smaller amount of data in the second type of shell material information into a third type of shell material information with the same amount of data as the first type of shell material information. It should be noted that interpolation can improve the overall consistency of the data between the first type of shell material information and multiple pieces of third type shell material information, and can reduce errors and biases caused by data mismatch.

[0113] In some implementations, a target first data pair is obtained from a plurality of first data pairs in the first type of shell material information, wherein the deformation information in the target first data pair is the maximum value among the plurality of first data pairs in the first type of shell material information. Based on the target first data pair, interpolation processing is performed on the plurality of first data pairs in each of the second type of shell material information to obtain the plurality of first data pairs in the third type of shell material information. .

[0114] For example, the multiple first data pairs in the third shell material information include: A111-B111, A112-B112, A113-B113, A114-B114, A115-B115; the multiple first data pairs obtained after interpolating the first shell material information include: A111-B1', A112-B2', A113-B3', A114-B4', A115-B5'; the multiple first data pairs obtained after interpolating the second shell material information include: A111-B11', A112-B12', A113-B13', A114-B14', A115-B15'.

[0115] Step S143: Determine the target shell material information based on the first type of shell material information and multiple third type shell material information.

[0116] In some implementations, for the shell material information corresponding to the first type of shell material information and the shell material information of multiple third type shell material information respectively, the force information in multiple first data pairs in each shell material information is averaged to obtain the data pair corresponding to the first force average. The mean square error is calculated by comparing the force information of multiple first data pairs in each shell material information with the mean value of the first force to obtain the mean square error value corresponding to each shell material information. Based on the mean square error values ​​corresponding to all shell material information, the shell material information corresponding to the minimum mean square error value is determined as the target shell material information.

[0117] In this embodiment, firstly, by using the large amount of first-type shell material information as a benchmark, interpolation processing is performed on the smaller amount of second-type shell material information to generate multiple third-type shell material information. This ensures that the number of third-type shell material information matches that of the first-type shell material information, facilitating unified processing. Then, based on the first-type shell material information and the multiple third-type shell material information, the optimal target shell material information is determined. This method effectively supplements the low-data-volume shell material information with the high-volume shell material information, improving overall data quality. Furthermore, the interpolation method fills data gaps, making the shell material information more complete. This improves the accuracy of simulation results of the target cell model under different operating conditions, thereby enhancing the accuracy and reliability of battery pack collision safety assessment.

[0118] In some embodiments, step S150 may include steps S151 to S154:

[0119] Step S151: Based on multiple deformation and force information in the target shell material information, determine the curve information of the first stress-strain curve;

[0120] Here, deformation information refers to the deformation of the battery cell casing under external force, recorded through tensile tests or other forms of mechanical testing, typically expressed as a change in length or a percentage. Deformation information reflects the reversible or irreversible deformation behavior of the battery cell casing under different stress conditions.

[0121] Force information refers to the external force applied to the casing of a battery cell under the same test conditions. This value is usually expressed in Newtons (N) or kilonewtons (kN) and is used to reflect the battery cell casing's ability to withstand external loads when subjected to external forces.

[0122] The first stress-strain curve includes multiple stress values ​​and multiple strain values ​​corresponding to each stress value. The strain value refers to the dimensionless quantity of the material deformation degree, and the strain value is usually determined by the ratio of the deformation value to the original size of the battery cell. The stress value refers to the internal force per unit area, and the stress value is usually determined by the ratio of the force value to the cross-sectional area of ​​the battery cell.

[0123] In this application, by converting multiple deformation and force information from the collected target shell material information into curve information of the first stress-strain curve, the mechanical response of the battery cell shell under different loads can be described more accurately, thereby improving the accuracy of subsequent simulation modeling.

[0124] Step S152: Determine the first elastic strain information based on the curve information of the first stress-strain curve;

[0125] Here, the first elastic strain information refers to the maximum strain value of the cell casing in the elastic stage of the first stress-strain curve. The elastic stage refers to the deformation range within which the cell casing can completely return to its original shape after the external force is removed. The first elastic strain information usually corresponds to the end of the linear portion of the first stress-strain curve, that is, the critical point before the cell casing begins to enter plastic deformation.

[0126] Understandably, the first elastic strain information can effectively distinguish the elastic and plastic behavior of the cell casing during the stress process, thereby improving the accuracy of the cell model.

[0127] Step S153: Based on the first elastic strain information and the curve information of the first stress-strain curve, determine the curve information of the first stress-plastic strain curve;

[0128] The information of the first stress-plastic strain curve is the result of correcting the information of the first stress-strain curve based on the known information of the first elastic strain.

[0129] In some embodiments, the first elastic strain information is subtracted from the multiple strain information in the first stress-strain curve to obtain the first stress-plastic strain curve. It is understood that the first stress-plastic strain curve is used to describe the stress-strain relationship of the battery cell casing during the plastic deformation stage, i.e., the nonlinear region remaining after removing the elastic portion.

[0130] Step S154: Determine the curve information of the target stress-strain curve based on the curve information of the first stress-plastic strain curve.

[0131] In some implementations, the plastic strain information corresponding to the maximum stress is obtained from the curve information of the first stress-plastic strain curve. ; in minimum strain information (0) and maximum strain information ( Within the specified range, numerical processing is performed on the curve information of the first stress-plastic strain curve to obtain the curve information of the target stress-strain curve. (Where g = 1, 2, ..., 20). The maximum strain information is obtained by extracting the plastic strain information corresponding to the maximum stress from the information of the first stress-plastic strain curve.

[0132] In one example, minimum strain information and maximum strain information can be found. Within the range, a first number of curve information is selected from the curve information of the first stress-plastic strain curve to obtain the curve information of the target stress-strain curve.

[0133] In one example, it can be based on minimum strain information and maximum strain information. Interpolation is performed according to the first quantity (e.g., 18) to obtain the curve information of the target stress-strain curve.

[0134] In this embodiment, firstly, multiple deformation and force information from the target casing material information are used to determine the first elastic strain information to distinguish the response characteristics of the cell casing in the elastic and plastic stages. Next, based on the first elastic strain information and the first stress-strain curve, a first stress-plastic strain curve is constructed to describe the behavior of the cell casing when permanent deformation occurs. Finally, combining the maximum stress information and the curve information of the first stress-plastic strain curve, the final target stress-strain curve is generated. In this way, on the one hand, by analyzing the material properties of the cell casing in stages, the ability of the target cell model to characterize complex mechanical behaviors can be improved; on the other hand, the target stress-strain curve can accurately describe the mechanical response of the cell casing under different loading conditions, improving the predictive ability of the target cell model, thereby effectively supporting the collision safety assessment of the battery pack during the design stage.

[0135] In some embodiments, step S130 may further include steps S131 and S132:

[0136] Step S131: Based on the first grid information, the second grid information, and the target extrusion test information, update the model information of the initial cell model and determine the model information of the first cell model;

[0137] Step S132: ... xyz The target parameters corresponding to the directions are updated in the model information of the first cell model to obtain the target cell model.

[0138] By updating the target parameters of the first cell model, key performance indicators can be precisely adjusted without changing the overall structure, making it more consistent with actual test data. This updating of target parameters significantly improves the fitting effect and generalization ability of the target cell model, thus enabling it to be used more reliably for engineering design and safety assessment.

[0139] In some implementations, the target parameters may include target strain-stress information and / or target strain rate-scaling factor information. The target strain-stress information is key data used to describe the relationship between strain and stress generated within the material when the battery cell is subjected to external loads. Target strain-stress information reflects the mechanical response characteristics of the battery cell in different directions and is fundamental to establishing an accurate battery cell model.

[0140] In some implementations... xyz The target strain-stress information corresponding to each direction includes x Target strain-stress information in the direction y Target strain-stress information in the direction zThe target strain-stress information in the direction includes multiple target strain information and multiple target stress information. There is a one-to-one correspondence between the multiple target strain information and the multiple target stress information. Each target strain information and the first target stress information can form a second data pair.

[0141] In some implementations, x The target strain-stress information in the direction is updated in the model information of the first cell model. y The target strain-stress information in the direction is updated in the model information of the first cell model. z The target strain-stress information in each direction is updated in the model information of the first cell model. The method for determining the target strain-stress information in each direction is the same. For the specific implementation process, please refer to steps S1321 to S1325 below.

[0142] In some implementations... xyz The target strain rate-scaling factor information for each direction includes x Target strain rate-scaling factor information in the direction y Target strain rate-scaling factor information in the direction and z The target strain rate-scaling factor information includes multiple target strain rates and multiple target scaling factors. There is a one-to-one correspondence between the multiple target strain rates and multiple target scaling factors, and each target strain rate and each target scaling factor can form a third data pair. Here, strain rate refers to the strain that occurs per unit time in the battery cell during stress, used to describe the response characteristics of the battery cell under dynamic load; the scaling factor is a parameter that adjusts the response of the battery cell behavior at different strain rates, used to reflect the changes in the mechanical properties of the battery cell under high strain rates.

[0143] In some implementations, a correlation coefficient is obtained; if the correlation coefficient is 1, the scaling factor information in the target strain rate-scaling factor information is set to 1. The method for determining the correlation coefficient is described in steps S114 to S116 below. If the correlation coefficient is 0, the method for determining the target strain rate-scaling factor information is described in steps S1326 to S1330 below.

[0144] In some implementations, x The target strain rate-scaling factor information in the direction is updated in the model information of the first cell model. y The target strain rate-scaling factor information in the direction is updated in the model information of the first cell model. zThe target strain rate-scaling factor information in each direction is updated in the model information of the first cell model. The method for determining the target strain rate-scaling factor information in each direction is the same.

[0145] It should be noted that the target strain-stress information and target strain rate-scaling factor information in the same direction are related to the extrusion rate of the battery cell. This extrusion rate includes a first type of extrusion rate and a second type of extrusion rate. The target strain-stress information corresponds to the second type of extrusion rate, and the target strain rate-scaling factor information corresponds to the first type of extrusion rate. The first type of extrusion rate can be used to achieve dynamic extrusion of the battery cell. Dynamic extrusion refers to an extrusion process performed on an object under high-speed deformation conditions, where the system is in a non-equilibrium state, and inertial effects and strain rate sensitivity are significant. The second type of extrusion rate is used to achieve static extrusion of the battery cell. Static extrusion refers to an extrusion process performed on an object under low-speed deformation conditions, where the system is close to equilibrium, and pressure and deformation change uniformly with time. The first type of extrusion rate can be 10-1000 mm / s, and the second type of extrusion rate can be 0.1-10 mm / s.

[0146] It is understandable that in this application, the target parameters in all directions are optimized and adjusted in combination with experimental test results in order to minimize the difference between the simulation results of the target cell model and the actual test results, thereby improving the model accuracy of the target cell model.

[0147] In this embodiment, the model information of the initial cell model is first updated based on the first grid information, the second grid information, and the target extrusion test information to generate an intermediate first cell model. Then, by updating the target parameters corresponding to all directions into the first cell model, on the one hand, each direction has independent target parameters to describe the mechanical properties of the cell under different extrusion rates, enabling the target cell model to reflect the anisotropy and dynamic effects of the cell; on the other hand, through iterative methods, the simulation results of the first cell model gradually approximate the experimental measurement results, ultimately obtaining the target cell model, thus improving the model accuracy of the target cell model.

[0148] In some embodiments, the target parameters include target strain-stress information; step S132 above may include steps S1321 to S1325:

[0149] Step S1321: For xyzIn each direction, in each iteration, multiple sets of first iteration strain-stress information are determined; wherein, the multiple sets of first iteration strain-stress information include multiple preset sets of first strain-stress information, the first strain-stress information includes multiple preset first strain information, and multiple first stress information determined based on a first range; the first strain information corresponds to the first stress information.

[0150] In some implementations, a single set of first strain-stress information includes multiple first strain information and multiple first stress information, with a one-to-one correspondence between the multiple strain information and the multiple stress information, and a third data pair can be formed between a single strain information and a single stress information, that is, a single set of first strain-stress information includes multiple third data pairs.

[0151] In some implementations, the preset plurality of first strain information can be user-defined first strain information at equal or unequal intervals. For example, the plurality of first strain information can be... .

[0152] In some implementations, a plurality of first stress information pieces, the same number as the plurality of first strain information pieces, are selected from a first range. The plurality of first stress information pieces should satisfy a first target selection condition, which may be: It should be noted that the initial range is different in each iteration, and it gradually decreases as the number of iterations increases. For example, in the first iteration, the initial range could be... In the second iteration, the first range can be ,in, f 1 can be the first scaling factor set by the user for each iteration round.

[0153] In some implementations, multiple sets of first strain-stress information can refer to p Group 1 strain-stress information, in which, .

[0154] In some implementations, during the first iteration, multiple sets of preset first strain-stress information are determined as multiple sets of first iterative strain-stress information; in other iterations besides the first iteration, multiple sets of preset first strain-stress information and third strain-stress information obtained from the previous iteration are determined as multiple sets of first iterative strain-stress information.

[0155] Step S1322: For xyz In each direction, multiple sets of first-iteration strain-stress information are updated to the model information of the first cell model, and multiple sets of first deformation-force information are obtained by running the first cell model;

[0156] Here, the first deformation-force information refers to the relationship between the amount of deformation exhibited by the first cell model and the applied external force under specific strain conditions.

[0157] In some implementations, the model information of the first cell model includes a cell extrusion simulation analysis module. During the first iteration, multiple sets of first-iteration strain-stress information include... p The first strain-stress information of the group is copied to the cell extrusion simulation analysis module. p Shares, and p The strain-stress information in the cell extrusion simulation analysis module is sequentially modified to any one of multiple sets of strain-stress information from the first iteration. After modification, the first cell model is run, thereby obtaining... p Group 1 Deformation - Force Information ,in The amount of data represented in each set of deformation-force information.

[0158] In some implementations, in iterations other than the first iteration, multiple sets of first iteration strain-stress information include p The first and third strain-stress information are used to copy the cell extrusion simulation analysis module. p+1 Shares, and p+1 The strain-stress information in the cell extrusion simulation analysis module is sequentially modified to any one of the first and third sets of strain-stress information. After modification, the first cell model is run to obtain... p+1 Group 1 Deformation - Force Information.

[0159] Understandably, the first cell model can obtain a set of initial deformation-force information through the cell extrusion simulation analysis module, therefore... p The cell extrusion simulation analysis module can obtain p Group 1 Deformation - Force Information.

[0160] In some implementations, a set of first iterative strain-stress information corresponds to a set of first deformation-force information. As can be seen from the above description, a set of first iterative strain-stress information includes multiple third data pairs, and multiple fourth data pairs can be obtained through multiple third data pairs. Each fourth data pair is formed by a single deformation information and a single force information. In other words, a set of first deformation-force information includes multiple fourth data pairs.

[0161] Step S1323: For xyzFor each direction, based on the preset multiple sets of first strain-stress information corresponding to the next iteration round, as well as the multiple sets of first deformation-force information and multiple sets of first iteration strain-stress information corresponding to the current iteration round, the multiple sets of first iteration strain-stress information corresponding to the next iteration round are determined until the first iteration termination condition is met.

[0162] Here, the first iteration termination condition can refer to stopping the iteration process when a certain preset standard is reached. In some implementations, the first iteration termination condition can be the maximum number of iterations, or it can be a first error threshold, etc.

[0163] It is understandable that the multiple sets of first-iteration strain-stress information corresponding to the next iteration are determined by the multiple sets of first-iteration deformation-force information corresponding to the current iteration, the multiple sets of first-iteration strain-stress information corresponding to the current iteration, and the multiple sets of first-iteration deformation-stress information preset for the next iteration. This feedback mechanism helps to continuously correct the parameter terms corresponding to the strain-stress information in the first cell model, making the first cell model gradually approach the optimal state. When the preset termination condition (such as the maximum number of iterations or the minimum error threshold) is reached, the iteration process ends, and the obtained target strain-stress information is updated into the first cell model, making the target cell model tend to stabilize and improving the model accuracy of the target cell model.

[0164] In some implementations, after determining multiple sets of strain-stress information for the first iteration corresponding to the next iteration round, steps S1321 to S1322 are executed to perform iterative calculations for the next iteration round.

[0165] Step S1324: For xyz In each direction, based on multiple sets of first deformation-force information and fourth deformation-force information corresponding to all iteration rounds, the target strain-stress information is determined from multiple sets of first iteration strain-stress information corresponding to all iteration rounds; the mean square error between the first deformation-force information and the fourth deformation-force information corresponding to the target strain-stress information is minimized, and the fourth deformation-force information is obtained by extruding the cell at the second type of extrusion rate;

[0166] In some implementations, after stopping the iteration, multiple sets of first deformation-force information obtained in each iteration are acquired; the first mean square error (MSE) value between each set of first deformation-force information and the fourth deformation-force information corresponding to each iteration is calculated to determine the degree of agreement between the simulation results of the first cell model and the extrusion experiment; based on the multiple first MSE values ​​corresponding to the multiple sets of first deformation-force information, a first target MSE value is determined; the first target MSE value is the minimum value among the multiple first MSE values; based on the multiple first target MSE values ​​corresponding to all iterations, a second target MSE value is determined; the second target MSE value is the minimum value among the multiple first target MSE values. It can be understood that the strain-stress information corresponding to this second target MSE value is the target strain-stress information.

[0167] In some implementations, the fourth deformation-force information can be represented as The fourth deformation-force information is obtained by measuring the cell through a compression experiment using the second type of compression rate, where the second type of compression rate is used to achieve static compression of the cell.

[0168] Step S1325: ... xyz The target strain-stress information corresponding to each direction is updated into the model information of the first cell model to obtain the target cell model.

[0169] Here, the target strain-stress information is updated to the strain-stress information section in the cell extrusion simulation analysis module.

[0170] Through the above steps S1321 to S1324, we can obtain... x Target strain-stress information corresponding to the direction y The target strain-stress information corresponding to the z-direction and the target strain-stress information corresponding to the z-direction.

[0171] Understandably, by xyz The target strain-stress information corresponding to each direction is updated to the model information of the first cell model, which can make the target cell model better match the experimental data, realize the optimization and correction of the target cell model, and thus enable the target cell model to more accurately reflect the mechanical response of the cell under various load conditions.

[0172] In this embodiment of the application, for xyzIn each direction, multiple sets of first-iteration strain-stress information are generated in each iteration and applied to the first cell model. Simulation of the first cell model yields the first deformation-force information corresponding to each direction. When a set termination condition is met, the target strain-stress information with the highest fit to the experimental data is selected as the target parameter by comparing the differences between the simulation results of the first cell model across all iterations. xyz The target strain-stress information corresponding to each direction is updated in the first cell model to form the final target cell model. In this way, on the one hand, automatic parameter optimization can be achieved, reducing the time cost of human trial and error; on the other hand, by iteratively approaching the optimal solution, the accuracy and stability of the target cell model are improved.

[0173] In some embodiments, step S1323 may further include steps S200 and S201:

[0174] Step S200: Based on multiple sets of first deformation-force information, multiple sets of first iterative strain-stress information, and multiple preset first approximation models, determine the third strain-stress information;

[0175] Here, the first approximation model is a simplified mathematical model used to predict material behavior. The structure of the first approximation model may include different types such as linear regression, polynomial fitting, and neural networks. Each first approximation model accepts a set of inputs and outputs corresponding prediction results. In this application, the input of the first approximation model is the first iteration strain-stress information, and the output of the first approximation model is the second deformation-force information.

[0176] In some implementations, multiple first approximation models can refer to at least two first approximation models, such as two first approximation models, three first approximation models, or six first approximation models.

[0177] In some implementations, multiple sets of first iterative strain-stress information are input into each first approximation model. Multiple sets of second deformation-force information corresponding to the multiple sets of first iterative strain-stress information can be obtained through each first approximation model. Based on the multiple sets of second deformation-force information and multiple sets of first deformation-force information obtained from all first approximation models, a first target approximation model is determined. Based on the first target approximation model, third strain-stress information is determined.

[0178] Step S201: Determine the preset multiple sets of first strain-stress information corresponding to the next iteration round, and the third strain-stress information corresponding to the current iteration round, as the multiple sets of first iteration strain-stress information corresponding to the next iteration round.

[0179] In some implementations, a first range corresponding to the next iteration round is determined; multiple first stress information is determined based on the first range corresponding to the next iteration round; and a single set of first strain-stress information is determined based on the multiple first stress information and multiple first strain information corresponding to the next iteration round. The first range corresponding to the next round can be determined based on a first scaling factor or can be directly set by the user.

[0180] In this embodiment, multiple first approximation models are introduced to predict multiple sets of first-iteration strain-stress information in the current iteration, and the third strain-stress information is determined based on the predicted multiple sets of second-deformation-force information and multiple sets of first-deformation-force information, and applied to the next iteration. This method can accelerate the optimization process, reduce unnecessary computation, and thus improve the computational efficiency of the target strain-stress information.

[0181] In some embodiments, step S200 may further include steps S2001 to S2004:

[0182] Step S2001: Input multiple sets of first-iteration strain-stress information into multiple preset first approximation models respectively, and determine multiple sets of second deformation-force information corresponding to the multiple first approximation models respectively;

[0183] In some implementations, multiple sets of first-iteration strain-stress information are used as inputs to each first approximation model. Each first approximation model is then used to run through the multiple sets of first-iteration strain-stress information to obtain multiple sets of second-iteration deformation-force information. .

[0184] In some implementations, a set of first iterative strain-stress information corresponds to a set of second deformation-force information. As can be seen from the above description, a set of first iterative strain-stress information includes multiple third data pairs, and multiple fourth data pairs can be obtained through multiple third data pairs. Each fourth data pair is formed by a single deformation information and a single force information. In other words, a set of second deformation-force information includes multiple fourth data pairs.

[0185] Step S2002: Based on the multiple sets of second deformation-force information corresponding to the multiple first approximation models, and the multiple sets of first deformation-force information, determine the first target approximation model from the multiple first approximation models; the mean square error between the multiple sets of second deformation-force information and the multiple sets of first deformation-force information corresponding to the first target approximation model is minimized;

[0186] Here, the first objective approximation model is the optimal model selected from multiple first approximation models. The selection criterion for the first objective approximation model is usually based on minimizing the mean square error between the predicted results of the first approximation model and the simulation results of the first cell model.

[0187] In some implementations, for each first approximation model, the corresponding second deformation-force information of the same third data pair is obtained. and first deformation-force information The second mean square error between the two data points is determined; based on the second mean square error corresponding to each of the third data pairs, the sum of the second mean square errors is determined. Based on the sum of the second mean square errors corresponding to each of the first approximation models, the first approximation model corresponding to the minimum mean square error is determined as the first target approximation model.

[0188] Step S2003: Use multiple sets of second-iteration strain-stress information as input to the first target approximation model for iterative calculation, and obtain multiple sets of third deformation-force information through the first target approximation model until the second iteration termination condition of the first target approximation model is met; wherein, the multiple sets of second-iteration strain-stress information include multiple sets of second strain-stress information, the second strain-stress information includes multiple preset first strain information, and multiple second stress information determined based on the second range;

[0189] Here, the second iteration termination condition can refer to stopping the iteration process when a certain preset standard is reached.

[0190] In this application, the second iteration termination condition may be that the number of iterations reaches a preset number of iterations, or that the mean square error between the third deformation-force information and the fourth deformation-force information predicted by the first target approximation model is less than a preset threshold.

[0191] In some implementations, a second range corresponding to the next iteration round is determined; based on the second range corresponding to the next round, multiple second stress information corresponding to the next iteration round is determined; based on the multiple second stress information corresponding to the next iteration round and multiple first strain information, a single set of second strain-stress information is determined. The second range corresponding to the next round can be determined based on a second scaling factor, or it can be directly set by the user.

[0192] In this application, the second scaling factor may be the same as or different from the first scaling factor, and the second range may be less than or equal to the first range.

[0193] Step S2004: Based on the multiple sets of third deformation-force information and fourth deformation-force information corresponding to all iteration rounds, determine the third strain-stress information from the multiple sets of second iteration strain-stress information corresponding to all iteration rounds; the mean square error between the third deformation-force information and the fourth deformation-force information corresponding to the third strain-stress information is minimized.

[0194] In some implementations, after stopping the iteration, multiple sets of third deformation-force information obtained in each iteration are acquired; the third mean square error (MSE) value between each set of third deformation-force information and the fourth deformation-force information corresponding to each iteration is calculated; based on the multiple MSE values ​​corresponding to the multiple sets of third deformation-force information, a third target MSE value is determined; the third target MSE value is the minimum value among the multiple third MSE values; based on the multiple third target MSE values ​​corresponding to all iterations, a fourth target MSE value is determined; the fourth target MSE value is the minimum value among the multiple third target MSE values. It can be understood that the second iteration strain-stress information corresponding to this fourth target MSE value is the third strain-stress information.

[0195] In this embodiment, firstly, the strain-stress information of the first iteration of the current iteration is input into multiple first approximation models to generate corresponding second deformation-force information; then, by comparing the difference between the second deformation-force information output by each approximation model and the actual simulation results (first deformation-force information), the best-performing first target approximation model is selected for parameter optimization of the strain-stress information; finally, the third strain-stress information is determined based on the first target approximation model. By gradually approximating the optimal solution through this iterative method, the accuracy and efficiency of strain-stress information parameter optimization are improved.

[0196] In some embodiments, the target parameter includes target strain rate-scaling factor information; step S132 above may include steps S1326 to S1330:

[0197] Step S1326: For xyz In each direction, in each iteration, multiple sets of first iteration strain rate-scaling coefficient information are determined; wherein, the multiple sets of first iteration strain rate-scaling coefficient information include multiple preset sets of first strain rate-scaling coefficient information, the first strain rate-scaling coefficient information includes multiple preset first strain rate information, and multiple first scaling coefficient information determined based on the third range; the first scaling coefficient information corresponds to the first strain rate information.

[0198] In some implementations, a single set of first strain rate-scaling factor information includes multiple first strain rate information and multiple first scaling factor information, with a one-to-one correspondence between the multiple strain rate information and the multiple scaling factor information, and a fifth data pair can be formed between a single strain rate information and a single scaling factor information, that is, a single set of first strain rate-scaling factor information includes multiple fifth data pairs.

[0199] In some implementations, the preset plurality of first strain rate information can be user-defined first strain information with equal or unequal intervals. For example, the plurality of first strain rate information can be... .

[0200] In some implementations, a plurality of first scaling factor information, the same number as the plurality of first strain rate information, is selected from the third range. The plurality of first scaling factor information should satisfy a second target selection condition, which may be... It should be noted that the third range is different in each iteration, and it gradually decreases as the number of iterations increases. For example, in the first iteration, the third range could be... In the second iteration, the third range can be ,in, f 3 can be the third scaling factor set by the user for each iteration round.

[0201] In some implementations, multiple sets of first strain rate-scaling factor information can refer to q Group 1 strain-stress information, in which, .

[0202] In some implementations, during the first iteration, multiple sets of preset first strain rate-scaling coefficient information are determined as multiple sets of first iteration strain rate-scaling coefficient information; in other iterations besides the first iteration, multiple sets of preset first strain rate-scaling coefficient information and third strain rate-scaling coefficient information obtained from the previous iteration are determined as multiple sets of first iteration strain rate-scaling coefficient information.

[0203] Step S1327: For xyz In each direction, multiple sets of first-iteration strain rate-scaling factor information are updated to the model information of the first cell model. Through the first cell model, multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates are obtained.

[0204] In some implementations, the model information of the first cell model includes a cell extrusion simulation analysis module. During the first iteration, multiple sets of first iteration strain rate-scaling factor information are included. q The first strain rate-scaling factor information is used to copy the cell extrusion simulation analysis module for each type of first extrusion rate. q Shares, and q The strain rate-scaling factor information in the cell extrusion simulation analysis module was modified sequentially as follows: q Any one of the first iteration strain rate-scaling factor information sets. After modification, control the first cell model to run, thereby obtaining multiple first-type extrusion rates corresponding to the first cell model. q Group 5 Deformation-Force Information.

[0205] For example, multiple first-type extrusion rates can be V 2 andV 3, V The fifth deformation-force information corresponding to 2 can be , V The fifth deformation-force information corresponding to 3 can be .

[0206] In some implementations, in iterations other than the first iteration, multiple sets of first iteration strain rate-scaling factor information include q The first strain rate-scaling factor information and the third strain rate-scaling factor information are copied by the cell extrusion simulation analysis module for each type of first extrusion rate. q+1 Shares, and q+1 The strain rate-scaling factor information in the cell extrusion simulation analysis module is sequentially modified to any one of the first and fourth sets of strain rate-scaling factor information. After modification, the first cell model is run, thereby obtaining multiple first-type extrusion rates corresponding to the following: q+1 Group 5 Deformation-Force Information.

[0207] Understandably, the first cell model can obtain a set of first strain rate-scaling factor information through the extrusion simulation analysis module for each cell. Therefore, for each type of first extrusion rate... q The cell extrusion simulation analysis module can obtain the results for each type of first-order extrusion rate. q Group 5 Deformation-Force Information.

[0208] In some implementations, the multiple sets of fifth deformation-force information corresponding to the multiple first-type extrusion rates can be multiple sets of fifth deformation-force information corresponding to each type of extrusion rate, for example... V 2. Multiple sets of fifth deformation-force information corresponding to the extrusion rate, and, V 3. Multiple sets of fifth deformation-force information corresponding to the extrusion rate. Each set of fifth deformation-force information corresponds to each set of first iteration strain rate-scaling factor information.

[0209] As explained above, a set of first-iteration strain rate-scaling factor information includes multiple sixth data pairs. These multiple sixth data pairs can be used to obtain multiple seventh data pairs corresponding to each first type of extrusion rate. In other words, multiple sixth data pairs can be used to obtain... V 2. Multiple seventh data pairs corresponding to the extrusion rate, and, V 3. Multiple seventh data pairs corresponding to the extrusion rate, wherein each seventh data pair is formed by a single deformation information and a single force information, that is, the fifth deformation-force information includes multiple seventh data pairs.

[0210] Step S1328: For xyz In each direction, based on the preset multiple sets of first strain rate-scaling coefficient information corresponding to the next iteration round, as well as the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the current iteration round and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the next iteration round are determined until the third iteration termination condition is met.

[0211] Here, the third iteration termination condition can refer to stopping the iteration process when a certain preset standard is reached. In some implementations, the third iteration termination condition can be the maximum number of iterations, the first iteration termination condition can be a first error threshold, etc.

[0212] It is understandable that the multiple sets of first-iteration strain rate-scaling coefficient information corresponding to the next iteration round are jointly determined by the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates in the current iteration round, the multiple sets of first-iteration strain rate-scaling coefficient information corresponding to the current iteration round, and the multiple sets of first-iteration strain rate-scaling coefficient information preset for the next round. This feedback mechanism helps to continuously correct the parameter terms corresponding to the target strain rate-scaling coefficient information in the first cell model, so that the first cell model gradually approaches the optimal state. When the preset termination condition (such as the maximum number of iterations or the minimum error threshold) is reached, the iteration process ends, and the obtained target iteration strain rate-scaling coefficient information is updated into the first cell model, making the target cell model tend to stabilize and improving the model accuracy of the target cell model.

[0213] In some implementations, after determining multiple sets of first iteration strain rate-scaling factor information corresponding to the next iteration round, steps S1326 to S1328 are executed to perform iterative calculations for the next iteration round.

[0214] Step S1329: For xyz In each direction, based on multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates in all iteration rounds, the target strain rate-scaling coefficient information is determined from multiple sets of first-iteration strain rate-scaling coefficient information corresponding to all iteration rounds; the sum of the root mean square errors between the multiple sets of fifth deformation-force information under multiple first-type extrusion rates corresponding to the target strain rate-scaling coefficient information and the multiple sixth deformation-force information under multiple first-type extrusion rates is minimized; the multiple sixth deformation-force information is obtained by extruding the battery cell through extrusion experiments at multiple first-type extrusion rates;

[0215] In some implementations, multiple sixth deformation-force information at multiple first-type extrusion rates can mean that each type of extrusion rate corresponds to one sixth deformation-force information, so that multiple first-type extrusion rates correspond to multiple sixth deformation-force information.

[0216] In some implementations, after stopping the iteration, multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates obtained in each iteration are acquired; the sum of multiple third mean square differences between the fifth deformation-force information corresponding to each set of multiple first-type extrusion rates in each iteration and the multiple sixth deformation-force information under multiple first-type extrusion rates is calculated to obtain a first mean square value sum, which is used to determine the degree of agreement between the simulation results of the first cell model and the extrusion experiment; based on the multiple first mean square values ​​sum corresponding to the multiple sets of fifth deformation-force information under multiple first-type extrusion rates, a first target mean square value sum is determined; the first target mean square difference is the minimum value among the multiple first mean square value sums; based on the multiple first target mean square value sums corresponding to all iterations, a second target mean square value sum is determined; the second target mean square value sum is the minimum value among the multiple first target mean square value sums. It can be understood that the first iterative strain rate-scaling coefficient corresponding to this second target mean square value sum is the target strain rate-scaling coefficient information.

[0217] In some implementations, the sixth deformation-force information corresponding to multiple first-type extrusion rates can be expressed as: and The sixth deformation-force information corresponding to multiple first-type extrusion rates is obtained by extrusion experiments on the battery cell at multiple first-type extrusion rates. Among them, the second-type extrusion rate is used to realize the dynamic extrusion of the battery cell.

[0218] For example, to obtain and The first submean squared error between them, and and The sum of the second sub-mean squared error and the first sub-mean squared error is the first mean squared value.

[0219] Step S1330: ... xyz The target strain rate-scaling factor information corresponding to each direction is updated into the model information of the first cell model to obtain the target cell model.

[0220] Here, will xyz The target strain rate-scaling factor information corresponding to each direction is updated to the strain rate-scaling factor information in the cell extrusion simulation analysis module.

[0221] Understandably, by xyzThe target strain rate-scaling factor information corresponding to each direction is updated to the model information of the first cell model, which can make the target cell model better match the experimental data, realize the optimization and correction of the target cell model, and thus enable the target cell model to more accurately reflect the mechanical response of the cell under various load conditions.

[0222] In this embodiment, multiple sets of first-iteration target strain rate-scaling factor information are generated in each iteration round and applied to the first cell model. Simulation using the first cell model yields fifth deformation-force information corresponding to multiple first-type extrusion rates. When a set termination condition is met, the target strain rate-scaling factor information with the highest fit to the experimental data is selected as the target parameter by comparing the differences between the simulation results of the first cell model across all iteration rounds and the experimental data. xyz The target strain rate-scaling factor information corresponding to each direction is updated in the first cell model to form the final target cell model. In this way, on the one hand, automatic parameter optimization can be achieved, reducing the time cost of human trial and error; on the other hand, by iteratively approaching the optimal solution, the accuracy and stability of the target cell model are improved.

[0223] In some embodiments, step S1328 above includes steps S202 and S203:

[0224] Step S202: Based on multiple sets of fifth deformation-force information, multiple sets of first iterative strain rate-scaling factor information, and multiple preset second approximation models corresponding to multiple first-type extrusion rates, determine the third strain rate-scaling factor information;

[0225] Here, the second approximation model is a simplified mathematical model used to predict material behavior. The structure of the second approximation model may include different types such as linear regression, polynomial fitting, and neural networks. Each second approximation model accepts a set of inputs and outputs corresponding prediction results. In this application, the input of the second approximation model is the first iteration strain rate-scaling coefficient information, and the output of the second approximation model is multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates.

[0226] In some implementations, multiple second approximation models can refer to at least two second approximation models, such as two second approximation models, three second approximation models, or six second approximation models.

[0227] In some implementations, multiple sets of first iterative strain rate-scaling factor information are input into each second approximation model. Through each second approximation model, multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates can be obtained. Based on the multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates obtained from all second approximation models, and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, a first target approximation model is determined. Based on the first target approximation model, third strain rate-scaling factor information is determined.

[0228] Step S203: Determine the preset multiple sets of first strain rate-scaling factor information corresponding to the next iteration round, and the third strain rate-scaling factor information corresponding to the current iteration round, as the multiple sets of first iteration strain rate-scaling factor information corresponding to the next iteration round.

[0229] In some implementations, a third range corresponding to the next iteration round is determined; multiple first scaling factor information is determined based on the third range corresponding to the next iteration round; and a single set of first strain rate-scaling factor information is determined based on the multiple first scaling factor information corresponding to the next iteration round and multiple first strain rate information. The first range corresponding to the next round can be determined based on the third scaling factor or can be directly set by the user.

[0230] In this embodiment, multiple second approximation models are introduced to predict multiple sets of first-iteration strain rate-scaling factor information in the current iteration, and the predicted third strain rate-scaling factor information is applied to the next iteration. This method can accelerate the optimization process, reduce unnecessary computation, and thus improve the computational efficiency of the target strain-stress information.

[0231] In some embodiments, step S202 may further include steps S2005 to S2008:

[0232] Step S2005: Input multiple sets of first iteration strain rate-scaling factor information into multiple preset second approximation models to determine multiple sets of seventh deformation-force information corresponding to multiple first type of extrusion rates;

[0233] In some implementations, multiple sets of first iterative strain rate-scaling factor information are used as inputs to each second approximation model. Each second approximation model is run on multiple sets of first iterative strain rate-scaling factor information based on multiple first extrusion rates to obtain multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates.

[0234] For example, multiple first-type extrusion rates can be V 2 and V 3, VThe seventh deformation-force information corresponding to 2 can be , V The seventh deformation-force information corresponding to 3 can be .

[0235] In some implementations, a set of first-iteration strain rate-scaling factor information is run at multiple first-type extrusion rates, corresponding to a set of seventh deformation-force information at multiple first-type extrusion rates. As can be seen from the above description, a set of first-iteration strain rate-scaling factor information includes multiple sixth data pairs. By running multiple sixth data pairs at each first-type extrusion rate, multiple seventh data pairs corresponding to each first-type extrusion rate can be obtained. Each seventh data pair is formed by a single deformation information and a single force information. In other words, a set of seventh deformation-force information at each type of extrusion rate includes multiple seventh data pairs.

[0236] Step S2006: Based on multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates under multiple second approximation models, and multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, determine the second target approximation model from the multiple second approximation models; the sum of the mean square errors between the multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates of the second target approximation model is minimized;

[0237] Here, the second objective approximation model is the optimal model selected from multiple second approximation models. The selection criterion for the second objective approximation model is usually based on minimizing the sum of the mean square errors between the predicted results of the second approximation model and the simulation results of the first cell model.

[0238] In some implementations, for each second approximation model, the sum of second sub-mean square values ​​is obtained between the fifth deformation-force information and the seventh deformation-force information at multiple first-type extrusion rates corresponding to the same fifth data pair; based on the sum of second sub-mean square values ​​corresponding to all fifth data pairs, a second mean square value is determined. Based on the sum of second mean square values ​​corresponding to all first approximation models, the second approximation model corresponding to the smallest sum of second mean square values ​​is determined as the second target approximation model.

[0239] For example, the second mean square sum can refer to obtaining and The third submean squared error between them, and and The sum of the fourth sub-mean squared error, the third sub-mean squared error, and the fourth sub-mean squared error is the second mean squared error.

[0240] Step S2007: Use multiple sets of second-iteration strain rate-scaling coefficient information as input to the second target approximation model for iterative calculation. Obtain multiple sets of eighth deformation-force information corresponding to multiple first-type extrusion rates through the second target approximation model until the fourth iteration termination condition of the second target approximation model is met. Among them, the multiple sets of second-iteration strain rate-scaling coefficient information include multiple sets of second strain rate-scaling coefficient information, and the second strain rate-scaling coefficient information includes multiple preset first strain rate information and multiple second scaling coefficient information determined based on the fourth range.

[0241] Here, the fourth iteration termination condition can refer to stopping the iteration process when a certain preset standard is reached.

[0242] In this application, the fourth iteration termination condition may be that the number of iterations reaches a preset number of iterations, or that the sum of the root mean square errors of the multiple eighth deformation-force information under multiple first-type extrusion rates predicted by the second target approximation model is less than a preset threshold.

[0243] In some implementations, a fourth range corresponding to the next iteration round is determined; based on the fourth range corresponding to the next round, multiple second scaling factor information corresponding to the next iteration round is determined; based on the multiple second scaling factor information corresponding to the next iteration round and multiple first strain information, a single set of second strain rate-scaling factor information is determined. The fourth range corresponding to the next round can be determined based on a fourth scaling factor, or it can be directly set by the user.

[0244] In this application, the fourth scaling factor may be the same as or different from the third scaling factor, and the fourth range may be less than or equal to the third range.

[0245] Step S2008: Based on the multiple sets of eighth deformation-force information corresponding to the multiple first-type extrusion rates of all iteration rounds, and the multiple sixth deformation-force information under the multiple first-type extrusion rates, determine the third strain rate-scaling coefficient information from the multiple sets of second-iteration strain rate-scaling coefficient information corresponding to all iteration rounds; the sum of the root mean square errors between the multiple eighth deformation-force information under the multiple first-type extrusion rates corresponding to the third strain rate-scaling coefficient information and the multiple sixth deformation-force information under the multiple first-type extrusion rates is the smallest.

[0246] In some implementations, after stopping the iteration, multiple sets of eighth deformation-force information corresponding to multiple first-type extrusion rates obtained in each iteration are acquired; the sum of multiple third mean square differences between the eighth deformation-force information corresponding to each set of multiple first-type extrusion rates in each iteration and the sixth deformation-force information under multiple first-type extrusion rates is calculated to obtain a third mean square value sum; based on the multiple third mean square values ​​sum corresponding to the multiple sets of eighth deformation-force information under multiple first-type extrusion rates, a third target mean square value sum is determined; the third target mean square difference is the minimum value among the multiple third mean square difference sums; based on the multiple third target mean square value sums corresponding to all iterations, a fourth target mean square value sum is determined; the fourth target mean square value sum is the minimum value among the multiple third target mean square value sums. It can be understood that the second iteration strain rate-scaling factor information corresponding to this fourth target mean square value sum is the third strain rate-scaling factor information.

[0247] For example, to obtain and The fifth submean squared error between them, and and The sum of the sixth sub-mean squared error, the fifth sub-mean squared error, and the sixth sub-mean squared error is the third mean squared error.

[0248] In this embodiment, firstly, the strain rate-scaling factor information of the first iteration of the current iteration is input into multiple second approximation models to generate multiple seventh deformation-force information under multiple first-type extrusion rates; then, by comparing the differences between the seventh deformation-force information under multiple first-type extrusion rates output by each second approximation model and the actual simulation results (fifth deformation-force information under multiple first-type extrusion rates), the second target approximation model with the best performance is selected for parameter optimization of the strain rate-scaling factor information; finally, the third strain rate-scaling factor information is determined based on the second target approximation model. By gradually approximating the optimal solution through this iterative method, the accuracy and efficiency of strain rate-scaling factor information parameter optimization are improved.

[0249] In some embodiments, the mesh information includes node information and cell information; the size information includes cell housing information, expected size information of the housing mesh, thickness information corresponding to multiple faces of the housing, expected size information of the core mesh, and core information; the above step S100 may include steps S101 to S103:

[0250] Step S101: Based on the cell casing information, the expected size information of the casing mesh, and the thickness information corresponding to multiple faces, determine the first node information of each node in multiple faces, and the first element information of each element in multiple faces;

[0251] Here, cell casing information refers to the basic geometric parameters of the cell. In some embodiments, cell casing information may include, but is not limited to, the cell casing length. y (direction), cell casing thickness ( x (direction), cell casing height ( z (Direction). The expected size information of the first mesh model is a preset mesh size based on design requirements, used to control the mesh division accuracy of the cell casing. The thickness information corresponding to multiple faces describes the material thickness of the casing in different directions. For example, if the casing has 6 faces, the thickness information corresponding to multiple faces can include the thickness of the front face, the back face, the left side, the right side, the top face, and the bottom face.

[0252] In some implementations, the first node information includes first node number information and first node position information in three-dimensional space, and the first unit information describes the first node number information and first sub-number information of a unit composed of multiple nodes.

[0253] For example, when the casing of the battery cell is modeled using quadrilateral units, the set of first node numbering information constituting the unit may include the first node numbering information of node N1, node N2, node N3, and node N4.

[0254] Step S102: Based on the expected size information of the core mesh, the core information, and the first node information of each node in multiple faces, determine the second node information of each node in the core, and the second element information of each element in the core;

[0255] Here, core information refers to the basic geometric parameters of the core. In some implementations, core information may include, but is not limited to, core length. y Direction), core thickness ( x (direction), core height ( z (Towards). The expected size information of the second mesh model is the mesh size preset according to the design requirements, which is used to control the mesh division accuracy of the battery cell core.

[0256] In some implementations, the second node information includes second node numbering information and second node position information in three-dimensional space, and the second unit information describes the second node numbering information and second sub-numbering information of a unit composed of multiple nodes.

[0257] For example, when the core of a battery cell is modeled using hexahedral elements, the set of second node numbering information constituting the element may include the second node numbering information of node N1, node N2, node N3, node N4, node N5, node N6, node N7, and node N8.

[0258] Step S103: Determine the mesh information of the mesh model based on the first node information corresponding to all nodes in multiple faces, the first element information corresponding to all elements in multiple faces, the second node information corresponding to all nodes in the core, and the second element information corresponding to all elements in the core.

[0259] In some implementations, the first node information corresponding to all nodes in multiple faces, the first element information corresponding to all elements in multiple faces, the second node information corresponding to all nodes in the core, and the second element information corresponding to all elements in the core are spliced ​​together according to a target order to determine the mesh information of the mesh model. The target order can be "first node number information - first node position information - first element information - second node number information - second node position information - second element information".

[0260] For example, the target order could be "first node number -- first node location information". x Coordinate values ​​-- First node location information y Coordinate values ​​-- First node location information z The coordinate values ​​are defined as follows: -- First sub-number information of the quadrilateral -- Number of the cell casing portion -- First node number information of node N1 -- First node number information of node N2 -- First node number information of node N3 -- First node number information of node N4 -- Cell casing thickness -- Second sub-number information of the hexahedron -- Number of the internal winding portion of the cell -- Second node number information of node N1 -- Second node number information of node N2 -- Second node number information of node N3 -- Second node number information of node N4 -- Second node number information of node N5 -- Second node number information of node N6 -- Second node number information of node N7 -- Second node number information of node N8. It can be understood that a cell includes a cell casing and a cell winding, and the number of the cell casing portion can refer to the first sub-number information, while the number of the internal winding portion can refer to the second sub-number information.

[0261] In this embodiment, firstly, based on the cell casing information, the expected size information of the casing mesh, and the thickness information corresponding to each of the multiple faces, the first node information and the first unit information of each face of the casing are generated. Then, based on the core information and the expected size information of the core mesh, the second node information and the second unit information inside the core are generated. Finally, the mesh information of the casing and the core are integrated together to form the mesh information of the complete cell mesh model. This ensures the accuracy of the mesh model structure and avoids modeling deviations caused by human design errors. Furthermore, the standardized mesh generation process improves the modeling efficiency and consistency of the mesh model.

[0262] In some embodiments, node information includes node number information and node location information; unit information includes unit number information; the above step S101 may include steps S1011 and S1012:

[0263] Step S1011: Based on the cell casing information, the expected size information of the casing mesh, and the thickness information corresponding to multiple surfaces, determine the first node number information and the first node position information of each node;

[0264] like Figure 2 As shown, the markings on each side of the battery cell casing are displayed. The markings on the front of the battery cell casing are 1-1, the bottom of the battery cell casing are 1-2, the left side of the battery cell casing are 1-3, the back of the battery cell casing are 1-4, the top of the battery cell casing are 1-5, and the right side of the battery cell casing are 1-6.

[0265] Below, with Figure 2 The calculation process for each node on each surface of the battery cell casing shown can be explained, including steps S3121 to S3126:

[0266] Step S3121: Calculate the mesh node information on the front of the cell casing;

[0267] like Figure 3 The diagram shows a grid diagram of the front of the battery cell casing. The lower boundary of the front of the battery cell casing is marked as 1-1-1, the first unit of the battery cell is marked as 1-1-9, the right boundary of the front of the battery cell casing is marked as 1-1-4, the first node on the right boundary is marked as 1-1-8, the last node on the right boundary is marked as 1-1-7, the first node of the battery cell is marked as 1-1-5, the left boundary of the front of the battery cell casing is marked as 1-1-2, the upper boundary of the front of the battery cell casing is marked as 1-1-3, the first node on the upper boundary is marked as 1-1-6, and the largest unit on the grid of the front of the battery cell casing is marked as 1-1-10.

[0268] In some implementations, such as Figure 3 As shown, when calculating the node information of the mesh on the front of the battery cell casing, along... x The direction is from left to right, then along z Construct a coordinate system from bottom to top. x The direction is line. z If the direction is column, then the total number of grid nodes on the front of the cell casing is... k+1 OK ，i+1 List.

[0269] The node number in row Z and column X of the grid on the front of the battery cell casing is:

[0270] (1);

[0271] in, N 0 indicates the number of the first node (1-1-5) of the battery cell. NumC x Indicates the cell casing mesh in x The number of quadrilateral units distributed in a specific direction.

[0272] NumC x For the cell casing mesh x The ratio of the directional dimension to the desired size of the cell housing grid is rounded down as shown in the following formula (2):

[0273] (2);

[0274] in, dx Indicates the grid pattern of the battery cell casing x Orientation dimension, S exp_C This indicates the desired size of the shell mesh.

[0275] dx For battery cells x Subtract the thickness of the left and right sides of the cell casing (the surfaces perpendicular to the x-axis) from the dimension (cell thickness). and Half of the sum is shown in the following formula (3):

[0276] (3);

[0277] in, T Indicates the grid pattern of the battery cell casing x Orientation dimension (cell casing thickness) Indicates the thickness of the left side of the battery cell casing, This indicates the thickness of the right side of the battery cell casing.

[0278] The node in row numZ and column numX corresponds tox The coordinates are:

[0279] (4);

[0280] in, S Cx This indicates that the quadrilateral unit on the battery cell casing is in x The actual dimensions of the direction.

[0281] S Cx The determination method is shown in the following formula (5):

[0282] (5);

[0283] The node in row numZ and column numX corresponds to y The coordinates are: y 1

[0284] The node in row numZ and column numX corresponds to z The coordinates are:

[0285] (6);

[0286] in, S Cz This indicates that the quadrilateral unit on the battery cell casing is in z The actual dimensions of the direction.

[0287] S Cz The determination method is shown in the following formula (7):

[0288] (7);

[0289] in, NumC z Indicates the cell casing mesh in z The number of quadrilateral units distributed in a specific direction.

[0290] NumC z The ratio of the z-direction dimension of the cell housing mesh to the desired dimension of the cell housing mesh is rounded down, as shown in the following formula (8):

[0291] (8);

[0292] in, dz Indicates the grid pattern of the battery cell casing z Orientation dimension, S exp_C This indicates the desired size of the cell casing grid.

[0293] dz For battery cells z Subtract the dimensions of the top and bottom surfaces of the cell casing from the cell casing height. z The thickness of the surface perpendicular to the axis is half of the sum of the thicknesses, as shown in formula (9):

[0294] (9);

[0295] in, T Indicates the grid pattern of the battery cell casing x Orientation dimension (cell thickness) Indicates the thickness of the top surface of the battery cell casing. This indicates the thickness of the bottom surface of the battery cell casing.

[0296] Step S3122: Calculate the mesh node information of the bottom surface of the cell casing;

[0297] like Figure 4 The diagram shows a schematic of the mesh on the bottom surface of the battery cell casing. The front boundary of the bottom surface of the battery cell casing is labeled 1-2-1, the first cell on the bottom surface of the battery cell casing is labeled 1-2-9, the right boundary of the bottom surface of the battery cell casing is labeled 1-2-4, the second node on the right boundary is labeled 1-2-8, the last node on the right boundary is labeled 1-2-7, the largest cell of the mesh on the bottom surface of the battery cell casing is labeled 1-2-10, the rear boundary of the bottom surface of the battery cell casing is labeled 1-2-3, the first node on the rear boundary is labeled 1-2-6, the left boundary of the bottom surface of the battery cell casing is labeled 1-2-2, and the first non-common node on the bottom surface of the battery cell casing is labeled 1-2-5.

[0298] In some implementations, such as Figure 4 As shown, when calculating the node information of the mesh on the bottom surface (1-2) of the battery cell casing, along... x The direction is from left to right, then along y Construct a coordinate system from front to back, such as Figure 4 It can be seen that the lower boundary (1-1-1) of the front surface (1-1) of the cell casing and the front boundary (1-2-1) of the bottom surface (1-2) of the cell casing are common, and the nodes are shared. x The direction is line. y If the direction is column, then the bottom surface mesh of the cell casing, excluding common nodes, has a total of j OK, i+1 Column nodes.

[0299] The node number in row numY and column numX of the grid on the bottom surface (1-2) of the battery cell casing is:

[0300] (10);

[0301] in, N 1 indicates the number of the last node (1-1-7) on the right boundary of the grid on the front of the cell casing.

[0302] The node in row numY and column numX corresponds to x The coordinates are:

[0303] (11);

[0304] The node in row numZ and column numX corresponds to y The coordinates are:

[0305] (12);

[0306] in, S Cy This indicates the actual size of the quadrilateral unit on the battery cell casing in the y-direction.

[0307] S Cy The determination method is shown in the following formula (13):

[0308] (13);

[0309] in, NumC y Indicates the cell casing mesh in y The number of quadrilateral units distributed in a specific direction.

[0310] NumC y For the cell casing mesh y The ratio of the directional dimension to the desired size of the cell housing grid, rounded down, is shown in the following formula (14):

[0311] (14);

[0312] in, dy Indicates the grid pattern of the battery cell casing y Orientation dimension, S exp_C This indicates the desired size of the cell casing grid.

[0313] dy For battery cells y Subtract half the sum of the thicknesses of the front and back sides (the surfaces perpendicular to the y-axis) of the cell casing from the dimension (cell casing length), as shown in the following formula (15):

[0314] (15);

[0315] in, LIndicates the grid pattern of the battery cell casing y Orientation dimension (cell casing length) Indicates the thickness of the front side of the battery cell casing. This indicates the thickness of the back side of the battery cell casing.

[0316] The z-coordinate of the node in row numZ and column numX is: z 1

[0317] Step S3123: Calculate the mesh node information on the left side of the cell casing;

[0318] like Figure 5 The diagram shows a mesh representation of the left side of the battery cell casing. The largest cell on the left side of the battery cell casing is labeled 1-3-10, the rear boundary of the left side of the battery cell casing is labeled 1-3-3, the second node on the rear boundary is labeled 1-3-8, the upper boundary of the left side of the battery cell casing is labeled 1-3-2, the last node on the upper boundary is labeled 1-3-7, the second node on the upper boundary is labeled 1-3-6, the front boundary of the left side of the battery cell casing is labeled 1-3-1, the first cell on the left side of the battery cell casing is labeled 1-3-9, the lower boundary of the left side of the battery cell casing is labeled 1-3-4, and the first non-common node on the left side is labeled 1-3-5.

[0319] In some implementations, such as Figure 5 As shown, when calculating the node information of the mesh on the left side of the battery cell casing, along... z The direction is from bottom to top, and then along y Construct a coordinate system from front to back, such as Figure 5 It can be seen that the front boundary (1-3-1) of the left side (1-3) of the battery cell casing shares the left boundary (1-1-2) of the front (1-1) of the battery cell casing, and the nodes are shared; the lower boundary (1-3-4) of the left side (1-3) of the battery cell casing shares the left boundary (1-2-2) of the bottom (1-2) of the battery cell casing, and the nodes are shared. y The direction is line. z If the direction is column, then the left side mesh of the cell casing, excluding common nodes, has a total of k OK, j Column nodes.

[0320] The node number in row numZ and column numY of the grid on the left side of the battery cell casing is:

[0321] (16);

[0322] in, N 2 indicates the number of the last node (1-2-7) on the right boundary of the grid on the left side of the cell casing.

[0323] The node in row numZ and column numY corresponds to x The coordinates are: x 1

[0324] The node in row numZ and column numY corresponds to y The coordinates are:

[0325] (17);

[0326] The z-coordinate of the node in row numZ and column numY is:

[0327] (18);

[0328] Step S3124: Calculate the mesh node information on the back of the cell casing;

[0329] like Figure 6 The diagram shows a schematic of the mesh on the back of the battery cell casing. The largest cell on the back of the battery cell casing is labeled 1-4-10, the upper boundary of the back of the battery cell casing is labeled 1-4-3, the second node on the upper boundary is labeled 1-4-6, the right boundary of the back of the battery cell casing is labeled 1-4-4, the second node on the right boundary is labeled 1-4-8, the last node on the right boundary is labeled 1-4-7, the left boundary of the back of the battery cell casing is labeled 1-4-2, the first non-common node on the back of the battery cell casing is labeled 1-4-5, the lower boundary of the back of the battery cell casing is labeled 1-4-1, and the first cell on the back of the battery cell casing is labeled 1-4-9.

[0330] In some implementations, such as Figure 6 As shown, when calculating the node information of the mesh on the back of the battery cell casing, along... x The direction is from left to right, then along z Construct a coordinate system from bottom to top, such as Figure 6 It can be seen that the lower boundary (1-4-1) of the back side (1-4) of the cell casing and the rear boundary (1-2-3) of the bottom surface (1-2) of the cell casing are common, sharing nodes; the left boundary (1-4-2) of the back side (1-4) of the cell casing and the rear boundary (1-3-3) of the bottom surface (1-3) of the cell casing are common, sharing nodes. x The direction is line. z If the direction is column, then the mesh on the back of the cell casing, excluding common nodes, has a total of k OK, i Column nodes.

[0331] The node number in row Z and column X of the grid on the back of the battery cell casing is:

[0332] (19);

[0333] in, N 3 indicates that the last node on the upper boundary of the left side of the battery cell casing is numbered (1-3-7).

[0334] The node in row numZ and column numX corresponds to x The coordinates are:

[0335] (20);

[0336] The node in row numZ and column numX corresponds to y The coordinates are:

[0337] (twenty one);

[0338] The node in row numZ and column numX corresponds to z The coordinates are:

[0339] (twenty two);

[0340] Step S3125: Calculate the mesh node information of the top surface of the cell casing;

[0341] like Figure 7 The diagram shows a schematic of the mesh on the top surface of the battery cell casing. The largest cell on the top surface of the battery cell casing is labeled 1-5-10. The rear boundary of the top surface of the battery cell casing is labeled 1-5-3. The intersection of two parallel lines adjacent to and parallel to the rear and left boundaries is labeled 1-5-6. The right boundary of the top surface of the battery cell casing is labeled 1-5-4. The second-to-last node on the right boundary is labeled 1-5-7. The second node on the right boundary is labeled 1-5-8. The front boundary of the top surface of the battery cell casing is labeled 1-5-1. The first non-common node on the top surface of the battery cell casing is labeled 1-5-5. The left boundary of the top surface of the battery cell casing is labeled 1-5-2. The first cell on the top surface of the battery cell casing is labeled 1-5-9.

[0342] In some implementations, such as Figure 7 As shown, when calculating the node information of the mesh on the top surface of the battery cell casing, along... x The direction is from left to right, then along y Construct a coordinate system from front to back, such as Figure 7It can be seen that the front boundary (1-5-1) of the top surface (1-5) of the battery cell casing shares the upper boundary (1-1-3) of the front side (1-1) of the battery cell casing, and the nodes are shared; the left boundary (1-5-2) of the top surface (1-5) of the battery cell casing shares the upper boundary (1-3-2) of the left side (1-3) of the battery cell casing, and the nodes are shared; the rear boundary (1-5-3) of the top surface (1-5) of the battery cell casing shares the upper boundary (1-4-3) of the back side (1-4) of the battery cell casing, and the nodes are shared. x The direction is line. y If the direction is column, then the top surface mesh of the cell casing, excluding common nodes, has a total of i OK, j-1 Column nodes.

[0343] The node number in row numX and column numY of the grid on the top surface of the battery cell casing is:

[0344] (twenty three);

[0345] in, N 4 indicates the number of the largest node (1-4-7) of the grid on the back of the cell casing.

[0346] The node in row numX and column numY corresponds to x The coordinates are:

[0347] (twenty four);

[0348] The node in row numX and column numY corresponds to y The coordinates are:

[0349] (25);

[0350] The node in row numX and column numY corresponds to z The coordinates are:

[0351] (26);

[0352] Step S3126: Calculate the grid node information on the right side of the cell casing.

[0353] like Figure 8The diagram shows a grid diagram of the right side of the battery cell casing. The largest cell on the right side of the battery cell casing is labeled 1-6-10; the last non-common node on the right side of the battery cell casing is labeled 1-6-7; the rear boundary of the right side of the battery cell casing is labeled 1-6-3; the intersection point between the parallel lines adjacent to and parallel to the lower boundary and the parallel lines adjacent to and parallel to the rear boundary is labeled 1-6-8; the lower boundary of the right side of the battery cell casing is labeled 1-6-4; the first non-common node on the first parallel line adjacent to and parallel to the front boundary of the right side of the battery cell casing is labeled 1-6-5; the first cell on the right side of the battery cell casing is labeled 1-6-9; the front boundary of the right side of the battery cell casing is labeled 1-6-1; the last non-common node on the first parallel line adjacent to and parallel to the front boundary of the right side of the battery cell casing is labeled 1-6-6; and the upper boundary of the right side of the battery cell casing is labeled 1-6-2.

[0354] In some implementations, such as Figure 8 As shown, when calculating the mesh node information on the right side of the battery cell casing, along... z The direction is from bottom to top, and then along y Construct a coordinate system from front to back, such as Figure 8 It can be seen that the front boundary (1-6-1) of the right side of the cell casing (1-6) is common to the right boundary (1-1-4) of the front side of the cell casing (1-1), and they share nodes; the lower boundary (1-6-4) of the right side of the cell casing (1-6) is common to the right boundary (1-2-4) of the bottom surface of the cell casing (1-2), and they share nodes; the rear boundary (1-6-3) of the right side of the cell casing (1-6) is common to the right boundary (1-4-4) of the back surface of the cell casing (1-4), and they share nodes; the upper boundary (1-6-2) of the right side of the cell casing (1-6) is common to the right boundary (1-5-4) of the top surface of the cell casing (1-5), and they share nodes. y The direction is line. z If the direction is column, then the right side mesh of the cell casing, excluding common nodes, has a total of k-1 OK, j-1 Column nodes.

[0355] The node number in row numZ and column numY of the grid on the right side of the battery cell casing is:

[0356] (27);

[0357] N5 represents the number of the second-to-last node (1-5-7) on the right boundary of the top surface of the battery cell casing.

[0358] The node in row numZ and column numY corresponds to x The coordinates are:

[0359] (28);

[0360] The node in row numZ and column numY corresponds to y The coordinates are:

[0361] (29);

[0362] The node in row numX and column numY corresponds to z The coordinates are:

[0363] (30);

[0364] Step S1012: Based on the cell casing information, the expected size information of the casing mesh, the thickness information corresponding to each of the multiple faces, and the first node number information corresponding to each node in the multiple faces, determine the first unit number information of each unit in the multiple faces; the first unit number information includes the first sub-number information used to identify the unit, and the first node number information corresponding to each node that makes up the unit.

[0365] The following describes the calculation process of each unit in each face, taking a scenario where the shell has 6 faces as an example. This process may include steps S3131 to S3136.

[0366] Step S3131: Calculate the grid cell information on the front side of the cell casing;

[0367] In some implementations, such as Figure 3 As shown, when calculating the cell information of the grid on the front side of the battery cell casing, along... x The direction is from left to right, then along z The coordinate system is constructed from bottom to top. x The direction is line. z If the direction is columns, then the total number of grid cells on the front of the cell casing is... k OK, i It should be noted that the coordinate system here is described in terms of cell dimension, which is different from the coordinate system described in step S3121 above, which is described in terms of node dimension. The number of rows and columns corresponding to the node dimension is 1 more than the number of rows and columns corresponding to the cell dimension.

[0368] The cell number in row Z and column X on the front of the battery cell casing is:

[0369] (31);

[0370] in, E 0 indicates the number of the first cell (1-1-9).

[0371] Then, the four nodes that make up the quadrilateral unit in row numZ and column numX are numbered as follows: ,in,

[0372] (32);

[0373] (33);

[0374] (34);

[0375] (35);

[0376] Step S3132: Calculation of grid cell information on the bottom surface of the battery cell casing;

[0377] In some implementations, such as Figure 4 As shown, when calculating the element information of the mesh on the bottom surface of the battery cell casing, along... x The direction is from left to right, then along y Construct a coordinate system from front to back, with x The direction is line. y The direction is column, and there are a total of j-1 OK, i Column nodes.

[0378] The cell number in row numY and column numX of the grid on the bottom surface of the battery cell casing is:

[0379] (36);

[0380] in, E 1 indicates the number of the largest cell (1-1-10) on the grid on the front of the cell casing.

[0381] Then, the four nodes that make up the quadrilateral unit in row numY and column numX are numbered as follows: ,in,

[0382] When numY=1, N1 is the numX-th node among the common nodes of the front (1-1) and bottom (1-2) of the cell casing; N2 is the numX+1-th node among the common nodes of the front (1-1) and bottom (1-2) of the cell casing; N4 is the number of the first non-common node (1-2-5) on the bottom (1-2) of the cell casing plus numX-1. .

[0383] When numY≠1, the four nodes of the quadrilateral element are numbered as follows: See the following formula:

[0384] (37);

[0385] N7 represents the number of the largest node (1-2-5) of the grid on the bottom surface (1-2) of the cell casing.

[0386] (38);

[0387] (39);

[0388] (40);

[0389] Step S3133: Calculate the grid cell information on the left side of the battery cell casing;

[0390] In some implementations, such as Figure 5 As shown, when calculating the element information of the mesh on the left side of the battery cell casing, along... z The direction is from bottom to top, and then along y Construct a coordinate system from front to back, with y The direction is line. z The direction is column, and there are a total of k-1 OK, j-1 Column unit.

[0391] The cell number in row Z and column Y of the grid on the left side of the cell casing is:

[0392] (41);

[0393] in, E 2 indicates the number of the largest cell (1-2-10) of the grid on the bottom surface of the cell casing.

[0394] Then, the four nodes that make up the quadrilateral unit in row numZ and column numY are numbered as follows: ,in,

[0395] When numZ=1 and numY=1, N1=N0 and N2 are the numbers of the first non-common node (1-2-5) on the bottom surface of the battery cell casing; N3 is the number of the first non-common node (1-3-5) on the left side of the battery cell casing; N4 is the number of the second node on the left boundary (1-1-2) of the front surface of the battery cell casing (the first node is actually the first node on the left boundary of the grid on the front surface of the battery cell casing).

[0396] When numZ=1 and numY≠1, N1 is the number of the numY-th node on the left boundary (1-2-2) of the bottom surface of the battery cell casing; N2 is the number of the (numY+1)-th node on the left boundary (1-2-2) of the bottom surface of the battery cell casing; N4 is the number of the first non-common node (1-2-5) on the bottom surface of the battery cell casing plus... ; .

[0397] When numZ≠1 and numY=1, N1 is the number of the numZ-th node on the left boundary (1-1-2) of the front of the battery cell casing; N2 is the number of the numZ-1-th non-common node on the left side of the battery cell casing; N3=N2+1; N4 is the number of the numZ+1-th node on the left boundary (1-1-2) of the front of the battery cell casing.

[0398] When numZ≠1 and numY≠1, the four nodes of the quadrilateral element are numbered as follows: See the following formula:

[0399] (42);

[0400] in, N 8 indicates the number of the first non-common node (1-3-5) on the left side of the cell casing.

[0401] (43);

[0402] (44);

[0403] (45);

[0404] Step S3134: Calculation of grid cell information on the back of the battery cell casing;

[0405] In some implementations, such as Figure 6 As shown, when calculating the cell information of the mesh on the back of the battery cell casing, along... x The direction is from left to right, then along z Construct a coordinate system from bottom to top, with x The direction is line. z The direction is column, and there are a total of k-1 OK, i-1 Column unit.

[0406] The cell number of the grid cell in row Z and column X on the back of the battery cell casing is:

[0407] (46);

[0408] in, E 3 indicates the number of the largest grid cell (1-3-10) on the left side of the cell casing.

[0409] Then, the four nodes that make up the quadrilateral unit in row numZ and column numX are numbered as follows: ,in,

[0410] When numZ=1 and numX=1, N1 is the number of the first node (1-2-6) on the rear boundary (1-2-3) of the bottom surface of the battery cell casing; N2 is the number of the second node on the rear boundary of the bottom surface of the battery cell casing; N3 is the number of the first non-common node (1-4-5) on the back side of the battery cell casing; N4 is the number of the second node (1-3-8) on the rear boundary (1-3-3) of the left side of the battery cell casing (the first node is actually the first node on the rear boundary of the mesh on the bottom surface of the battery cell casing).

[0411] When numZ=1 and numX≠1, N1 is the number of the numX-th node on the rear boundary (1-2-3) of the bottom surface of the cell casing; N2 is the number of the numX+1-th node on the rear boundary of the bottom surface of the cell casing; N4 is the number of the first non-common node (1-4-5) on the back side of the cell casing plus... N3 = N4 + 1.

[0412] When numZ≠1 and numX=1, N1 is the number of the numZ-th node on the rear boundary (1-3-3) of the left side of the cell casing; N2 is the number of the first non-common node (1-4-5) on the back side of the cell casing plus... ; ; .

[0413] When numZ≠1 and numX≠1, N1 is the number of the first non-common node (1-4-5) on the back of the cell casing plus... ; ; ; .

[0414] Step S3135: Calculation of grid cell information on the top surface of the battery cell casing;

[0415] In some implementations, such as Figure 7 As shown, when calculating the grid node cell information on the top surface of the battery cell casing, along... x The direction is from left to right, then along y Construct a coordinate system from front to back, with x The direction is line. z The direction is column, and there are a total of i-1 OK, j Column unit.

[0416] The cell number of the grid cell in row numX and column numY on the top surface of the battery cell casing is:

[0417] (47);

[0418] in, E4 indicates the number of the largest cell (1-4-10) of the grid on the back of the cell casing.

[0419] Then, the four nodes that make up the quadrilateral unit in row numX and column numY are numbered as follows: ,in,

[0420] When numY=1 and numX=1, N1 is the number of the first node (1-1-6) on the upper boundary (1-1-3) of the front of the cell casing; N2 is the number of the second node (1-3-6) on the upper boundary (1-3-2) of the left side of the cell casing (the first node is actually the first node on the upper boundary of the front of the cell casing); N3 is the number of the first non-common node (1-5-5) on the top surface of the cell casing; N4 is the number of the second node on the upper boundary (1-1-3) of the front of the cell casing.

[0421] When numY=NumC y When numX=1, N1 is the number of the second-to-last node on the upper boundary (1-3-2) of the left side of the battery cell casing; N2 is the number of the last node (1-3-7) on the upper boundary (1-3-2) of the left side of the battery cell casing; N3 is the number of the second node (1-4-6) on the upper boundary (1-4-3) of the back side of the battery cell casing (the first node is actually the last node on the upper boundary of the left side of the battery cell casing); N4 is the number of the first non-common node (1-5-5) on the top surface of the battery cell casing plus... .

[0422] When numY=1 and numX≠1, N1 is the number of the numXth node on the upper boundary (1-1-3) of the front of the cell casing; N2 is the number of the numX-1th non-common node on the top surface (1-5) of the cell casing; N3=N2+1; N4 is the number of the numX+1th node on the upper boundary (1-1-3) of the front of the cell casing.

[0423] When numY=NumC y When numX≠1, N1 is the number of the first non-common node (1-5-5) on the top surface (1-5) of the cell casing plus... N2 is the number of the (numX-1)th node on the upper boundary (1-4-3) of the back side (1-4) of the battery cell casing (the first node is actually the last node on the upper boundary of the left side of the battery cell casing); N3 is the number of the (numX)th node on the upper boundary (1-4-3) of the back side (1-4) of the battery cell casing (the first node is actually the last node on the upper boundary of the left side of the battery cell casing). .

[0424] When numY≠1, numY≠NumC y When numX=1, N1 is the number of the numY-1th node on the upper boundary (1-3-2) of the left side (1-3) of the battery cell casing; N2 is the number of the numYth node on the upper boundary (1-3-2) of the left side (1-3) of the battery cell casing (the first node is actually the first node on the upper boundary of the front side of the battery cell casing); N4 is the number of the first non-common node (1-5-5) on the top surface (1-5) of the battery cell casing plus... ; .

[0425] When numY≠1, numY≠NumC y When numX≠1, N1 is the number of the first non-common node (1-5-5) on the top surface (1-5) of the cell casing plus... ; ; ; .

[0426] Step S3136: Calculation of grid cell information on the right side of the cell casing;

[0427] In some implementations, such as Figure 8 As shown, when calculating the mesh node cell information on the right side of the battery cell casing, along... z The direction is from bottom to top, and then along y Construct a coordinate system from front to back, with y The direction is line. z The direction is column, and there are a total of k-2 OK, j-2 Column unit.

[0428] The cell number of the grid cell in row Z and column Y on the right side of the cell casing is:

[0429] (48);

[0430] in, E 5 indicates the number of the largest grid cell (1-5-10) on the top surface of the battery cell casing.

[0431] Then, the four nodes that make up the quadrilateral unit in row numZ and column numY are numbered as follows: ,in,

[0432] When numY=1 and numZ=1, N1 is the number of the first node (1-1-8) on the right boundary (1-1-4) of the front of the cell casing; N2 is the number of the second node (1-1-4) on the right boundary of the front of the cell casing; N3 is the number of the first non-common node (1-6-5) on the first parallel line adjacent to and parallel to the front boundary of the right side (1-6) of the cell casing; N4 is the number of the second node (1-2-8) on the right boundary (1-2-4) of the bottom of the cell casing (the first node is actually the first node on the right boundary of the front of the cell casing).

[0433] When numY=NumC y When numZ=1, N1 is the number of the last non-common node (1-6-7) on the right side of the cell casing minus N2 is the number of the second node (1-4-8) on the right boundary (1-4-4) on the back of the cell casing (the first node is actually the last node on the right boundary of the bottom of the cell casing); N3 is the number of the last node (1-2-7) on the right boundary (1-2-4) on the bottom of the cell casing (1-2); N4 is the number of the second to last node on the right boundary (1-2-4) on the bottom of the cell casing (1-2).

[0434] When numY=NumC y numZ=NumC z At that time, N1 is the number of the second to last node (1-5-7) on the right boundary (1-5-4) of the top surface of the cell casing (the last node is actually the last node on the right boundary of the back surface of the cell casing); N2 is the number of the last node (1-4-7) on the right boundary (1-4-4) of the back surface (1-4) of the cell casing; N3 is the number of the second to last node on the right boundary (1-4-4) of the back surface (1-4) of the cell casing; N4 is the number of the last non-common node (1-6-7) on the right side (1-6) of the cell casing.

[0435] When numY=1, numZ=NumC z In this context, N1 is the number of the last node (1-1-7) on the right boundary (1-1-4) of the front side (1-1) of the cell casing; N2 is the number of the second node (1-5-8) on the right boundary (1-5-4) of the top surface (1-5) of the cell casing (the first node is actually the last node on the right boundary of the front side of the cell casing); N3 is the number of the last node (1-6-6) on the first parallel line adjacent to and parallel to the front boundary of the right side (1-6) of the cell casing, plus... N4 is the number of the second to last node on the right boundary (1-1-4) of the front (1-1) of the cell casing.

[0436] When numY=1, numZ≠1, numZ≠NumC z In this case, N1 is the number of the Z-th node on the right boundary (1-1-4) of the front side (1-1) of the cell casing; N2 is the number of the (Z+1)-th node on the right boundary (1-1-4) of the front side (1-1) of the cell casing; N4 is the number of the last node (1-6-6) on the first parallel line adjacent to and parallel to the front boundary of the right side (1-6) of the cell casing, plus... ; .

[0437] When numY≠1, numY≠NumC y numZ=NumC z In this context, N1 is the number of the numY-th node on the right boundary (1-5-4) of the top surface (1-5) of the cell casing; N2 is the number of the numY+1-th node on the right boundary (1-5-4) of the top surface (1-5) of the cell casing; and N4 is the number of the last node 1-6-6 on the first parallel line adjacent to and parallel to the front boundary of the right side (1-6) of the cell casing, plus... ; .

[0438] When numY=NumC y numZ≠1, numZ≠NumC z At that time, N1 is the number of the last non-common node (1-6-7) on the right side (1-6) of the cell casing minus N2 is the number of the last node (1-4-7) on the right boundary (1-4-4) of the back of the cell casing (1-4) minus the number of the last node (1-4-7). N3 is the number of the last node (1-4-7) on the right boundary (1-4-4) of the back of the cell casing (1-4) minus the number of the last node (1-4-7). ; .

[0439] When numY≠1, numY≠NumC y When numZ≠1, N1 is the number of the numY-th node on the right boundary (1-2-4) of the bottom surface (1-2) of the cell casing; N2 is the number of the first non-common node (1-6-5) on the first parallel line adjacent to and parallel to the front boundary of the right side surface (1-6) of the cell casing, plus... ; N4 is the number of the numY+1th node on the right boundary (1-2-4) of the bottom surface (1-2) of the cell casing.

[0440] When numY≠1, numY≠NumC y numZ≠1, numZ≠NumC zAt that time, N1 is the number of the first non-common node (1-6-5) on the first parallel line adjacent to and parallel to the front boundary of the right side (1-6) of the cell casing, plus... ; ; ; .

[0441] In this embodiment, by defining the first node information of each node and the first unit information of each unit in the shell mesh, the parameterization of the cell shell mesh is improved and the management of the shell mesh is simplified. This facilitates subsequent modification and expansion of the shell mesh. On the other hand, by establishing the first node information and the first unit information of the shell mesh, the readability and maintainability of the shell mesh are improved.

[0442] In some embodiments, node information includes node number information and node location information; unit information includes unit number information; step S102 above may include steps S1021 and S1022:

[0443] Step S1021: Based on the expected size information, core information and first node information of the core mesh, determine the second node number information and second node position information of each node in the core;

[0444] In some implementations, such as Figure 9 As shown, when calculating the grid node information of the internal core of the battery cell, along... z The direction is from bottom to top, along x Construct a coordinate system from left to right, and then from front to back along the y-axis. y The direction is line. z Direction is column, x The direction is layered, and each layer of the grid in the internal core (1-7) of the battery cell has a total of p+1 OK, n+1 Column nodes, total 2m layer.

[0445] The node numbering of the numX-th layer, numZ-th row, and numY-th column of the internal core mesh of the battery cell is as follows:

[0446] (49);

[0447] in, N 6 indicates the number of the last non-common node (1-6-7) on the right side of the cell casing. NumJ y This indicates the grid pattern of the internal winding core of the battery cell. y The number of hexahedral units distributed in a specific direction. NumJ z This indicates the grid pattern of the internal winding core of the battery cell.z The number of hexahedral units distributed in a specific direction.

[0448] NumJ y The ratio of the y-direction dimension of the internal core mesh to the desired internal core dimension of the battery cell is rounded down, as shown in the following formula (50):

[0449] (50);

[0450] in, l Indicates the internal winding core of the battery cell y Orientation dimension (length of the internal winding of the battery cell). S exp_JR This indicates the desired size of the internal winding core of the battery cell.

[0451] NumJ z Internal winding mesh of the battery cell z The ratio of the directional dimension to the desired internal core dimension of the battery cell, rounded down, is shown in the following formula (51):

[0452] (51);

[0453] in, h Indicates the internal winding core of the battery cell z Orientation dimension (height of the internal winding core of the battery cell).

[0454] When the node is on the left side layer (1-7-1), the x-coordinate of the node in the numXth layer, numZth row, and numYth column is:

[0455] (52);

[0456] in, S JRx This indicates the actual dimensions of the internal winding core in the x-direction.

[0457] S JRx The determination method is shown in the following formula (53):

[0458] (53);

[0459] in, NumJ x This indicates the grid pattern of the internal winding core of the battery cell. x The number of hexahedral units distributed in a specific direction.

[0460] NumJ x Internal winding mesh of the battery cell xThe ratio of the directional dimension to the desired internal core dimension of the battery cell, rounded down, is shown in the following formula (54):

[0461] (54);

[0462] in, t Indicates the internal winding core of the battery cell x Orientation dimension (thickness of the internal winding core of the battery cell).

[0463] When it is a left-side layer node, the node corresponding to the node in the numXth layer, numZth row, and numYth column is... y The coordinates are:

[0464] (55);

[0465] in, S JRy Indicates that the internal winding core of the battery cell is in y The actual dimensions of the direction.

[0466] S JRy The determination method is shown in the following formula (56):

[0467] (56);

[0468] When it is a left-side layer node, the node corresponding to the node in the numXth layer, numZth row, and numYth column is... z The coordinates are:

[0469] (57);

[0470] in, S JRz Indicates that the internal winding core of the battery cell is in z The actual dimensions of the direction.

[0471] S JRz The determination method is shown in the following formula (58):

[0472] (58);

[0473] When it is a node in the right face layer (1-7-2), the node corresponding to the node in the numXth layer, numZth row, and numYth column is... x The coordinates are:

[0474] (59);

[0475] When it is a right-side layer node, the node corresponding to the node in the numXth layer, numZth row, and numYth column is... y The coordinates are:

[0476] (60);

[0477] When it is a right-side layer node, the node corresponding to the node in the numXth layer, numZth row, and numYth column is... z The coordinates are:

[0478] (61).

[0479] Step S1022: Based on the expected size information of the core mesh, the core information, and the first node information, as well as the second node number information corresponding to each node, determine the second unit number information of each unit; the second unit number information includes the second sub-number information used to identify the unit, and the second node number information corresponding to each node that makes up the unit.

[0480] In some implementations, such as Figure 9 As shown, when calculating the cell information of the internal core mesh of the battery cell, along... z The direction is from bottom to top, along x The direction is from left to right, then along y Construct a coordinate system from front to back, with y The direction is line. z Direction is column, x If the direction is a layer, then each layer of the internal winding core (1-7) of the battery cell has a total of p OK, n Columns, total m layer.

[0481] The numbering of the hexahedral cell in the numX-th layer, numZ-th row, and numY-th column of the internal core mesh of the battery cell is as follows:

[0482] (62);

[0483] in, E 6 indicates the number of the largest unit (1-6-10) on the right side of the cell casing.

[0484] Then, the eight nodes that make up the hexahedral element in the numXth layer, numZth row, and numYth column are numbered as follows: ,in,

[0485] (63);

[0486] in, N 10 This indicates the number of the first node (1-7-3) of the winding core inside the battery cell.

[0487] (64);

[0488] (65);

[0489] (66);

[0490] (67);

[0491] (68);

[0492] (69);

[0493] (70);

[0494] In this embodiment, by defining the second node information of each node and the second unit information of each unit in the core mesh, the parameterization of the core mesh is improved and the management of the core mesh is simplified. This facilitates subsequent modification and expansion of the core mesh. On the other hand, by establishing the second node information and the second unit information of the core mesh, the readability and maintainability of the core mesh are improved.

[0495] In some embodiments, the target extrusion test data includes xyz The target time-deformation-force information for each direction, and the target deformation-force information for each direction; xyz Directions include x direction, y direction and z Direction; Extrusion test information includes xyz First time-deformation-force information for each direction; the above step S110 includes steps S111 to S114:

[0496] Step S111: For each set of first time-deformation-force information in each direction, based on the deformation information in the first time-deformation-force information, perform duplicate data removal operation on the first time-deformation-force information to obtain second time-deformation-force information;

[0497] Here, the duplicate data removal operation refers to deleting data points with the same or similar first deformation information and the same time information in each group of first time-deformation-force information.

[0498] It is understandable that the first-time-deformation-force information includes first-time information, first-deformation information, and first-force information. Therefore, when multiple sets of first-time-deformation-force information are stored in a target data table, this data table includes a time column, a deformation information column, and a force information column. In this scenario, the duplicate data removal operation for multiple sets of first-time-deformation-force information can be performed as follows: check the time column in the target data table; obtain the first quantity corresponding to the non-repeating time information in the time column, and the second quantity corresponding to all rows in that time column; when the first quantity is less than the second quantity, determine the first-time-deformation-force information corresponding to the first quantity as the second-time-deformation-force information. For example, x Multiple sets of second-time-deformation-force information in the direction can be represented as ; y Multiple sets of second-time-deformation-force information in the direction can be represented as ; z Multiple sets of second-time-deformation-force information in the direction can be represented as .

[0499] In some implementations, a single set of first time-deformation-force information includes multiple first time information, multiple first deformation information, and multiple first force information. The multiple first time information, multiple first deformation information, and multiple first force information correspond one-to-one. A single time information, a single first deformation information, and a single force information can form a ninth data pair. That is, a single set of first time-deformation-force information includes multiple ninth data pairs.

[0500] Step S112: For each direction, based on the force information in multiple sets of second time-deformation-force information, perform data filtering operations on multiple sets of second time-deformation-force information to determine the target time-deformation-force information; the mean square error value corresponding to the force information in the target time-deformation-force information is the smallest;

[0501] Here, the data filtering operation refers to selecting a set of data with the best stability from multiple sets of second-time-deformation-force information as the target time-deformation-force information. For example, for x The direction, the target time-deformation-force information can be represented as ;for y The direction, the target time-deformation-force information can be represented as ;for z The direction, the target time-deformation-force information can be represented as .

[0502] In some implementations, the target time-deformation-force information is determined based on the force information in multiple sets of second time-deformation-force information, referring to the data filtering operations in steps S141 to S143 above.

[0503] It is understandable that in this application, the mean square error of the force information in the target time-deformation-force information is the smallest. The smaller the mean square error, the more stable the data. In other words, the change of the force information in the target time-deformation-force information is smooth and the reliability is higher.

[0504] Step S113: For each direction, perform data optimization on the target time-deformation-force information to determine the target deformation-force information;

[0505] Here, data optimization refers to further processing the selected target time-deformation-force information to eliminate outliers, smooth curves, or adjust data distribution. Data optimization makes the obtained target deformation-force information more consistent with actual physical behavior. Common data optimization methods include interpolation, filtering, and fitting.

[0506] Step S114: Based on xyz The target time-deformation-force information and target deformation-force information corresponding to each direction are used to determine the target extrusion test information.

[0507] Here, the target time-deformation-force information and target deformation-force information corresponding to each direction can refer to... x Target time-deformation-force information and target deformation-force information in the direction y Target time-deformation-force information and target deformation-force information in the direction z Target time-deformation-force information and target deformation-force information in the direction.

[0508] In this embodiment, by deduplicating, filtering, and optimizing multiple sets of extrusion test information, the final target extrusion test information used is ensured to have high representativeness and stability. This reduces the impact of invalid or noisy data on the establishment process of the target cell model, and improves the accuracy and reliability of the target cell model by using the optimized data as the input for training the target cell model.

[0509] In some embodiments, after step S112 described above, steps S115 to S117 may also be included:

[0510] Step S115: For each direction, determine the first sub-target time-deformation-force information corresponding to multiple first-type extrusion rates and the second sub-target time-deformation-force information corresponding to the second-type extrusion rate from the target time-deformation-force information;

[0511] In some implementations, the time-deformation-force information of the second sub-target corresponding to each direction can be represented as: The time-deformation-force information of multiple first sub-targets corresponding to each direction can be represented as follows: , .

[0512] Step S116: For each direction, determine the correlation between the time-deformation-force information of multiple first sub-targets and the time-deformation-force information of the second sub-targets;

[0513] In some implementations, calculation and The first correlation between them, and and The second correlation between them.

[0514] Step S117: For each direction, based on the correlation of all the time-deformation-force information of the first sub-target, determine the correlation coefficient between multiple time-deformation-force information of the first sub-target and the time-deformation-force information of the second sub-target.

[0515] In some implementations, if the first correlation and the second correlation meet a preset correlation threshold, the correlation coefficient is... Dcoeff Set to 1; if the first and second correlations do not meet the preset correlation threshold, the correlation coefficient will be... Dcoeff Set to 0.

[0516] It is understandable that the correlation coefficients for each direction can be obtained through the above steps S115 to S117.

[0517] In some embodiments, the target time-deformation-force information includes first sub-target time-deformation-force information corresponding to multiple first-type extrusion rates, and second sub-target time-deformation-force information corresponding to second-type extrusion rates; the first-type extrusion rate is much larger than the second-type extrusion rate; the above step S113 may include steps S1131 to S1133:

[0518] Step S1131: For each first type of extrusion rate, based on the maximum force information in the first sub-target time-deformation-force information corresponding to the first type of extrusion rate, normalize the first sub-target time-deformation-force information to determine the ninth deformation-force information; based on the ninth deformation-force information and the first preset quantity, determine the first range sum.

[0519] In this application, the target time-deformation-force information is divided into two types: multiple first sub-target time-deformation-force information corresponding to multiple first-type extrusion rates (high rate) and second sub-target time-deformation-force information corresponding to the second-type extrusion rate (low rate). The first sub-target time-deformation-force information is used to characterize the mechanical response of the battery cell under dynamic extrusion, and the second sub-target time-deformation-force information characterizes the mechanical response of the battery cell under static extrusion. In this way, the mechanical response of the battery cell under different extrusion rates can be characterized simultaneously.

[0520] It is understandable that the time-deformation-force information of the first sub-target includes multiple force information, multiple time information, and multiple deformation information. These multiple force information, time information, and deformation information correspond one-to-one. Each force information, each time information, and each deformation information constitutes a tenth data pair; that is, the time-deformation-force information of the first sub-target includes multiple tenth data pairs. Therefore, the maximum force information can be obtained from the force information in these multiple tenth data pairs.

[0521] In some implementations, the maximum force information from the time-deformation-force information of the first sub-target is obtained; using the maximum force information as a reference standard, the time-deformation-force information of the first sub-target is normalized to obtain the ninth deformation-force information under a unified metric scale. V 2. Extrusion rate corresponding to ,as well as V 3. Extrusion rate corresponding to Understandably, normalization can enhance the comparability between different groups of data.

[0522] Step S1132: Based on the maximum force information in the time-deformation-force information of the second sub-target, normalize the time-deformation-force information of the second sub-target to determine the tenth deformation-force information; based on the tenth deformation-force information and the first preset quantity, determine the second range sum.

[0523] Here, normalization is a common data standardization method. Its purpose is to eliminate the impact of differences in dimensions or scales caused by different testing conditions, so that different test data are comparable.

[0524] It is understandable that the time-deformation-force information of the second sub-target includes multiple force information, multiple time information, and multiple deformation information. These multiple force information, multiple time information, and multiple deformation information correspond one-to-one. Each force information, each time information, and each deformation information constitutes an eleventh data pair; that is, the time-deformation-force information of the second sub-target includes multiple eleventh data pairs. Therefore, the maximum force information can be obtained from the force information in these multiple eleventh data pairs.

[0525] In some implementations, the maximum force information in the time-deformation-force information of the second sub-target is obtained; using the maximum force information as a reference standard, the time-deformation-force information of the second sub-target is normalized to obtain the tenth deformation-force information under a unified metric scale, for example, the deformation-force information corresponding to the second type of extrusion rate. .

[0526] Step S1133: Determine the target deformation-force information based on multiple first range sums, multiple ninth deformation-force information, tenth deformation-force information, and second range sums.

[0527] The above steps S1131 to S1133 can obtain the target deformation-force information corresponding to each direction.

[0528] In this embodiment, by normalizing and performing range analysis on multiple sets of extrusion test information, the extrusion test information under different extrusion rates is quantitatively evaluated, thereby determining the target deformation-force information under different extrusion rates. On the one hand, normalization can eliminate the scale differences between data under different test conditions and improve the comparability of data; on the other hand, range analysis can identify areas with large data fluctuations, thereby taking targeted optimization measures to improve the quality and stability of data.

[0529] In some embodiments, step S1133 may further include steps S1133-1 to S1133-3:

[0530] Step S1133-1: Determine the data stability of multiple ninth deformation-force information based on multiple first range sums and second range sums;

[0531] In some implementations, a first ratio between each first range sum and the second range sum is obtained; if the first ratio corresponding to each of the multiple first range sums is greater than a first preset threshold, the data stability of the multiple ninth deformation-force information is determined to meet the target condition.

[0532] In some implementations, a first ratio between each first range sum and the second range sum is obtained; if the first ratio corresponding to each of the multiple first range sums is less than or equal to a first preset threshold, it is determined that the data stability of the multiple ninth deformation-force information does not meet the target condition.

[0533] Step S1133-2: If the data stability of multiple ninth deformation-force information meets the target condition, determine the target deformation-force information based on the second preset quantity, multiple ninth deformation-force information, and tenth deformation-force information;

[0534] In some implementations, for each ninth deformation-force information, a second preset number of first sub-deformation-force information is selected from the ninth deformation-force information; a second preset number of second sub-deformation-force information is selected from the tenth deformation-force information; and a target deformation-force information is determined based on the first sub-deformation-force information and the second sub-deformation-force information corresponding to the multiple ninth deformation-force information.

[0535] It is understandable that the tenth deformation-force information corresponds to the second type of extrusion rate, and multiple ninth deformation-force information correspond to multiple first type of extrusion rates. That is, multiple first sub-deformation-force information correspond to multiple different first type of extrusion rates, and the second sub-deformation-force information corresponds to the second type of extrusion rate. In other words, the target deformation-force information includes multiple first sub-deformation-force information corresponding to multiple first type of extrusion rates, and second sub-deformation-force information corresponding to the second type of extrusion rate. Each first type of extrusion rate corresponds to each first sub-deformation-force information.

[0536] Step S1133-3: If the data stability of multiple ninth deformation-force information does not meet the target condition, smooth the multiple ninth deformation-force information respectively to obtain multiple eleventh deformation-force information; for each eleventh deformation-force information, determine the twelfth deformation-force information based on the maximum deformation information, the second preset quantity, and the eleventh deformation-force information; determine the thirteenth deformation-force information based on the maximum deformation information, the second preset quantity, and the tenth deformation-force information; determine the target deformation-force information based on the multiple twelfth and thirteenth deformation-force information.

[0537] Here, smoothing is a data processing technique used to reduce noise and abnormal fluctuations in data, making the data more continuous and regular. In this application, by smoothing multiple ninth deformation-force information items separately, unnecessary jittery data in the ninth deformation-force information can be removed, while retaining the main trend. In some embodiments, methods such as moving average, polynomial fitting, or low-pass filtering are used to smooth the above data.

[0538] For example, polynomial formulas are used to process multiple ninth deformation-force information. , By performing fitting, multiple eleventh deformation-force information were obtained. , .

[0539] In some implementations, if the amount of data for the eleventh deformation-force information is determined to be greater than a second preset number (e.g., 100), the maximum and minimum deformation information within the eleventh deformation-force information are acquired; based on the maximum and minimum deformation information, the second preset number, and the eleventh deformation-force information, the twelfth deformation-force information is determined. For example, taking a second preset number of 100 as an example, the maximum deformation information within the eleventh deformation-force information is acquired. and minimum deformation information This way you can and 98 values ​​are inserted at equal intervals as the twelfth deformation information. During implementation, the first twelfth deformation information is... The second twelfth transformation information is The third, twelfth transformation information is And so on, until the 100th twelfth transformation information is obtained. The force information corresponding to the twelfth deformation is obtained by linear interpolation of the eleventh deformation-force information using 100 deformation values ​​of the twelfth deformation. During implementation, the force information is determined... Corresponding Twelve Force Information ,as well as Corresponding Twelve Force Information Thus, based on multiple twelfth transformation information, Corresponding Twelve Force Information ,as well as Corresponding Twelve Force Information Linear interpolation is performed to obtain the twelve force information corresponding to each twelfth deformation information; thus, based on all the twelfth deformation information and the twelve force information corresponding to each twelfth deformation information, the twelfth deformation-force information is determined.

[0540] In this embodiment, by evaluating data stability based on multiple first ranges and second ranges, and selecting different data processing strategies based on the stability results, unreliable data can be effectively filtered out, thereby improving the model accuracy of the target cell model.

[0541] In some embodiments, step S1131 may further include steps S1131-1 to S1131-2:

[0542] Step S1131-1: Select multiple fourteenth deformation-force information from the ninth deformation-force information according to the first preset number, and determine the range of force information in each fourteenth deformation-force information;

[0543] Here, the first preset quantity refers to a value defined according to system settings or user input parameters. This value is used to control the number of data points selected for each range calculation. The range represents the difference between the maximum and minimum values ​​of the force information contained in the fourteenth deformation-force information, and is used to measure the degree of fluctuation of the force information contained in the fourteenth deformation-force information.

[0544] In some implementations, multiple fourteenth deformation-force information entries can be selected sequentially from the ninth deformation-force information entries, using a first preset number as a window, and the range of force information in each fourteenth deformation-force information entry can be obtained.

[0545] For example, the ninth deformation-force information may include: W1-D1, W2-D2, W3-D3, W4-D4, W5-D5, W6-D6, W7-D7. With the first preset quantity being 4, the fourteenth deformation-force information obtained by the first window movement is: W1-D1, W2-D2, W3-D3, W4-D4. The maximum and minimum values ​​are found among D1, D2, D3, and D4, and the difference is calculated to obtain the first range value. The second window movement obtains W2-D2, W3-D3, W4-D4, W5-D5, and the maximum and minimum values ​​are found among D2, D3, D4, and D5, and the difference is calculated to obtain the second range value. The third window movement obtains W3-D3, W4-D4, W5-D5, W6-D6, and the maximum and minimum values ​​are found among D3, D4, D5, and D6, and the difference is calculated to obtain the third range value. The fourth window movement yields W4-D4, W5-D5, W6-D6, and W7-D7. The maximum and minimum values ​​are then found among D4, D5, D6, and D7, and the difference is calculated to obtain the fourth range value.

[0546] It is understandable that the ninth deformation-force information includes multiple deformation information and multiple force information, and there is a one-to-one correspondence between the multiple deformation information and the multiple force information. In this way, each deformation information and each force information constitute a twelfth data pair. That is, the ninth deformation-force information includes multiple twelfth data pairs, while the fourteenth deformation-force information is a first preset number of multiple thirteenth data pairs selected from the ninth deformation-force information.

[0547] Step S1131-2: Sum all the ranges to determine the first range sum.

[0548] Here, the first range sum is the result of adding up the range values ​​corresponding to all the fourteenth deformation-force information. This indicator is used to reflect the fluctuation of the overall data.

[0549] For example, the sum of the first range, the second range, the third range, and the fourth range is used to obtain the first range sum.

[0550] In this embodiment, by setting a fixed sampling interval, samples are extracted from the ninth deformation-force information and its range is calculated to evaluate the data fluctuation. In this way, on the one hand, the data stability of the ninth deformation-force information can be quantitatively measured, and on the other hand, the consistency and comparability of the ninth deformation-force information analysis are ensured by sampling at a fixed interval.

[0551] In some embodiments, step 130 above includes steps S131 to S133:

[0552] Step S131: Based on the first grid information, cell casing information, and target extrusion test information, determine the target stop information; the target stop information is used to control the stop operation of the target cell model;

[0553] Step S132: Based on the first grid information, determine the pressure head position information; the pressure head position information is used to characterize the position of the pressure head used to extrude the battery cell on the battery cell;

[0554] Step S133: Based on the first grid information, the second grid information, the indenter position information, the target stop information, and the target extrusion test information... xyz The target deformation-force information in each direction is used to update the model information of the initial cell model, thus obtaining the model information of the first cell model.

[0555] In some implementations, the model information of the initial cell model includes a target stop information parameter module, and the target stop information obtained in step S131 is updated to the target stop information parameter module.

[0556] For example, and , and , and Corresponding to each, and

[0557] Update to the target stop information parameter module.

[0558] In this embodiment, by setting target stop information and pressure head position information and updating them in the model information of the initial cell model, the model accuracy of the target cell model can be improved, thereby improving the simulation efficiency and reliability of the target cell model, and further supporting the safety assessment and optimization of the battery pack in the design stage.

[0559] In some embodiments, step S131 may include steps S1311 to S1315:

[0560] Step S1311: Based on the first grid information and the cell casing information, determine... xyzThe third node number information corresponds to each direction in the direction; the third node number information is related to the cell in... xyz The directions correspond to the number of the nearest node at the center point of the surface;

[0561] Here, the third node number is the number of the node closest to the center point of the face in the three directions of the cell. The center point of the face can be the intersection of the diagonals of the face.

[0562] In some implementations, the information is determined from the first grid information. x The third node number information corresponding to the direction. Among them, x The third node number information corresponding to the direction can refer to the node number on the left side of the cell casing that is closest to the intersection of the diagonals of the left side of the cell casing. Or, the number of the node on the right side of the cell casing that is closest to the intersection of the diagonals on the left side of the cell casing.

[0563] In some implementations, the information is determined from the first grid information. y The third node number information corresponding to the direction. Among them, y The third node number corresponding to the direction can be the number of the node on the front of the cell casing that is closest to the intersection of the diagonals on the front of the cell casing. Alternatively, it can be the number of the node on the back of the battery cell casing that is closest to the intersection of the left diagonal of the battery cell casing.

[0564] In some implementations, the information is determined from the first grid information. z The third node number information corresponding to the z-direction. Specifically, the third node number information corresponding to the z-direction can be the number of the node on the bottom surface of the battery cell casing that is closest to the intersection of the diagonals of the bottom surface of the battery cell casing. Alternatively, it can be the number of the node on the back of the battery cell casing that is closest to the intersection of the diagonals of the top face of the battery cell casing.

[0565] Step S1312: Based on the cell thickness information in the cell casing information, compare it with the target extrusion test information... x The maximum deformation value in the target deformation-force information along the direction is used to determine the first difference;

[0566] Understandably, the target compression test information includes x The target deformation-force information includes multiple deformation and force information items. Each deformation and force item corresponds one-to-one, forming a thirteenth data pair. Therefore, from... x The maximum deformation value can be obtained from the target deformation-force information in the direction. .

[0567] In some implementations, the thickness information is compared with the maximum deformation value. By performing the difference operation, we can obtain the first difference. The first difference is used to describe the cell's performance under stress. x When the directional compression stops, the pressure head that compresses the battery cell and... The distance between the corresponding nodes. It's understandable that the target cell model calculates the pressure head and distance in real time during runtime. The distance between corresponding nodes, when this distance value reaches the first difference value When the time comes, the program will stop running.

[0568] Step S1313: Based on the thickness information of the cell length in the cell casing information and the maximum deformation value in the target deformation-force information in the y direction in the target extrusion test information, determine the second difference;

[0569] Understandably, the target compression test information includes y The target deformation-force information includes multiple deformation and force information items. Each deformation and force item corresponds one-to-one, forming a thirteenth data pair. Therefore, from... y The maximum deformation value can be obtained from the target deformation-force information in the direction. .

[0570] In some implementations, the thickness information is compared with the maximum deformation value. By performing the difference operation, we can obtain the second difference. The second difference is used to describe the cell's resistance to... y When the directional compression stops, the pressure head that compresses the battery cell and... The distance between the corresponding nodes. It's understandable that the target cell model calculates the pressure head and distance in real time during runtime. The distance between corresponding nodes, when this distance value reaches the second difference value When the time comes, the program will stop running.

[0571] Step S1314: Based on the cell height information in the cell casing information, and the target compression test information... z The maximum deformation value in the target deformation-force information in the direction is used to determine the third difference;

[0572] Understandably, the target compression test information includes z The target deformation-force information includes multiple deformation and force information items. Each deformation and force item corresponds one-to-one, forming a thirteenth data pair. Therefore, from... z The maximum deformation value can be obtained from the target deformation-force information in the direction. .

[0573] In some implementations, the thickness information is compared with the maximum deformation value. By performing the difference operation, we can obtain the third difference. The third difference is used to describe the cell's resistance. z When the directional compression stops, the pressure head that compresses the battery cell and... The distance between the corresponding nodes. It's understandable that the target cell model calculates the pressure head and distance in real time during runtime. The distance between corresponding nodes, when this distance value reaches the third difference. When the time comes, the program will stop running.

[0574] Step S1315: Based on the first difference, the second difference, the third difference, and... xyz The third node number information corresponding to each direction is used to determine the target stopping information.

[0575] In this embodiment, target stopping information is generated by multi-directional difference calculation based on the first grid information, the cell shell information and the target extrusion test information. This can effectively determine the running stopping conditions of the target cell model in different directions and avoid excessive extrusion of the cell, which could cause excessive deformation of the cell.

[0576] In some embodiments, step S132 may include steps S1321 and S1322:

[0577] Step S1321: Based on the first grid information, determine the pressure head at... xyz The position information of the target nodes on the surface of the shell corresponding to each direction; the target nodes are used to represent the center of the surface;

[0578] Here, a target node refers to a specific node selected in three-dimensional space to represent the center position of a certain surface (such as the front or bottom surface of a battery cell casing).

[0579] In some implementations, the pressure head is in x The direction of the compression position is , , ; the pressure head is y The direction of the compression position is , , ; the pressure head is z The direction of the compression position is , , .

[0580] Step S1322: Determine the pressure head position information based on the position information of the target nodes corresponding to all directions.

[0581] In this embodiment, the position of the pressure head is determined by defining target nodes and combining the position information of target nodes from multiple directions. This operation method can improve the simulation accuracy of the cell model when it is subjected to external forces in multiple directions, thereby making the evaluation of the mechanical performance of the cell model more reliable.

[0582] The following describes the application of the embodiments of this application in a real-world scenario.

[0583] To avoid the risk of internal short circuits caused by structural deformation during collisions, it is necessary to accurately simulate the mechanical properties of the battery pack during the design phase to assess its safety. As the smallest energy-carrying unit within the battery pack, the accuracy of the simulation of the battery cell directly determines the accuracy of the battery pack safety assessment.

[0584] Battery cell structures are complex, exhibiting different mechanical properties under varying stress directions, as well as dynamic effects. A typical battery cell model includes a finite element mesh reflecting the structural characteristics of the cell and a material model reflecting its mechanical properties. To meet engineering design needs, the internal structure of the cell often employs a simplified macroscopic mesh to simulate combinations of different microstructures, while a corresponding material model approximates the comprehensive mechanical properties exhibited by these different microstructure combinations. The current methods for establishing battery cell models have the following problems: ① Battery cell sizes vary, and manually creating finite element meshes in finite element preprocessing software is labor-intensive; ② Material models are relatively simple, and a single material model cannot simultaneously reflect the anisotropy and dynamic effect characteristics of the battery cell. During use, it is necessary to select the corresponding material model based on the actual force direction or strain rate range of the battery cell, which makes the application inconvenient; ③ The anisotropy of the material model is defined through coordinate systems or vectors. Moving or rotating the finite element mesh of the battery cell will cause the material model and the finite element mesh of the battery cell to no longer match, resulting in incorrect calculation results; ④ There are too many parameters to be identified in the material model and many simulation conditions. Manually adjusting a certain parameter through repeated trial and error to obtain a mechanical response close to that of the experiment is not accurate and is time-consuming.

[0585] This application provides a method for determining a battery cell model, such as... Figure 10 As shown, steps S300 to S370 are included:

[0586] Step S300: Read in the input file.

[0587] Here, the input files include file path parameters, cell size parameters, cell casing material test parameters, cell extrusion test parameters, and extrusion head type parameters. Among these,

[0588] The file path parameters include the absolute path to the source file, the absolute path to the calculated file, and the absolute path to the output file.

[0589] Cell size and location parameters include the cell casing length (i.e. y (Dimensions), cell casing thickness (i.e.) x (Dimensions), cell housing height (i.e.) z (Dimensions), front thickness of cell housing and back thickness of cell housing (with) y (Surface perpendicular to the axis), thickness of the left side of the cell housing and thickness of the right side of the cell housing (with) x (Surface perpendicular to the axis), thickness of the top surface of the cell housing and thickness of the bottom surface of the cell housing (with) z (Surface perpendicular to axis), internal core length of the cell, internal core thickness of the cell, internal core height of the cell, desired size of the cell housing mesh, desired size of the internal core mesh of the cell, and the first node of the cell mesh. x , y , z Coordinate values.

[0590] The battery cell casing material testing parameters were obtained by referring to the tensile testing standards for metallic materials and using tensile test deformation-force data. (Where o=1, 2, 3 represent 3 sets of repeated tests, and g represents g data points in each test), sample size data (such as width, gauge length, thickness) and corresponding unit system.

[0591] The parameters for cell extrusion testing are the parameters for the cell under pressure. x , y , z The time-deformation-force data collected during the directional compression test , , (Where o=1, 2, 3 represent 3 sets of repeated trials; k=1, 2, 3 represent 3 different trial rates; g represents g data points in each test), a total of 27 sets of experimental data.

[0592] The parameters of the extrusion head type are as follows x , y , z The shape and size of the extrusion head used in three-directional extrusion, for example, when x When the extrusion head for directional input is circular in shape and has a size of D30, it indicates... x The direction is achieved by extruding with a spherical head with a diameter of 30mm.

[0593] It should be noted that the cell casing material test parameters are optional. Whether or not the cell casing material test parameters (i.e., the multiple sets of casing material information mentioned above) are needed depends on the simplification of the cell model. For example, if the cell model is simplified to several parts such as the cell casing and the internal winding core, then the cell casing material test parameters are needed; if the cell model is simplified to only one part, then the cell casing material test parameters are not needed.

[0594] In some implementations, reading the input file involves reading the input file parameters into a table, including reading the file path parameter data into a path table, reading the cell size parameters into a cell size location table, reading the cell casing material test parameters into a cell casing material test data table, reading the cell extrusion test parameters into an extrusion test data table, and reading the extrusion head type parameters into an extrusion head type data table.

[0595] In some embodiments, such as Figure 11 As shown, step S300 above includes steps S301 to S305:

[0596] Step S301: Read in the file path parameter;

[0597] In some implementations, file path parameter data is read into a path table, which has 1 column and 3 rows, storing the absolute paths of the source file, the calculated file, and the output file, respectively.

[0598] Step S302: Read in the cell size and position parameters;

[0599] In some implementations, the cell size and location parameters are read into a cell size and location table. This table has 1 column and 17 rows, storing the cell casing length, cell casing thickness, cell casing height, front and back cell casing thicknesses, left and right cell casing thicknesses, top and bottom cell casing thicknesses, internal core length, internal core thickness, internal core height, desired cell casing grid size, desired internal core grid size, and the first node of the cell grid. x , y , z Coordinate values.

[0600] Step S303: Read in the test parameters of the cell casing material;

[0601] In some implementations, the battery cell casing material test parameters are read into a battery cell casing material test data table. This battery cell casing material test data table has 8 columns and stores, from left to right, the deformation, force, and sample size data and unit system of the battery cell casing material test for 3 tests.

[0602] Step S304: Read in the cell extrusion test parameters;

[0603] In some implementations, the cell extrusion test parameters are read into an extrusion test data table, which has 27 columns and the same number of rows as the maximum number of test data points.

[0604] Step S305: Read in the extrusion head type parameters;

[0605] In some implementations, extrusion head type parameters are read into an extrusion head type data table, which has 1 column and 6 rows, stored sequentially from top to bottom. x Directional extrusion head shape, x Directional extrusion head size, y Directional extrusion head shape, y Directional extrusion head size, z Directional extrusion head shape, z Directional extrusion head size.

[0606] Step S310: Establish the finite element mesh model of the battery cell.

[0607] Here, establishing a finite element model of a battery cell refers to generating a battery cell mesh by calling the battery cell size and location table data.

[0608] In some embodiments, such as Figure 12 As shown, step S310 above includes steps S311 to S314:

[0609] Step S311: Assigning cell parameters;

[0610] Access the cell size location table and assign variables to the following parameters: cell casing length, cell casing thickness, cell casing height, cell casing front thickness, cell casing back thickness, cell casing left side thickness, cell casing right side thickness, cell casing top thickness, cell casing bottom thickness, cell internal core length, cell internal core thickness, cell internal core height, desired size of the cell casing mesh, desired size of the cell internal core mesh, and the 3D coordinate value of the first node of the cell casing mesh: L , T , H , , , , , , , l , t , h , , , x 1, y1, z 1. Among them, the cell casing length, cell casing thickness, and cell casing height correspond to the cell casing information mentioned above; the cell internal winding length, cell internal winding thickness, and cell internal winding height correspond to the winding information mentioned above.

[0611] Step S312: Calculation of cell grid node information;

[0612] Here, the calculation of cell grid node information includes the calculation of cell shell node information (i.e., the first node information mentioned above) and the calculation of cell internal winding core node information (i.e., the second node information mentioned above). The node information can be derived from the node number (i.e., the first node number information mentioned above) and the node's position in three-dimensional space. x , y , z The coordinate values ​​(i.e., the location information of the first node mentioned above) constitute the structure. For example... Figure 2 As shown, the markings on each side of the battery cell casing are displayed. The markings on the front of the battery cell casing are 1-1, the bottom of the battery cell casing are 1-2, the left side of the battery cell casing are 1-3, the back of the battery cell casing are 1-4, the top of the battery cell casing are 1-5, and the right side of the battery cell casing are 1-6.

[0613] In some implementations, such as Figure 12 As shown, step S312 may include steps S3121 to S3127: Step S3121: Calculation of grid node information on the front side of the cell casing; Step S3122: Calculation of grid node information on the bottom side of the cell casing; Step S3123: Calculation of grid node information on the left side of the cell casing; Step S3124: Calculation of grid node information on the back side of the cell casing; Step S3125: Calculation of grid node information on the top side of the cell casing; Step S3126: Calculation of grid information on the right side of the cell casing; Step S3127: Calculation of grid node information on the inner core of the cell.

[0614] Step S313: Calculation of cell grid unit information;

[0615] Here, the calculation of cell grid unit information includes the calculation of cell shell unit information (i.e., the first unit information mentioned above) and the calculation of cell internal winding unit information (i.e., the second unit information mentioned above). The unit information includes the unit number (i.e., the first sub-number information and the second sub-number information mentioned above) and the number of the nodes that make up the unit.

[0616] In some implementations, such as Figure 12As shown, step S313 may include steps S3131 to S3137: Step S3131: Calculation of grid cell information on the front side of the cell casing; Step S3132: Calculation of grid cell information on the bottom side of the cell casing; Step S3133: Calculation of grid cell information on the left side of the cell casing; Step S3134: Calculation of grid cell information on the back side of the cell casing; Step S3135: Calculation of grid cell information on the top side of the cell casing; Step S3136: Calculation of grid cell information on the right side of the cell casing; Step S3137: Calculation of grid cell information of the internal core of the cell.

[0617] Step S314: Output the finite element mesh model of the battery cell (i.e., the mesh information of the mesh model mentioned above).

[0618] Here, following the solver's required format, the format is "First node number -- First node location information". x Coordinate values ​​-- First node location information y Coordinate values ​​-- First node location information z The node and cell information of the battery cell obtained in the above steps are output to a file in the following order: coordinate value -- first sub-number information of the quadrilateral -- number of the battery cell housing part -- first node number information of node N1 -- first node number information of node N2 -- first node number information of node N3 -- first node number information of node N4 -- thickness -- second sub-number information of the hexahedron -- number of the internal core part of the battery cell -- second node number information of node N1 -- second node number information of node N2 -- second node number information of node N3 -- second node number information of node N4 -- second node number information of node N5 -- second node number information of node N6 -- second node number information of node N7 -- second node number information of node N8.

[0619] Step S320: Generate the stress-strain curve of the battery cell casing (i.e., the curve information of the target stress-strain curve mentioned above).

[0620] Here, the stress-strain curve of the battery cell casing is generated based on the test data table of the battery cell casing material.

[0621] In some implementations, such as Figure 13 As shown, step S320 may further include steps S331 and S332:

[0622] Step S331: Screen test data for cell casing materials;

[0623] Here, we access the cell casing material test data table (i.e., the multiple sets of casing material information mentioned above), compare the deformation values ​​of the last data point of the three sets of test data, and take the maximum value among the three. dmax Based on the deformation data with the largest deformation value, the force values ​​of the other two sets of data are interpolated to obtain three sets of interpolated deformation-force data. (i.e., the information on the third type of shell material and the information on the first type of shell material mentioned above), and take the average of three sets of force values ​​for each deformation value, thus obtaining the average of the three sets of deformation-force data. The three sets of interpolated deformation-force data respectively with the mean Calculate the mean square deviation (o=1, 2, 3), and the set with the smallest mean square error is taken as the final selected test data for the cell casing material (i.e. the target casing material information mentioned above).

[0624] Step S332: Convert the battery cell casing material test data.

[0625] Here, tensile test deformation-force data are converted into engineering stress-strain curves. The engineering stress-strain curve is converted into a real stress-strain curve according to the principle of constant volume. (i.e., the curve information of the first stress-strain curve mentioned above); subtract the elastic strain from all strains to obtain the stress-plastic strain curve. (i.e., the curve information of the first stress-plastic strain curve mentioned above); Calculate the plastic strain value corresponding to the maximum stress value in the stress-plastic strain curve. ; with the minimum strain value being 0 and the maximum strain value being Interpolation calculations were performed at intervals of 18 points to obtain new stress-strain curves. (where g = 1, 2, ..., 20) (i.e., the curve information of the target stress-strain curve mentioned above).

[0626] It should be noted that whether or not the step of generating the cell casing stress-strain curve is needed can be determined based on the simplification level of the cell model.

[0627] Step S330: Preprocess cell test data.

[0628] In some implementations, such as Figure 14 As shown, step S330 may include steps S341 to S344:

[0629] Step S341: Delete duplicate data (i.e., the duplicate data removal operation described above).

[0630] Here, we access the extrusion test data table, examine the time column, and obtain the number of unique values ​​in the time column and the total number of rows in the time column. If the number of unique values ​​is less than the total number of rows in the time column, it indicates that there are duplicate values ​​in the time column. We then extract the time-deformation-force corresponding to the row numbers of the unique values ​​in the time column to form new data. , , (i.e., the second time-deformation-force information mentioned above).

[0631] Step S342: Screen the cell test data (i.e., the data screening operation mentioned above).

[0632] Here, referring to step S331 above, the result obtained from step S341 above... , , In the process, the set of test data with the smallest root mean square error of force value is obtained from the three sets of test data for each extrusion direction, thus obtaining the screened cell test data. , , (i.e., the target time-deformation-force information mentioned above).

[0633] Step S343: Calculate curve correlation;

[0634] here, and This represents the dynamic compression test data in the x-direction. This represents quasi-static extrusion test data in the y-direction; and This represents the dynamic compression test data in the y-direction. This represents quasi-static extrusion test data in the y-direction; and This represents the dynamic extrusion test data in the z-direction. This represents the quasi-static extrusion test data in the z-direction. Dynamic extrusion test data are calculated. and The data were compared with those from the quasi-static extrusion test. The correlation between the two data points is calculated. When the correlation is high, the correlation coefficient Dcoeff is set to 1; when the correlation is low, the correlation coefficient Dcoeff is set to 0. The correlation calculation can use, but is not limited to, the mean squared error (MSE). Specifically, the MSE is calculated between the force values ​​in the dynamic extrusion test data and the force values ​​in the quasi-static extrusion test data. When the MSE is below a certain value, the dynamic extrusion test data and the quasi-static extrusion test data are considered close, and the correlation coefficient Dcoeff is set to 1, indicating that the cell has no dynamic effect.

[0635] It should be noted that the above It can be , , Any of the above It can be , , Any of the above It can be , , Any one of them. Among them, , and There is a corresponding relationship, for example, for In this case, for , for .

[0636] Step S344: Optimize cell test data (i.e., the data optimization operation mentioned above).

[0637] Here, optimizing the test data involves smoothing and reducing the data obtained in step S342 above.

[0638] During implementation, the extrusion test data selected from each direction will be... , , Normalize according to the maximum value of each force to obtain , , (i.e., the ninth deformation-force information mentioned above); calculate the range (ΔFm) of the forces within the fixed displacement window (ΔDis) (i.e., the first preset quantity mentioned above), and sum the ranges of the forces within the m fixed displacement windows. (i.e., the sum of the first and second ranges mentioned above), when the sum of the range values ​​of the dynamic test data force ( and The sum of the range values ​​of the forces in the quasi-static test data () and the quasi-static test data () When the ratio of () to () is greater than a certain value, it indicates that the dynamic test data fluctuates greatly.

[0639] Using, but not limited to, polynomial formulas for dynamic test data with large fluctuations , By fitting, we can obtain , Check data , , If the number of rows exceeds a certain value, such as 100 rows (i.e., the second preset number mentioned above), then 98 values ​​are inserted at equal intervals between 0 and the maximum deformation value as new deformation data, and new deformation-force data are formed by interpolating the force values. , , (i.e., the aforementioned target deformation-force information).

[0640] Step S340: Update the source file for the cell extrusion simulation analysis.

[0641] Here, the source files for the cell extrusion simulation analysis include calculation files submitted to the solver, script files for extracting calculation results, and text files of experimental curves. Among them,

[0642] The calculation files submitted to the solver include the main control file, the finite element mesh model file of the battery cell, the material model file of the battery cell shell, the equivalent material model file of the internal coil of the battery cell, and the extrusion head model file. The main control file includes simulation files corresponding to three different extrusion rates in three directions (xyz), that is, nine simulation files corresponding to nine extrusion test conditions. The main control file calls the finite element mesh model file of the battery cell, the material model file of the battery cell shell, the equivalent material model file of the internal coil of the battery cell, and the extrusion head model file through association statements.

[0643] The script file for extracting calculation results is formatted according to the solver's requirements. After running, it can extract the calculation results to generate cell deformation-extrusion head reaction force data in the cell extrusion simulation analysis. ;

[0644] The test curve text file contains cell deformation-extrusion head reaction force data, totaling 9 files, each representing a different direction and extrusion rate;

[0645] Updating the source files for the cell extrusion simulation analysis includes updating the calculation stop parameters, loading parameters, indenter association statement parameters, and indenter position parameters in the main control file; updating the cell finite element mesh model file; and updating the benchmark test curve file. It should be noted that all updates to the cell extrusion simulation analysis source files are performed by opening, replacing, writing, and saving them in text format.

[0646] In some implementations, such as Figure 15 As shown, step S340 may include steps S351 to S357:

[0647] Step S351: Update the calculation stopping parameters (i.e., the target stopping information mentioned above);

[0648] During implementation, the absolute paths of the source files are stored in the access path table; the main control file in the source files is opened; the node information in the finite element mesh model file of the battery cell generated in step S120 is read; based on the node information in the finite element mesh model file of the battery cell, the coordinates of the intersection points of the bottom diagonals of the battery cell shell, the front diagonals of the battery cell shell, and the left diagonals of the battery cell shell are calculated; based on the coordinates of the intersection points of the bottom diagonals of the battery cell shell, the front diagonals of the battery cell shell, and the left diagonals of the battery cell shell, the node numbers of the bottom mesh nodes of the battery cell shell closest to the intersection points of the bottom diagonals of the battery cell shell, the front mesh nodes of the battery cell shell closest to the intersection points of the front diagonals of the battery cell shell, and the left mesh nodes of the battery cell shell closest to the intersection points of the left diagonals of the battery cell shell are determined from the node information in the finite element mesh model file; based on the deformation-force data obtained after optimizing the battery cell test data in step S330... Maximum deformation value in the middle The cell casing thickness L and the maximum deformation value in the x direction. The difference is calculated by subtracting the length H of the battery cell casing from the maximum deformation value in the y direction. The difference is calculated by subtracting the cell casing height T from the maximum deformation value in the z-direction. By performing subtraction, the nodes on the press head under 9 different extrusion conditions were obtained. , , final distance (i.e., the first difference mentioned above) (i.e., the second difference mentioned above) (i.e., the third difference mentioned above) (where k=1, 2, 3); find the line in the main control file where the stopping parameters are calculated, and use the node and the final distance parameter... and , and , and replace.

[0649] Step S352: Update loading parameters;

[0650] During implementation, the absolute paths of the source files are stored in the access path table; the main control file in the source file is opened; the line numbers corresponding to the start and end positions of the loading parameter section in the main control file are located; the content before the starting line of the loading parameter section is rewritten in the main control file as before; the time-deformation-force data obtained after filtering the cell test data in step S330 is called. , , Continue writing the time-deformed data from the previous step; rewrite the content after the end line of the loading parameter section from the previous step, just as before.

[0651] Step S353: Update the parameters of the pressure head association statement;

[0652] During implementation, the absolute paths of the source files are stored in the access path table; the main control file in the source files is opened; the extrusion head type data table is accessed to obtain the extrusion head shape and size for each extrusion direction; the name of the extrusion head model file corresponding to the extrusion head shape and size is searched under the absolute path where the source files are stored; and the parameters of the extrusion head association statement in the main control file are replaced with the name of the extrusion head model file.

[0653] Step S354: Update the pressure head position parameters;

[0654] During implementation, the absolute path of the source file is stored in the access path table; the main control file in the source file is opened; the cell parameters obtained in step S310 are called to calculate the positioning parameters of the pressure head in the x, y, and z directions; the pressure head position parameters in the main control file are found and replaced with the new pressure head positioning parameters.

[0655] Among them, the positioning parameters of the pressure head in the x, y, and z directions are as follows when extruding in the z direction: , , During x-axis compression: , , During y-axis compression: , , .

[0656] Step S355: Update the finite element mesh parameters of the battery cell;

[0657] During implementation, the absolute path of the source file is stored in the access path table; the finite element mesh model file of the battery cell in the source file is opened; the line numbers corresponding to the start and end positions of the battery cell mesh parameter section with specific markings in the battery cell finite element mesh model file are located; the content before the start line of the battery cell mesh parameter is rewritten in the battery cell finite element mesh model file as before; the battery cell finite element mesh model file generated in step S340 is opened, the content is copied, and it is written into the battery cell finite element mesh model file in the source file, continuing from the previous step; the content after the end line of the battery cell mesh parameter is rewritten in the previous step as before; the file is saved.

[0658] Step S356: Update the benchmark test curve file;

[0659] During implementation, the absolute paths of the source files are stored in the access path table; the benchmark test curve file in the source files is opened; and the deformation-force data obtained after smoothing and reducing the test data in step S340 is retrieved. , , And replace the original data in the benchmark test curve file.

[0660] Step S357: Update the stress-strain curve;

[0661] During implementation, the absolute paths of the source files are stored in the access path table; the cell casing material model file in the source files is opened; and the stress-strain curve from step S320 is called. (where g = 1, 2, ..., 20), and replace the original shell strain-stress information in the battery cell shell material model in the source file.

[0662] Step S350: Optimize the static parameters of the equivalent material of the internal winding core of the battery cell.

[0663] Here, the quasi-static parameters of the equivalent material of the internal core of the battery cell are the strain-stress data pair in the x-direction. (i.e., the aforementioned target strain-stress information), strain-stress data in the y-direction. (i.e., the aforementioned target strain-stress information), strain-stress data in the z-direction. (i.e., the target strain-stress information mentioned above), where 2≤ ≤6; strain is a predefined number of unequal or equal intervals. ,in, This indicates the number of strain-stress data pairs.

[0664] Optimizing the quasi-static parameters of the equivalent material of the internal core of a battery cell involves finding a predefined set of stress values ​​corresponding to a given strain, so that the deformation-force data extracted from the simulation is as close as possible to the deformation-force data from the experiment. The order of optimizing the quasi-static parameters of the equivalent material of the internal core of the battery cell is as follows: x-direction strain-stress data... y-direction strain-stress data strain-stress data in the z-direction .

[0665] In some implementations, such as Figure 16 As shown, step S360 above includes steps S361 to S364:

[0666] Step S361: First optimization iteration;

[0667] 1) The first sampling of the stress value to be optimized;

[0668] Here, for exist Sampling is performed within the range (i.e., the first range mentioned above), excluding those that do not meet the constraints. After sampling, at least p sets of first sampled values ​​are formed (i.e., the above multiple sets of first iteration strain-stress information), among which, .

[0669] 2) Generate the calculation file for the first iteration;

[0670] Access the absolute path where the source files are stored, copy p copies of the x-direction quasi-static extrusion simulation analysis source files (i.e., the first cell model) obtained in step S340 above, and store each copy in a new folder corresponding to the absolute path where the calculation files are stored. Then, modify the strain-stress values ​​of the equivalent material model files of the internal core of each cell in each of the p folders under the absolute path where the calculation files are stored to one of the p sets of first sampled values.

[0671] 3) Extraction of the calculation results of the first iteration;

[0672] The solver is invoked to run the calculation files submitted for solver operations in the aforementioned p folders. After the calculations are completed, the script file for extracting the calculation results is run to extract p sets of simulation deformation-force data. (i.e., the aforementioned multiple sets of first deformation-force information), among which, Indicates the quantity of deformation-force data, with values ​​similar to... equal.

[0673] 4) Approximate model selection;

[0674] Establish at least three approximation models, and use the obtained p groups of first sampled values ​​as input to each first approximation model. Run each first approximation model on the p groups of first sampled values ​​to obtain p groups of predicted deformation-force data. For each first approximation model, obtain the predicted deformation-force data corresponding to the same first sample value. Simulation deformation-force data of group p The first mean square error between the samples is determined; based on the first mean square error corresponding to each of the sampled values, the sum of the first mean square errors is determined. Based on the sum of the first mean square errors corresponding to each of the approximate models, the first approximate model corresponding to the minimum mean square error is determined as the first target approximate model.

[0675] 5) Stress parameter optimization based on approximate model;

[0676] The first objective approximation model determined in 4) above is optimized, and the variables are... The range is The constraints are Design a spatial scaling factor, and optimize the predicted deformation-force data of the first objective approximation model. The test deformation-force data stored in the benchmark test curve file The minimum mean square error between the two data points is achieved. The optimization termination condition is that the number of iterations reaches a set value or the mean square error between the predicted deformation-force data and the experimental deformation-force data is less than a set value.

[0677] Step S362: Second optimization iteration;

[0678] 1) The stress value to be optimized is sampled for the second time;

[0679] Here, will The sampling range was adjusted to After excluding those that do not meet the constraints After sampling, at least p groups of first sampled values ​​are formed, where, and the result obtained in step 5) during the first iteration (i.e., the aforementioned third strain-stress information) is used as one of the first sampled values.

[0680] 2) Generate the calculation file for the second iteration;

[0681] Access the absolute path where the source files are stored, copy p copies of the quasi-static extrusion simulation analysis source files in the x-direction obtained in step S340 above, and store each copy in a new folder corresponding to the absolute path where the calculation files are stored. Then, modify the strain-stress values ​​of the equivalent material model files of the internal core of each cell in each of the p folders under the absolute path where the calculation files are stored to one of the p sets of first sampled values.

[0682] 3) Extraction of the results of the second iteration;

[0683] Call the solver to run the calculation files submitted to the solver in the above p folders. After the calculation is completed, run the script file to extract the calculation results and extract p sets of simulation deformation-force data.

[0684] 4) Approximate model selection;

[0685] Establish at least three first approximation models, and use the obtained p sets of sampled values ​​as input to each first approximation model. Run each approximation model on the p sets of sampled values ​​to obtain p sets of predicted deformation-force data. (That is, the aforementioned multiple sets of second deformation-force information). For each first approximation model, obtain the predicted deformation-force data corresponding to the same sampled values. Simulation deformation-force data of group p The first mean square error between the samples is determined; based on the first mean square error corresponding to each of the sampled values, the sum of the first mean square errors is determined. Based on the sum of the first mean square errors corresponding to each of the approximate models, the approximate model corresponding to the minimum mean square error is determined as the first target approximate model.

[0686] 5) Stress parameter optimization based on approximate model;

[0687] The first objective approximation model determined in 4) above is optimized, and the variables are... The range is The constraints are Design a spatial scaling factor, and optimize the predicted deformation-force data of the first objective approximation model. The test deformation-force data stored in the benchmark test curve file The minimum mean square error between the two data points is achieved. The optimization termination condition is that the number of iterations reaches a set value or the mean square error between the predicted deformation-force data and the experimental deformation-force data is less than a set value.

[0688] Step S363: The nth optimization iteration;

[0689] This process is repeated for the first iteration, then for the third, fourth... iterations, until the optimization termination condition is met.

[0690] Step S364: Determine the optimized value in the x-direction.

[0691] Calculate the simulation deformation-force data extracted from all iterative simulation files. With experimental deformation-force data Find the simulation folder with the smallest mean square error, and extract the x-direction strain-stress data pair from the equivalent material model file of the internal core of the battery cell. This value is the optimal x-direction strain-stress data pair. Then, access the battery cell internal core equivalent material model file located at the absolute path of the source file, and replace the x-direction strain-stress data with... .

[0692] Optimize the quasi-static parameters of the internal core equivalent material of the battery cell, strain-stress data in the y-direction. Based on the optimized quasi-static parameters of the internal core material of the battery cell, strain-stress data in the x-direction were used to... The steps, after optimization, are to replace the strain-stress data pairs in the y-direction of the equivalent material model file of the internal core of the battery cell (located in the absolute path of the source file) with the optimal strain-stress data pairs in the y-direction. .

[0693] Optimize the z-direction strain-stress data of the equivalent material of the internal core of the battery cell. Based on the optimized quasi-static parameters of the internal core material of the battery cell, strain-stress data in the x-direction were used to... The steps, after optimization, are to replace the z-direction strain-stress data pairs of the battery cell internal core equivalent material model file located at the absolute path of the source file with the optimal z-direction strain-stress data pairs. .

[0694] Step S360: Optimize the dynamic parameters of the equivalent material of the internal winding core of the battery cell.

[0695] Here, the dynamic parameters of the equivalent material of the internal core of the battery cell are the x-direction strain rate parameter minus the scaling factor data pair. y-direction strain rate parameter - scaling factor data pair z-direction strain rate parameter - scaling factor data pair , where 2≤ ≤6; the strain rate parameter is a predefined number of unequal or equal intervals. ,in, This indicates the number of strain-stress data pairs.

[0696] Optimizing the dynamic parameters of the equivalent material inside the battery cell's core involves finding a set of scaling factor values ​​corresponding to predefined strain rate parameters, so that the deformation-force data extracted from the simulation is as close as possible to the deformation-force data from the experiment. Specifically, the order for optimizing the quasi-static parameters of the equivalent material inside the battery cell's core is: x-direction strain rate parameter - scaling factor data pair. y-direction strain rate parameter - scaling factor data pair z-direction strain rate parameter - scaling factor data pair .

[0697] In some implementations, the correlation coefficient in the x-direction calculated in step S330 above is obtained. When Dcoeff = 1, then... =1, in this scenario, replace all scaling factors in the x-direction strain rate parameter-scaling factor data pair of the battery cell internal core equivalent material model file stored in the absolute path of the source file with 1; when Dcoeff=0, such as Figure 17 As shown, step S360 above includes steps S371 to S374:

[0698] Step S371: First optimization iteration;

[0699] 1) The first sampling of the scaling factor to be optimized;

[0700] Here, for exist Sampling is conducted within the range (i.e., the third range mentioned above), excluding those that do not meet the constraints. After sampling, at least q sets of second sampled values ​​are formed, where, .

[0701] 2) Generate the calculation file for the first iteration;

[0702] Access the absolute path where the source files are stored, and copy q copies of the dynamic extrusion simulation analysis related source files for the first and second rates (i.e., the multiple first-type extrusion rates) in the x-direction of the cell extrusion simulation analysis source files obtained in step S340 above. Store each copy corresponding to each rate in a new folder under the absolute path where the calculation files are stored. Then, modify the strain rate parameter-scaling factor data value of the equivalent material model file of the internal core of the cell in each of the q folders for different rates under the absolute path where the calculation files are stored to one of the q sets of second sampled values.

[0703] 3) Extraction of the calculation results of the first iteration;

[0704] The solver is invoked to run the calculation files submitted to the solver in q folders at different speeds. After the calculations are completed, the script file for extracting the calculation results is run to extract q sets of simulation deformation-force data at different speeds. , (That is, multiple sets of fifth deformation-force information corresponding to the above-mentioned multiple first-type extrusion rates), among which, Indicates the quantity of deformation-force data, with values ​​similar to... equal.

[0705] 4) Approximate model selection;

[0706] Establish at least three second approximation models, and use the obtained q sets of second sampled values ​​as input to each second approximation model. Run each second approximation model on the q sets of sampled values ​​to obtain the predicted deformation-force data for the q sets of the first and second rates. and (That is, multiple sets of seventh deformation-force information corresponding to the aforementioned multiple first-type extrusion rates). For each second approximation model, the predicted deformation-force data of the first sampling rate corresponding to the same sample value are obtained. and simulation deformation-force data The first mean square error between the two values, and the predicted deformation-force data at the second sampling rate corresponding to the same sample value. and simulation deformation-force data The second mean square error between the two samples is determined; based on the first and second mean square errors corresponding to all the sampled values, the sum of the first mean square errors is determined. Based on the sum of the first mean square errors corresponding to all the second approximation models, the second approximation model corresponding to the minimum mean square error is determined as the second target approximation model.

[0707] 5) Scaling factor optimization based on approximate model;

[0708] The second objective approximation model determined in 4) above is optimized, and the variables are... The range is The constraints are The design space scaling factor is f, and the optimization objective is to compare the predicted deformation-force data of the first rate from the approximate model of the second objective with the experimental deformation-force data stored in the benchmark experimental curve file. The minimum mean square error between them, and the second target approximation model predicts the second type of rate deformation-force data and the test deformation-force data stored in the benchmark test curve file. The mean square error between the two is minimized. The optimization termination condition is that the number of iterations reaches a set value or the mean square error between the predicted deformation-force data and the experimental deformation-force data corresponding to the two rates predicted by the approximate model is less than the set value.

[0709] Step S372: Second optimization iteration;

[0710] 1) The scaling factor to be optimized is sampled for the second time;

[0711] Here, will The sampling range was adjusted to After excluding those that do not meet the constraints After sampling, at least q sets of sampled values ​​are formed, among which, And the result obtained from the optimization based on the approximate model during the first iteration As one of the sampled values.

[0712] 2) Generate the calculation file for the first iteration;

[0713] Access the absolute path where the source files are stored, and copy q copies of the dynamic extrusion simulation analysis related source files for the first and second rates in the x direction obtained in step S340 above. Store each copy corresponding to each rate in a new folder under the absolute path where the calculation files are stored. Then, modify the strain rate parameter-scaling factor data value of the equivalent material model file of the internal core of the battery cell in each of the q folders for different rates under the absolute path where the calculation files are stored to one of the q sets of sampled values.

[0714] 3) Extraction of the calculation results of the first iteration;

[0715] The solver is invoked to run the calculation files submitted to the solver in q folders at different speeds. After the calculations are completed, the script file for extracting the calculation results is run to extract q sets of simulation deformation-force data at different speeds. , .

[0716] 4) Approximate model selection;

[0717] Establish at least three second approximation models, and use the obtained q sets of sampled values ​​as input to each second approximation model. Run each second approximation model on the q sets of sampled values ​​to obtain the predicted deformation-force data for the first and second rates in the q sets. and For each second approximation model, predictive deformation-force data at the first sampling rate corresponding to the same sample value are obtained. and simulation deformation-force data The first mean square error between the two values, and the predicted deformation-force data at the second sampling rate corresponding to the same sample value. and simulation deformation-force data The second mean square error between the two samples is determined; based on the first and second mean square errors corresponding to all the sampled values, the sum of the first mean square errors is determined. Based on the sum of the first mean square errors corresponding to all the approximate models, the approximate model corresponding to the minimum mean square error is determined as the second target approximate model.

[0718] 5) Scaling factor optimization based on approximate model;

[0719] The second objective approximation model determined in 4) above is optimized, and the variables are... The range is The constraints are The design space scaling factor is f, and the optimization objective is to compare the predicted deformation-force data of the first rate from the approximate model of the second objective with the experimental deformation-force data stored in the benchmark experimental curve file. The minimum mean square error between them, and the second target approximation model predicts the second type of rate deformation-force data and the test deformation-force data stored in the benchmark test curve file. The mean square error between the two is minimized. The optimization termination condition is that the number of iterations reaches a set value or the mean square error between the predicted deformation-force data and the experimental deformation-force data corresponding to the two rates predicted by the approximate model is less than the set value.

[0720] Step S373: The nth optimization iteration;

[0721] This process is repeated for the second iteration, then for the third, fourth, and so on, until the optimization termination condition is met.

[0722] Step S374: Determine the optimized value in the x-direction.

[0723] Calculate the first-rate simulation deformation-force data extracted from all iterative simulation files. With experimental deformation-force data The mean square error of the sixth deformation-force information (i.e., the deformation-force data simulated at the second rate) is compared with that of the second type of rate simulation. With experimental deformation-force data Find the simulation folder with the smallest sum of mean square errors, and extract the x-direction strain rate parameter-scaling factor data pair from the equivalent material model file of the internal core of the battery cell. This value is the optimal x-direction strain-stress data pair. Then, access the battery cell internal core equivalent material model file located at the absolute path of the source file, and replace the x-direction strain-stress data with... (i.e., the target strain rate-scaling factor information mentioned above).

[0724] Optimize the dynamic parameters of the equivalent material in the internal winding core of the battery cell, the strain rate parameter in the y-direction, and the scaling factor data. Check the correlation coefficient between the quasi-static and dynamic extrusion test data in the y-direction. When Dcoeff=1, then... In this scenario, all scaling factors in the y-direction strain rate parameter-scaling factor data of the battery cell internal core equivalent material model file stored in the absolute path of the source file are replaced with 1; when Dcoeff=0, the x-direction strain rate parameter-scaling factor data of the optimized battery cell internal core equivalent material dynamic parameters are adjusted accordingly. The steps involve optimizing the dynamic parameters of the equivalent material inside the battery cell, specifically the strain rate parameter in the y-direction and the scaling factor data. After optimization, replace the y-direction strain rate parameter-scaling factor data pair in the battery cell internal core equivalent material model file located at the absolute path of the source file with the optimal y-direction strain rate parameter-scaling factor data pair. .

[0725] Optimize the dynamic parameters of the equivalent material in the core of the battery cell, z-direction strain rate parameter - scaling factor data pair Check the correlation coefficient between the quasi-static and dynamic extrusion test data in the z-direction. When Dcoeff=1, then... In this scenario, all scaling factors in the z-direction strain rate parameter-scaling factor data of the battery cell internal core equivalent material model file stored in the absolute path of the source file are replaced with 1; when Dcoeff=0, the x-direction strain rate parameter-scaling factor data of the optimized battery cell internal core equivalent material dynamic parameters are adjusted accordingly. The steps involve optimizing the dynamic parameters of the equivalent material inside the battery cell, specifically the strain rate parameter in the z-direction and the scaling factor data. After optimization, replace the z-direction strain rate parameter-scaling factor data pairs in the battery cell internal core equivalent material model file stored in the absolute path of the source file with the optimal z-direction strain-stress data pairs. .

[0726] Step S370: Output cell model.

[0727] Here, access the absolute path where the source files are stored, read and copy the contents of the finite element mesh model file of the battery cell, the material model file of the battery cell shell, and the equivalent material model file of the internal coil of the battery cell; create a new file under the absolute path where the output files are stored, open it and write the contents copied in the previous step, and finally save it to form the battery cell model file.

[0728] The embodiments of this application can bring the following beneficial effects: (1) The finite element mesh of the battery cell is parameterized, and the node order, element direction and position of the finite element mesh are uniquely determined. It will not be different due to human reasons, and the standardization is high and the mesh generation speed is faster; (2) The number of parameters to be identified in the material model is reduced, the number of optimization iterations is greatly reduced, and the identification difficulty is reduced; (3) The anisotropy and dynamic effects of the battery cell are unified in one model, and each direction has independent material parameters to describe the quasi-static and dynamic mechanical properties. With the goal of minimizing the difference between simulation and experimental results, the battery cell model can be obtained quickly and accurately through iterative optimization.

[0729] Based on the foregoing embodiments, this application provides a device for determining a battery cell model, such as... Figure 18 As shown, the cell model determining device 1800 includes:

[0730] The acquisition module 1810 is used to acquire the target information of the battery cell; the target information of the battery cell includes the size information of the battery cell, multiple sets of extrusion test information and the model information of the initial battery cell model;

[0731] The first determining module 1820 is used to determine the mesh information of the mesh model of the battery cell based on the size information of the battery cell; the mesh information of the mesh model includes the first mesh information of the battery cell shell and the second mesh information of the battery cell core.

[0732] The second determining module 1830 is used to perform preprocessing operations on multiple sets of extrusion test information to determine the target extrusion test information; the preprocessing operations include at least one of the following: duplicate data removal operation, data filtering operation, and data optimization operation.

[0733] The update module 1840 is used to update the model information of the initial cell model based on the first grid information, the second grid information, and the target extrusion test information, so as to obtain the target cell model.

[0734] The update module includes: a first update unit, used to update the model information of the initial cell model based on the first grid information, the second grid information, and the target extrusion test information, and to determine the model information of the first cell model; and a second obtaining unit, used to... xyz The target parameters corresponding to each direction are updated in the model information of the first cell model to obtain the target cell model.

[0735] In some embodiments, the target information includes multiple sets of shell material information of the shell, and the cell model determination device further includes: a third determination module, used to determine the target shell material information based on the multiple sets of shell material information; the mean square error value corresponding to the force information in the target shell material information is minimized; a fourth determination module, used to determine the curve information of the target stress-strain curve based on the target shell material information; and a first update unit, further used to update the model information of the initial cell model based on the curve information of the target stress-strain curve, the first mesh information, the second mesh information, and the target extrusion test information, to obtain the model information of the first cell model.

[0736] In some embodiments, the third determining module includes: a first determining unit, configured to determine a first type of shell material information and a plurality of second type shell material information from a plurality of sets of shell material information; the data volume of the first type of shell material information is greater than the data volume corresponding to each of the plurality of second type shell material information; a first obtaining unit, configured to perform interpolation processing on the plurality of second type shell material information based on the first type of shell material information to obtain a plurality of third type shell material information; the data volume of the first type of shell material information is equal to the data volume corresponding to each of the plurality of third type shell material information; and a second determining unit, configured to determine target shell material information based on the first type of shell material information and the plurality of third type shell material information.

[0737] In some embodiments, the fourth determining module includes: a third determining unit, configured to determine the curve information of a first stress-strain curve based on multiple deformation information and multiple force information in the target shell material information; a fourth determining unit, configured to determine first elastic strain information based on the curve information of the first stress-strain curve; a fifth determining unit, configured to determine the curve information of a first stress-plastic strain curve based on the first elastic strain information and the curve information of the first stress-strain curve; and a sixth determining unit, configured to determine the curve information of a target stress-strain curve based on the curve information of the first stress-plastic strain curve.

[0738] In some embodiments, the target parameters include target strain-stress information; the second obtaining unit includes: a first determining subunit, configured to target... xyz In each direction, during each iteration, multiple sets of first-iteration strain-stress information are determined; wherein, the multiple sets of first-iteration strain-stress information include multiple preset sets of first strain-stress information, the first strain-stress information includes multiple preset first strain information, and multiple first stress information determined based on a first range; the first strain information corresponds to the first stress information; the first running subunit is used for targeting xyzIn each direction, multiple sets of first-iteration strain-stress information are updated to the model information of the first cell model. Multiple sets of first-deformation-force information are obtained by running the first cell model. The second determined sub-unit is used for... xyz For each direction, based on multiple sets of preset first strain-stress information corresponding to the next iteration round, and multiple sets of first deformation-force information and multiple sets of first iteration strain-stress information corresponding to the current iteration round, multiple sets of first iteration strain-stress information corresponding to the next iteration round are determined until the first iteration termination condition is met; the third determined sub-unit is used for... xyz In each direction, based on multiple sets of first deformation-force information and fourth deformation-force information corresponding to all iteration rounds, the target strain-stress information is determined from multiple sets of first iteration strain-stress information corresponding to all iteration rounds; the mean square error between the first deformation-force information and the fourth deformation-force information corresponding to the target strain-stress information is minimized, and the fourth deformation-force information is obtained by extruding the cell at the second type of extrusion rate; the first update sub-unit is used to update the target strain-stress information corresponding to each direction in the xyz direction to the model information of the first cell model to obtain the target cell model.

[0739] In some embodiments, the second determining subunit is further configured to: determine third strain-stress information based on multiple sets of first deformation-force information, multiple sets of first iterative strain-stress information, and multiple preset first approximation models; and determine the preset multiple sets of first strain-stress information corresponding to the next iteration round, and the third strain-stress information corresponding to the current iteration round, as the multiple sets of first iterative strain-stress information corresponding to the next iteration round.

[0740] In some embodiments, the second determining subunit is further configured to: input multiple sets of first iterative strain-stress information into multiple preset first approximation models respectively, and determine multiple sets of second deformation-force information corresponding to the multiple first approximation models respectively; based on the multiple sets of second deformation-force information corresponding to the multiple first approximation models respectively, and the multiple sets of first deformation-force information, determine a first target approximation model from the multiple first approximation models; minimize the mean square error between the multiple sets of second deformation-force information and the multiple sets of first deformation-force information corresponding to the first target approximation model; perform iterative calculation by using the multiple sets of second iterative strain-stress information as input to the first target approximation model, and obtain the first target approximation model. The model obtains multiple sets of third deformation-force information until the second iteration termination condition of the first objective approximation model is met; wherein, the multiple sets of second iteration strain-stress information include multiple preset sets of second strain-stress information, the second strain-stress information includes multiple first strain information, and multiple second stress information determined based on the second range; based on the multiple sets of third deformation-force information and fourth deformation-force information corresponding to all iteration rounds, the third strain-stress information is determined from the multiple sets of second iteration strain-stress information corresponding to all iteration rounds; the mean square error between the third deformation-force information and the fourth deformation-force information corresponding to the third strain-stress information is minimized.

[0741] In some embodiments, the target parameters include target strain rate-scaling factor information; the second obtaining unit includes: a fourth determining subunit, configured to target... xyz In each direction, during each iteration, multiple sets of first iteration strain rate-scaling coefficient information are determined; wherein, the multiple sets of first iteration strain rate-scaling coefficient information include multiple preset sets of first strain rate-scaling coefficient information, the first strain rate-scaling coefficient information includes multiple preset first strain rate information, and multiple first scaling coefficient information determined based on a third range; the first scaling coefficient information corresponds to the first strain rate information; the second update sub-unit is used for... xyz In each direction, multiple sets of first-iteration strain rate-scaling factor information are updated to the model information of the first cell model. Through the first cell model, multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates are obtained; the fifth determining sub-unit is used for... xyz In each direction, based on the preset multiple sets of first strain rate-scaling coefficient information corresponding to the next iteration round, as well as the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the current iteration round and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the next iteration round are determined until the third iteration termination condition is met; the sixth determined sub-unit is used for targeting xyzIn each direction, based on multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates in all iteration rounds, the target strain rate-scaling coefficient information is determined from multiple sets of first-iteration strain rate-scaling coefficient information corresponding to all iteration rounds; the sum of the mean square errors between the multiple fifth deformation-force information under multiple first-type extrusion rates corresponding to the target strain rate-scaling coefficient information and the multiple sixth deformation-force information under multiple first-type extrusion rates is minimized; the multiple sixth deformation-force information is obtained by extruding the cell through extrusion experiments at multiple first-type extrusion rates; the third update subunit is used to... xyz The target strain rate-scaling factor information corresponding to each direction is updated into the model information of the first cell model to obtain the target cell model.

[0742] In some embodiments, the fifth determining subunit is further configured to: determine the third strain rate-scaling coefficient information based on multiple sets of fifth deformation-force information, multiple sets of first iterative strain rate-scaling coefficient information, and multiple preset second approximation models corresponding to multiple first type of extrusion rates; and determine the preset multiple sets of first strain rate-scaling coefficient information corresponding to the next iteration round, and the third strain rate-scaling coefficient information corresponding to the current iteration round, as the multiple sets of first iterative strain rate-scaling coefficient information corresponding to the next iteration round.

[0743] In some embodiments, the fifth determining subunit is further configured to: input multiple sets of first iterative strain rate-scaling coefficient information into multiple preset second approximation models to determine multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates; based on the multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates under multiple second approximation models, and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, determine a second target approximation model from the multiple second approximation models; the sum of the mean square errors between the multiple sets of seventh deformation-force information corresponding to multiple first-type extrusion rates and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates in the second target approximation model is minimized; use the multiple sets of second iterative strain rate-scaling coefficient information as input to the second target approximation model for iterative calculation, and obtain multiple first-type extrusion rate sub-models through the second target approximation model. The process involves identifying multiple sets of eighth deformation-force information corresponding to each iteration, until the fourth iteration termination condition of the second objective approximation model is met. These multiple sets of second iteration strain rate-scaling coefficient information include multiple sets of second strain rate-scaling coefficient information, which in turn include multiple preset first strain rate information and multiple second scaling coefficient information determined based on the fourth range. Based on the multiple sets of eighth deformation-force information corresponding to multiple first-type extrusion rates in all iteration rounds, and the multiple sixth deformation-force information under multiple first-type extrusion rates, a third strain rate-scaling coefficient information is determined from the multiple sets of second iteration strain rate-scaling coefficient information corresponding to each iteration round. The sum of the root mean square errors between the multiple eighth deformation-force information under multiple first-type extrusion rates corresponding to the third strain rate-scaling coefficient information and the multiple sixth deformation-force information under multiple first-type extrusion rates is minimized.

[0744] In some embodiments, the mesh information includes node information and cell information; the size information includes cell housing information, expected size information of the housing mesh, thickness information corresponding to multiple faces of the housing, expected size information of the core mesh, and core information; the first determining module includes: a seventh determining unit, used to determine the first node information of each node in the multiple faces and the first cell information of each cell in the multiple faces based on the cell housing information, the expected size information of the housing mesh, and the thickness information corresponding to multiple faces; an eighth determining unit, used to determine the second node information of each node in the core and the second cell information of each cell in the core based on the expected size information of the core mesh, the core information, and the first node information of each node in the multiple faces; and a ninth determining unit, used to determine the mesh information of the mesh model based on the first node information corresponding to all nodes in the multiple faces, the first cell information corresponding to all cells in the multiple faces, the second node information corresponding to all nodes in the core, and the second cell information corresponding to all cells in the core.

[0745] In some embodiments, node information includes node number information and node position information; unit information includes unit number information; the seventh determining unit includes: a seventh determining subunit, used to determine the first node number information and the first node position information of each node based on the cell housing information, the expected size information of the housing mesh, and the thickness information corresponding to each of the multiple faces; an eighth determining subunit, used to determine the first unit number information of each unit in the multiple faces based on the cell housing information, the expected size information of the housing mesh, the thickness information corresponding to each of the multiple faces, and the first node number information corresponding to each node in the multiple faces; the first unit number information includes the first sub-number information used to identify the unit, and the first node number information corresponding to each node constituting the unit.

[0746] In some embodiments, the target extrusion test data includes xyz The target time-deformation-force information for each direction, and the target deformation-force information for each direction; xyz Directions include x direction, y direction and z Direction; Extrusion test information includes xyz The first time-deformation-force information for each direction; the second determination module includes: a rejection unit, used to perform duplicate data rejection operations on the first time-deformation-force information for each group of first time-deformation-force information in each direction, based on the deformation information in the first time-deformation-force information, to obtain second time-deformation-force information; a tenth determination unit, used to perform data filtering operations on multiple groups of second time-deformation-force information for each direction, based on the force information in multiple groups of second time-deformation-force information, to determine target time-deformation-force information; the mean square error value corresponding to the force information in the target time-deformation-force information is minimized; an eleventh determination unit, used to perform data optimization operations on the target time-deformation-force information for each direction, to determine target deformation-force information; based on xyz The target time-deformation-force information and target deformation-force information corresponding to each direction are used to determine the target extrusion test information.

[0747] In some embodiments, the target time-deformation-force information includes first sub-target time-deformation-force information corresponding to multiple first-type extrusion rates, and second sub-target time-deformation-force information corresponding to a second-type extrusion rate; the first-type extrusion rate is much larger than the second-type extrusion rate; the eleventh determining unit includes: a ninth determining subunit, configured to, for each first-type extrusion rate, normalize the first sub-target time-deformation-force information based on the maximum force information in the first sub-target time-deformation-force information corresponding to the first-type extrusion rate to determine the ninth deformation-force information; and determine the first range sum based on the ninth deformation-force information and a first preset quantity; a tenth determining subunit, configured to, normalize the second sub-target time-deformation-force information based on the maximum force information in the second sub-target time-deformation-force information to determine the tenth deformation-force information; and determine the second range sum based on the tenth deformation-force information and the first preset quantity; and an eleventh determining subunit, configured to determine the target deformation-force information based on multiple first range sums, multiple ninth deformation-force information, tenth deformation-force information, and the second range sum.

[0748] In some embodiments, the eleventh determining subunit is further configured to: determine the data stability of multiple ninth deformation-force information based on multiple first range sums and second range sums; if the data stability of the multiple ninth deformation-force information meets the target condition, determine the target deformation-force information based on a second preset quantity, multiple ninth deformation-force information, and tenth deformation-force information; if the data stability of the multiple ninth deformation-force information does not meet the target condition, perform smoothing processing on the multiple ninth deformation-force information respectively to obtain multiple eleventh deformation-force information; for each eleventh deformation-force information, determine the twelfth deformation-force information based on the maximum deformation information in the eleventh deformation-force information, the second preset quantity, and the eleventh deformation-force information; determine the thirteenth deformation-force information based on the maximum deformation information in the tenth deformation-force information, the second preset quantity, and the tenth deformation-force information; and determine the target deformation-force information based on the multiple twelfth and thirteenth deformation-force information.

[0749] In some embodiments, the ninth determining subunit is further...

Claims

1. A method for determining a battery cell model, characterized in that, The method comprises: Obtaining target information of the battery cell; the target information of the battery cell includes size information of the battery cell, a plurality of groups of extrusion test information, and model information of an initial battery cell model; the plurality of groups of extrusion test information are used to represent mechanical response characteristics of the battery cell after different extrusion loads with different extrusion rates are applied to the battery cell in different directions different directions respectively; the model information of the initial battery cell model is used to represent a mechanical response characteristic of the battery cell after an extrusion load with a certain extrusion rate is applied to the battery cell in a certain direction determining grid information of a grid model of the battery cell based on the size information of the battery cell; the grid information of the grid model comprises first grid information of a shell of the battery cell and second grid information of a winding core of the battery cell; performing a preprocessing operation on the multiple groups of extrusion test information to determine target extrusion test information; the preprocessing operation comprises a repeated data elimination operation, a data screening operation and a data optimization operation; updating model information of the initial battery cell model based on the first grid information, the second grid information and the target extrusion test information to obtain a target battery cell model; wherein the updating of the model information of the initial battery cell model based on the first grid information, the second grid information and the target extrusion test information to obtain the target battery cell model comprises: updating the model information of the initial battery cell model based on the first grid information, the second grid information and the target extrusion test information to determine model information of a first battery cell model; Will The target parameters corresponding to each direction are updated in the model information of the first cell model to obtain the target cell model; the target parameters include target stress-strain information and / or target strain rate-scaling factor information.

2. The method according to claim 1, characterized in that the target information comprises multiple groups of shell material information of the shell, and the method further comprises: determining target shell material information based on the multiple groups of shell material information; the mean square error value corresponding to the force information in the target shell material information is the smallest; determining curve information of a target stress-strain curve based on the target shell material information; the updating of the model information of the initial battery cell model based on the first grid information, the second grid information and the target extrusion test information to determine the model information of the first battery cell model comprises: updating the model information of the initial battery cell model based on the curve information of the target stress-strain curve, the first grid information, the second grid information and the target extrusion test information to obtain the model information of the first battery cell model.

3. The method according to claim 2, characterized in that the determination of the target shell material information based on the multiple groups of shell material information comprises: determining first shell material information and multiple second shell material information in the multiple groups of shell material information; the data amount of the first shell material information is greater than the data amount corresponding to each of the multiple second shell material information; performing interpolation processing on the multiple second shell material information based on the first shell material information to obtain multiple third shell material information; the data amount of the first shell material information is equal to the data amount corresponding to each of the multiple third shell material information; determining the target shell material information based on the first shell material information and the multiple third shell material information.

4. The method according to claim 2, characterized in that the determination of the curve information of the target stress-strain curve based on the target shell material information comprises: determining curve information of a first stress-strain curve based on multiple deformation information and multiple force information in the target shell material information; determining first elastic strain information based on the curve information of the first stress-strain curve; determining curve information of a first stress-plastic strain curve based on the first elastic strain information and the curve information of the first stress-strain curve; Determine curve information of a target stress-strain curve based on the curve information of the first stress-plastic strain curve.

5. The method according to claim 1, characterized in that The target parameter includes target strain-stress information. Said The target parameter corresponding to each of the directions is updated into the model information of the first battery cell model respectively, to obtain a target battery cell model, including: For the In each iteration round, a plurality of groups of first iteration strain-stress information is determined for each of the directions; wherein the plurality of groups of first iteration strain-stress information comprises a plurality of groups of first strain-stress information preset, the first strain-stress information comprising a plurality of first strain information preset and a plurality of first stress information determined based on a first range; the first strain information corresponds to the first stress information. for the for each of the directions, updating the plurality of sets of first iteration strain-stress information into model information of the first cell model, obtaining a plurality of sets of first deformation-force information by running the first cell model; Regarding the above In each direction, based on the preset multiple sets of first strain-stress information corresponding to the next iteration round, as well as the multiple sets of first deformation-force information and the multiple sets of first iteration strain-stress information corresponding to the current iteration round, the multiple sets of first iteration strain-stress information corresponding to the next iteration round are determined until the first iteration termination condition of the iteration is met. Regarding the above In each direction, based on multiple sets of first deformation-force information and fourth deformation-force information corresponding to all iteration rounds, target strain-stress information is determined from multiple sets of first iteration strain-stress information corresponding to all iteration rounds; the mean square error between the first deformation-force information and the fourth deformation-force information corresponding to the target strain-stress information is minimized, and the fourth deformation-force information is obtained by extruding the cell at the second type of extrusion rate; The The target strain-stress information corresponding to each direction is updated in the model information of the first cell model to obtain the target cell model.

6. The method according to claim 5, characterized in that The determination of the plurality of sets of first iteration strain-stress information corresponding to the next iteration round based on the plurality of sets of first strain-stress information corresponding to the next iteration round, the plurality of sets of first deformation-force information corresponding to the current iteration round, and the plurality of sets of first iteration strain-stress information corresponding to the current iteration round comprises: Determine third strain-stress information based on the plurality of sets of first deformation-force information, the plurality of sets of first iteration strain-stress information, and a plurality of first approximation models preset. The plurality of sets of first iteration strain-stress information corresponding to the next iteration round are determined based on the plurality of sets of first strain-stress information corresponding to the next iteration round and the third strain-stress information corresponding to the current iteration round.

7. The method according to claim 6, characterized in that The determination of the third strain-stress information based on the plurality of sets of first deformation-force information, the plurality of sets of first iteration strain-stress information, and a plurality of first approximation models preset comprises: Input the plurality of sets of first iteration strain-stress information into the plurality of first approximation models respectively to determine a plurality of sets of second deformation-force information corresponding to the plurality of first approximation models respectively; Determine a first target approximation model from the plurality of first approximation models based on the plurality of sets of second deformation-force information corresponding to the plurality of first approximation models respectively and the plurality of sets of first deformation-force information; the mean square error value between the plurality of sets of second deformation-force information corresponding to the first target approximation model and the plurality of sets of first deformation-force information is the smallest; Iteratively calculate a plurality of sets of second iteration strain-stress information as input of the first target approximation model, obtain a plurality of sets of third deformation-force information through the first target approximation model, and stop until a second iteration termination condition of the first target approximation model is met; wherein the plurality of sets of second iteration strain-stress information include a plurality of sets of second strain-stress information, and the second strain-stress information includes a plurality of first strain information preset and a plurality of second strain information determined based on a second range; Determine third strain-stress information from the plurality of sets of second iteration strain-stress information corresponding to all iteration rounds based on the plurality of sets of third deformation-force information corresponding to all iteration rounds respectively and the fourth deformation-force information; the mean square error value between the third deformation-force information corresponding to the third strain-stress information and the fourth deformation-force information is the smallest.

8. The method of claim 1, wherein The target parameter includes target strain rate-scaling factor information. Said The target parameter corresponding to each of the directions is updated into the model information of the first battery cell model respectively, to obtain a target battery cell model. For the In each iteration round, for each direction, a plurality of groups of first iteration strain rate-scaling coefficient information is determined; wherein the plurality of groups of first iteration strain rate-scaling coefficient information comprises a plurality of groups of preset first strain rate-scaling coefficient information, the first strain rate-scaling coefficient information comprises a plurality of preset first strain rate information and a plurality of first scaling coefficient information determined based on a third range; the first scaling coefficient information corresponds to the first strain rate information. For each of the directions For each of the directions, the plurality of sets of first iteration strain rate-scaling coefficient information is updated into model information of the first battery cell model, and a plurality of sets of fifth deformation-force information corresponding to a plurality of first extrusion rates respectively is obtained by the first battery cell model. Regarding the above In each direction, based on the preset multiple sets of first strain rate-scaling coefficient information corresponding to the next iteration round, as well as the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the current iteration round and the multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates, the multiple sets of first iteration strain rate-scaling coefficient information corresponding to the next iteration round are determined until the third iteration termination condition is met. Regarding the above In each direction, based on multiple sets of fifth deformation-force information corresponding to multiple first-type extrusion rates in all iteration rounds, target strain rate-scaling coefficient information is determined from multiple sets of first-iteration strain rate-scaling coefficient information corresponding to all iteration rounds; the sum of the root mean square errors between the multiple fifth deformation-force information under multiple first-type extrusion rates corresponding to the target strain rate-scaling coefficient information and the multiple sixth deformation-force information under multiple first-type extrusion rates is minimized; the multiple sixth deformation-force information is obtained by extruding the battery cell through extrusion experiments at multiple first-type extrusion rates; The The target strain rate-scaling factor information corresponding to each of the directions is updated into the model information of the first cell model respectively, to obtain a target cell model.

9. The method according to claim 8, characterized in that The determination of the plurality of sets of first iteration strain rate-scaling factor information corresponding to the next iteration round based on the plurality of sets of first strain rate-scaling factor information corresponding to the next iteration round, the plurality of sets of first iteration strain rate-scaling factor information corresponding to the current iteration round, and the plurality of sets of fifth deformation-force information corresponding to the plurality of first type extrusion rates respectively comprises: determine third strain rate-scaling coefficient information based on the plurality of groups of fifth deformation-force information corresponding to the plurality of first extrusion rates respectively, the plurality of groups of first iteration strain rate-scaling coefficient information, and the plurality of second approximation models preset; determine, as the plurality of groups of first iteration strain rate-scaling coefficient information corresponding to the next iteration round, the plurality of groups of first strain rate-scaling coefficient information preset corresponding to the next iteration round and the third strain rate-scaling coefficient information corresponding to the current iteration round.

10. The method according to claim 9, characterized in that The method for determining the third strain rate-scaling coefficient information based on the plurality of groups of fifth deformation-force information corresponding to the plurality of first extrusion rates respectively, the plurality of groups of first iteration strain rate-scaling coefficient information, and the plurality of second approximation models preset comprises: input the plurality of groups of first iteration strain rate-scaling coefficient information into the plurality of second approximation models to determine a plurality of groups of seventh deformation-force information corresponding to the plurality of first extrusion rates respectively; determine a second target approximation model from the plurality of second approximation models based on the plurality of groups of seventh deformation-force information corresponding to the plurality of first extrusion rates respectively under the plurality of second approximation models and the plurality of groups of fifth deformation-force information corresponding to the plurality of first extrusion rates respectively, wherein a sum of mean square errors between the plurality of groups of seventh deformation-force information corresponding to the plurality of first extrusion rates respectively and the plurality of groups of fifth deformation-force information corresponding to the plurality of first extrusion rates respectively is the minimum under the second target approximation model; perform iterative calculation on the plurality of groups of second iteration strain rate-scaling coefficient information as input of the second target approximation model to obtain a plurality of groups of eighth deformation-force information corresponding to the plurality of first extrusion rates respectively through the second target approximation model until a fourth iteration termination condition of the second target approximation model is satisfied, wherein the plurality of groups of second iteration strain rate-scaling coefficient information comprises a plurality of groups of second strain rate-scaling coefficient information, the second strain rate-scaling coefficient information comprises a plurality of first strain rate information preset and a plurality of second scaling coefficient information determined based on a fourth range; determine third strain rate-scaling coefficient information from the plurality of groups of second iteration strain rate-scaling coefficient information corresponding to all iteration rounds based on the plurality of groups of eighth deformation-force information corresponding to the plurality of first extrusion rates respectively under all iteration rounds and the plurality of sixth deformation-force information under the plurality of first extrusion rates, wherein a sum of mean square errors between the plurality of eighth deformation-force information under the plurality of first extrusion rates corresponding to the third strain rate-scaling coefficient information and the plurality of sixth deformation-force information under the plurality of first extrusion rates is the minimum.

11. The method according to claim 1, characterized in that The grid information comprises node information and element information, and the size information comprises cell shell information, expected size information of a shell grid, thickness information corresponding to a plurality of faces of the shell respectively, expected size information of a roll core grid, and roll core information. The method for determining grid information of a grid model of a battery cell based on size information of the battery cell comprises: determine first node information of each node in the plurality of faces and first cell information of each cell in the plurality of faces based on the cell shell information, the expected size information of the shell grid, and the thickness information corresponding to each of the plurality of faces; determine second node information of each node in the winding core and second cell information of each cell in the winding core based on the expected size information of the winding core grid, the winding core information, and the first node information of each node in the plurality of faces; determine grid information of the grid model based on the first node information corresponding to all nodes in the plurality of faces, the first cell information corresponding to all cells in the plurality of faces, the second node information corresponding to all nodes in the winding core, and the second cell information corresponding to all cells in the winding core.

12. The method according to claim 11, characterized in that The node information includes node number information and node position information; and the cell information includes cell number information. The method comprises the following steps of: determining first node number information and first node position information of each node based on the cell shell information, the expected size information of the shell grid, and the thickness information corresponding to each of the plurality of faces; determining first cell number information of each cell in the plurality of faces based on the cell shell information, the expected size information of the shell grid, the thickness information corresponding to each of the plurality of faces, and the first node number information corresponding to all nodes in the plurality of faces; the first cell number information comprises first sub-number information for identifying a cell and first node number information corresponding to nodes constituting the cell.

13. The method of claim 1, wherein The target extrusion test information includes target time-deformation-force information for each of the directions, and target deformation-force information for each of the directions; the directions; the extrusion test information includes first time-deformation-force information for each of the directions;​​​ The method comprises the following steps of: performing repeated data elimination on the first time-deformation-force information based on deformation information in the first time-deformation-force information to obtain second time-deformation-force information for each set of first time-deformation-force information in each direction; performing data screening on a plurality of sets of second time-deformation-force information based on force information in the plurality of sets of second time-deformation-force information to determine target time-deformation-force information for each direction; the force information in the target time-deformation-force information corresponds to the smallest mean square error value; performing data optimization on the target time-deformation-force information to determine target deformation-force information for each direction; based on determining target extrusion test information based on the target time-deformation-force information and the target deformation-force information corresponding to each of the directions, respectively.

14. The method according to claim 13, characterized in that The target time-deformation-force information comprises first sub-target time-deformation-force information corresponding to a plurality of first type extrusion rates and second sub-target time-deformation-force information corresponding to a second type extrusion rate; the first type extrusion rate is much greater than the second type extrusion rate; The method comprises the following steps of: performing data optimization on the target time-deformation-force information to determine target deformation-force information. The first sub-target time-deformation-force information is normalized based on the maximum force information in the first sub-target time-deformation-force information corresponding to the first type of extrusion rate, and a ninth deformation-force information is determined; and a first range sum is determined based on the ninth deformation-force information and a first preset number. The second sub-target time-deformation-force information is normalized based on the maximum force information in the second sub-target time-deformation-force information, and a tenth deformation-force information is determined; and a second range sum is determined based on the tenth deformation-force information and the first preset number. The target deformation-force information is determined based on the multiple first range sums, the multiple ninth deformation-force information, the tenth deformation-force information, and the second range sum.

15. The method according to claim 14, characterized in that The target deformation-force information is determined based on the multiple first range sums, the multiple ninth deformation-force information, the tenth deformation-force information, and the second range sum, including: The data stability of the multiple ninth deformation-force information is determined based on the multiple first range sums and the second range sum; In a case where the data stability of the multiple ninth deformation-force information meets a target condition, the target deformation-force information is determined based on a second preset number, the multiple ninth deformation-force information, and the tenth deformation-force information; In a case where the data stability of the multiple ninth deformation-force information does not meet the target condition, the multiple ninth deformation-force information is smoothed to obtain multiple eleventh deformation-force information; for each eleventh deformation-force information, a twelfth deformation-force information is determined based on maximum deformation information in the eleventh deformation-force information, the second preset number, and the eleventh deformation-force information; a thirteenth deformation-force information is determined based on maximum deformation information in the tenth deformation-force information, the second preset number, and the tenth deformation-force information; and the target deformation-force information is determined based on the multiple twelfth deformation-force information and the thirteenth deformation-force information.

16. The method of claim 14, wherein The first range sum is determined based on the ninth deformation-force information and a first preset number, including: Multiple fourteenth deformation-force information is selected from the ninth deformation-force information according to the first preset number, and a range of force information in each fourteenth deformation-force information is determined; All ranges are summed to determine the first range sum.

17. The method according to any one of claims 1 to 16, characterized in that The model information of the first battery cell model is determined by updating the model information of the initial battery cell model based on the first grid information, the second grid information, and the target extrusion test information, including: Target stop information is determined based on the first grid information, battery cell shell information, and the target extrusion test information; the target stop information is used to control the stop of the target battery cell model; A pressure head position information is determined based on the first grid information; the pressure head position information represents the position of a pressure head for extruding a battery cell on the battery cell; and Based on the first grid information, the second grid information, the pressure head position information, the target stop information, and the target extrusion test information, model information of the initial battery cell model is updated to obtain model information of the first battery cell model.

18. The method of claim 17, wherein The target stop information is determined based on the first grid information, battery cell shell information, and the target extrusion test information. determine, based on the first grid information and cell shell information, a second grid information third node number information corresponding to each of the directions respectively; the cell shell information includes length information of the cell, height information of the cell and thickness information of the cell, and the third node number information is a number of a node closest to a center point on a surface corresponding to each of the directions respectively. third node number information corresponding to each of the directions respectively; the cell shell information includes length information of the cell, height information of the cell and thickness information of the cell, and the third node number information is a number of a node closest to a center point on a surface corresponding to each of the directions respectively. determining a first difference value based on the thickness information of the battery cell in the battery cell housing information and the maximum deformation value in the target deformation-force information in the direction of the target extrusion test information, determining a first difference value based on the thickness information of the battery cell in the battery cell housing information and the maximum deformation value in the target deformation-force information in the direction of the target extrusion test information, determines a second difference value based on the length information of the battery cell in the battery cell housing information and the maximum deformation value in the target deformation-force information in the direction of the target extrusion test information. determines a second difference value based on the length information of the battery cell in the battery cell housing information and the maximum deformation value in the target deformation-force information in the direction of the target extrusion test information. Based on the cell height information in the cell casing information, and the target compression test information... The maximum deformation value in the target deformation-force information in the direction is used to determine the third difference; determining the target stop information based on the first difference value, the second difference value, the third difference value, and the third node number information corresponding to each of the directions, respectively.

19. The method of claim 17, wherein The pressure head position information is determined based on the first grid information. Based on the first grid information, the pressure head is determined to be in... The position information of the target node on the surface of the shell corresponding to each direction; the target node is used to represent the center of the surface; The pressure head position information is determined based on position information of target nodes corresponding to all directions.

20. An apparatus for determining a model of a battery cell, the apparatus comprising: The device comprises: The application discloses a method for establishing an initial battery cell model, and belongs to the technical field of battery cell modeling. The application discloses a method for establishing an initial battery cell model, and belongs to the technical field of battery cell modeling. A first determination module is configured to determine grid information of a grid model of a battery cell based on size information of the battery cell; the grid information of the grid model comprises first grid information of a shell of the battery cell and second grid information of a winding core of the battery cell; A second determination module is configured to perform preprocessing operations on the plurality of sets of extrusion test information to determine target extrusion test information; the preprocessing operations comprise repeated data elimination operations, data screening operations, and data optimization operations; An updating module is configured to update model information of an initial battery cell model based on the first grid information, the second grid information, and the target extrusion test information to obtain a target battery cell model. The updating module comprises: A first updating unit is configured to update model information of the initial battery cell model based on the first grid information, the second grid information, and the target extrusion test information to determine model information of a first battery cell model. The second receiving unit is used to... The target parameters corresponding to each direction are updated in the model information of the first cell model to obtain the target cell model; the target parameters include target stress-strain information and / or target strain rate-scaling factor information.

21. An electronic device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, The processor implements the steps in the method of any one of claims 1 to 19 when executing the program.

22. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program implements the steps in the method of any one of claims 1 to 19 when executed by the processor.

23. A computer program product comprising computer programs or instructions, characterized in that, The computer program or instructions implement the steps in the method of any one of claims 1 to 19 when executed by the processor.

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