Battery cell model determination method and device, equipment, medium and product

Abstract

The invention provides a battery cell model determination method and device, equipment, a medium and a product. The method comprises the following steps: acquiring target information of a battery cell; the target information of the battery cell comprises size information of the battery cell, multiple groups of extrusion test information and model information of the initial battery cell model; 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 roll core of the battery cell; performing preprocessing operation on the multiple groups of extrusion test information, and determining target extrusion test information; the preprocessing operation comprises at least one of the following operations: repeated data elimination operation, data screening operation and data optimization operation; and on the basis of the first grid information, the second grid information and the target extrusion test information, updating the model information of the initial battery cell model to obtain a target battery cell model, so that the obtained target battery cell model can accurately reflect the mechanical behavior of the battery cell.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automobiles, in particular to a determination method and device of a battery cell model, an equipment, a medium and a product. BACKGROUND

[0002] In the field of automobiles, the safety of a battery pack as a key energy storage unit directly affects the safety performance of the whole vehicle. The accurate modeling of the mechanical behavior of a battery cell as a basic unit of the battery pack is of great significance to the evaluation of the safety of the battery pack under extreme conditions such as collision, and therefore, it is an important issue in engineering design to establish a battery cell model that can accurately reflect the mechanical behavior of the battery cell. SUMMARY

[0003] One of the purposes of the present application is to provide a determination method of a battery cell model to establish a battery cell model that can accurately reflect the mechanical behavior of the battery cell. The second purpose of the present application is to provide a determination device of a battery cell model. The third purpose of the present application is to provide an electronic device. The fourth purpose of the present application is to provide a computer-readable storage medium. The fifth purpose of the present application is to provide a computer program product.

[0004] In order to achieve the above-mentioned purposes, the technical solutions adopted by the present application are as follows: The determination method of the battery cell model provided by the embodiments of the present application comprises the following steps: obtaining target information of a battery cell; the target information of the battery cell comprises size information of the battery cell, a plurality of extrusion test information and model information of an initial battery cell model; 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 plurality of extrusion test information to determine target extrusion test information; the preprocessing operation comprises at least one of the following: a repeated data elimination operation, a data screening operation and a data optimization operation; 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 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; and updating the model information of the first battery cell model based on the target parameter corresponding to each direction in the target direction to obtain the target battery cell model. xyz The target parameter corresponding to each direction in the target direction is updated to the model information of the first battery cell model to obtain the target battery cell model.

[0005] According to the above technical means, first, the grid information of the grid model of the battery cell is determined through the size information of the battery cell in the target information, wherein the grid information of the grid model includes first grid information for describing the grid of the shell of the battery cell, and second grid information for describing the grid of the jelly-roll of the battery cell, which realizes parameterization of the grid model of the battery cell, so that the node order, unit direction and node position of the grid model are uniquely determined, and different grid models caused by human factors are avoided, the standardization of the grid model is improved, and the generation speed of the grid model is improved, which can effectively reduce manual intervention and improve modeling efficiency. Secondly, by preprocessing a plurality of groups of extrusion test information, redundant data is removed and data closest to the actual test results is retained, which can improve the accuracy and reliability in the subsequent modeling process. Finally, based on the first grid information and the second grid information of the grid model and the target extrusion test information, the model information of the initial battery cell model is updated to generate a first battery cell model in an intermediate state. Subsequently, the target parameters corresponding to all directions are updated into the first battery cell model, on the one hand, each direction has an independent target parameter to describe the mechanical properties of the battery cell under different extrusion rates, so that the target battery cell model can reflect the anisotropy and dynamic effect of the battery cell, and the target battery cell model can accurately reflect the mechanical behavior of the battery cell under different extrusion scenarios, thereby improving the credibility of the simulation results of the target battery cell model. On the other hand, the simulation results of the first battery cell model are gradually approximated to the experimental measurement results through iteration, and finally the target battery cell model is obtained, which can improve the model accuracy of the target battery cell model and provide strong support for the safety design of the battery pack.

[0006] Further, the target information includes a plurality of groups of shell material information of the shell, and the method further includes: determining target shell material information based on the plurality of 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 the curve information of the target stress-strain curve based on the target shell material information; 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 the model information of the first battery cell model, including: 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.

[0007] According to the above technical means, first, by screening a plurality of shell material information, a group of force information corresponding to the minimum mean square error value is selected as the target shell material information, thereby effectively improving the accuracy of the target battery cell model. Then, the corresponding target stress-strain curve is generated based on the target shell material information, and is updated to the model information of the first battery cell model, so that the finally generated target battery cell model can more accurately describe the deformation characteristics of the battery cell shell under stress conditions, thereby improving the credibility of the simulation results of the target battery cell model. 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.

[0008] Further, based on the plurality of shell material information, the target shell material information is determined, including: determining the first type of shell material information in the plurality of shell material information, and a plurality of second type of shell material information; the data amount of the first type of shell material information is greater than the data amount corresponding to the plurality of second type of shell material information respectively; based on the first type of shell material information, the plurality of second type of shell material information is respectively interpolated to obtain a plurality of third type of shell material information; the data amount of the first type of shell material information is equal to the data amount corresponding to the plurality of third type of shell material information respectively; based on the first type of shell material information and the plurality of third type of shell material information, the target shell material information is determined.

[0009] According to the above technical means, first, by taking the first type of shell material information with large data amount as the reference, the second type of shell material information with small data amount is interpolated to generate a plurality of third type of shell material information, so that the third type of shell material information is consistent in quantity with the first type of shell material information, facilitating unified processing. Then, based on the first type of shell material information and the plurality of third type of shell material information, the optimal target shell material information is determined. Through this method, on the one hand, the high data amount of the shell material information can be fully utilized to supplement the low data amount of the shell material information, improving the overall data quality; on the other hand, the interpolation method fills the data gap, making the shell material information more complete, thereby improving the accuracy of the simulation results of the target battery cell model under different working conditions, and further improving the accuracy and reliability of the battery pack collision safety evaluation.

[0010] Further, based on the target shell material information, the curve information of the target stress-strain curve is determined, including: based on the plurality of deformation information and the plurality of force information in the target shell material information, the curve information of the first stress-strain curve is determined; based on the curve information of the first stress-strain curve, the first elastic strain information is determined; based on the first elastic strain information and the curve information of the first stress-strain curve, the curve information of the first stress-plastic strain curve is determined; based on the curve information of the first stress-plastic strain curve, the curve information of the target stress-strain curve is determined.

[0011] 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.

[0012] 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 battery cell model, and a target battery cell model is obtained.

[0013] According to the above technical means, for xyz In each iteration round, a plurality of sets of first iteration strain-stress information is generated for each direction, and is applied to the first battery cell model, and first deformation-force information corresponding to each direction is obtained through simulation of the first battery cell model. When the set termination condition is met, the target strain-stress information with the highest fitting degree with the experimental data is selected as the target parameter by comparing the differences between the simulation results of the first battery cell model in all iteration rounds and the experimental data. And the xyz The target strain-stress information corresponding to each direction is updated into the first battery cell model to form a final target battery cell model. In this way, on the one hand, the automatic optimization of parameters can reduce the time cost of human trial and error; on the other hand, the iterative approach gradually approaches the optimal solution, improving the accuracy and stability of the target battery cell model.

[0014] Further, based on the plurality of sets of first strain-stress information corresponding to the next iteration round, and the plurality of sets of first deformation-force information and the plurality of sets of first iteration strain-stress information corresponding to the current iteration round, the plurality of sets of first iteration strain-stress information corresponding to the next iteration round is determined, including: determining 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 the plurality of first approximation models; and determining 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 as the plurality of sets of first iteration strain-stress information corresponding to the next iteration round.

[0015] According to the above technical means, by introducing a plurality of first approximation models to predict the plurality of sets of first iteration strain-stress information in the current iteration, and determining the third strain-stress information based on the plurality of sets of second deformation-force information obtained by prediction and the plurality of sets of first deformation-force information, and applying it to the next iteration round, this method can speed up the optimization process and reduce unnecessary calculation amount, thereby improving the calculation efficiency of the target strain-stress information.

[0016] Further, based on the plurality of sets of first deformation-force information, the plurality of sets of first iterative strain-stress information, and the plurality of first approximation models, the third strain-stress information is determined, including: inputting the plurality of sets of first iterative 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; 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, a first target approximation model is determined from the plurality of first approximation models; the mean square error 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; the plurality of sets of second iterative strain-stress information is taken as the input of the first target approximation model for iterative calculation, and the plurality of sets of third deformation-force information is obtained through the first target approximation model until the second iteration termination condition of the first target approximation model is met; wherein the plurality of sets of second iterative strain-stress information includes the plurality of sets of second strain-stress information, and the second strain-stress information includes the plurality of first strain information and the plurality of second stress information determined based on the second range; based on the plurality of sets of third deformation-force information corresponding to all iteration rounds respectively and the fourth deformation-force information, the third strain-stress information is determined from the plurality of sets of second iterative strain-stress information corresponding to all iteration rounds respectively; the mean square error between the third strain-stress information corresponding to the third deformation-force information and the fourth deformation-force information is the smallest.

[0017] According to the above technical means, first, the first iterative strain-stress information of the current iteration round is input into the plurality of first approximation models to generate the 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 result (first deformation-force information), the first target approximation model with the best performance is selected for parameter optimization of strain-stress information; finally, the third strain-stress information is determined based on the first target approximation model, and the optimal solution is gradually approached through this iterative method, which improves the accuracy and efficiency of strain-stress information parameter optimization.

[0018] Further, the target parameters include target strain rate-scaling coefficient information; the target parameters corresponding to each of the directions are updated to the model information of the first battery cell model to obtain a target battery cell model, including: for each of the directions xyz Further, the target parameters include target strain rate-scaling coefficient information; the target parameters corresponding to each of the directions are updated to the model information of the first battery cell model to obtain a target battery cell model, including: for each of the directions xyz Further, the target parameters include target strain rate-scaling coefficient information; the target parameters corresponding to each of the directions are updated to the model information of the first battery cell model to obtain a target battery cell model, including: for each of the directions xyzIn each of the directions, update the plurality of groups of the first iteration strain rate-scaling coefficient information into the model information of the first battery cell model, and obtain, by the first battery cell model, a plurality of groups of the fifth deformation-force information corresponding to the plurality of first extrusion rates respectively; for xyz In each of the directions, based on the plurality of groups of the first iteration strain rate-scaling coefficient information corresponding to the next iteration round and the plurality of groups of the fifth deformation-force information corresponding to the plurality of first extrusion rates respectively, determine the plurality of groups of the first iteration strain rate-scaling coefficient information corresponding to the next iteration round until the third iteration termination condition is met; for xyz In each of the directions, based on the plurality of groups of the fifth deformation-force information corresponding to the plurality of first extrusion rates respectively in all iteration rounds, determine the target strain rate-scaling coefficient information from the plurality of groups of the first iteration strain rate-scaling coefficient information corresponding to all iteration rounds respectively; the sum of the mean square error values between the plurality of fifth deformation-force information corresponding to the plurality of first extrusion rates under the target strain rate-scaling coefficient information and the plurality of sixth deformation-force information under the plurality of first extrusion rates is the minimum; the plurality of sixth deformation-force information is obtained by extrusion experiment on the battery cell by the plurality of first extrusion rates; and update xyz In each of the directions, update the target strain rate-scaling coefficient information corresponding to each direction respectively into the model information of the first battery cell model to obtain the target battery cell model.

[0019] According to the above technical means, in each iteration round, a plurality of groups of the first iteration target strain rate-scaling coefficient information is generated and applied to the first battery cell model, and the fifth deformation-force information corresponding to the plurality of first extrusion rates respectively is obtained by simulation of the first battery cell model. When the set termination condition is met, by comparing the differences between the simulation results of the first battery cell model in all iteration rounds and the experimental data, the target strain rate-scaling coefficient information with the highest fitting degree with the experimental data is selected as the target parameter. And update xyz In each of the directions, update the target strain rate-scaling coefficient information corresponding to each direction respectively into the first battery cell model to form the final target battery cell model. In this way, on the one hand, the automatic optimization of parameters can be realized, and the time cost of human trial and error can be reduced; on the other hand, the optimal solution is gradually approached by iteration, and the accuracy and stability of the target battery cell model are improved.

[0020] Further, based on the preset plurality of groups of first strain rate-scaling factor information corresponding to the next iteration round, and the plurality of groups of first iteration strain rate-scaling factor information corresponding to the current iteration round and 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 factor information corresponding to the next iteration round is determined, including: determining third strain rate-scaling factor 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 factor information, and the preset plurality of second approximation models; and determining the plurality of groups of first iteration strain rate-scaling factor information corresponding to the next iteration round based on the preset plurality of groups 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.

[0021] According to the above technical means, by introducing a plurality of second approximation models to predict the plurality of groups of first iteration strain rate-scaling factor information of the current iteration, and based on the third strain rate-scaling factor information obtained by prediction, it is applied to the next iteration round. Through this method, the optimization process can be accelerated, unnecessary calculation amount can be reduced, and the calculation efficiency of the target strain-stress information can be improved.

[0022] Further, 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 iterative strain rate-scaling coefficient information, and the plurality of second approximate models preset, the third strain rate-scaling coefficient information is determined, including: inputting the plurality of groups of first iterative strain rate-scaling coefficient information into the plurality of second approximate models, to determine a plurality of groups of seventh deformation-force information corresponding to the plurality of first extrusion rates respectively; 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 approximate models, and the plurality of groups of fifth deformation-force information corresponding to the plurality of first extrusion rates respectively, a second target approximate model is determined from the plurality of second approximate models; the sum of the mean square differences 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 corresponding to the second target approximate model is the minimum; the plurality of groups of second iterative strain rate-scaling coefficient information are taken as the input of the second target approximate model for iterative calculation, and the plurality of groups of eighth deformation-force information corresponding to the plurality of first extrusion rates respectively are obtained through the second target approximate model, until the fourth iteration termination condition of the second target approximate model is satisfied; wherein the plurality of groups of second iterative strain rate-scaling coefficient information include the plurality of groups of second strain rate-scaling coefficient information, the second strain rate-scaling coefficient information includes the plurality of first strain rate information preset and the plurality of second scaling coefficient information determined based on the fourth range; based on the plurality of groups of eighth deformation-force information corresponding to the plurality of first extrusion rates respectively in all iteration rounds, and the plurality of sixth deformation-force information under the plurality of first extrusion rates, the third strain rate-scaling coefficient information is determined from the plurality of groups of second iterative strain rate-scaling coefficient information corresponding to all iteration rounds respectively; the sum of the mean square differences 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.

[0023] According to the above technical means, first, the first iterative strain rate-scaling coefficient information of the current iteration round is input into the plurality of second approximate models to generate the plurality of seventh deformation-force information under the plurality of first extrusion rates; then, by comparing the differences between the seventh deformation-force information under the plurality of first extrusion rates output by each second approximate model and the actual simulation results (the fifth deformation-force information under the plurality of first extrusion rates), the second target approximate 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 approximate model, and the optimal solution is gradually approached through this iterative method, which improves the accuracy and efficiency of parameter optimization of the strain rate-scaling coefficient information.

[0024] Further, the grid information includes node information and cell information; the size information includes battery shell information, expected size information of the shell grid, thickness information corresponding to each of the plurality of surfaces, expected size information of the roll core grid, and roll core information; based on the size information of the battery cell, the grid information of the grid model of the battery cell is determined, including: based on the battery shell information, the expected size information of the shell grid, and the thickness information corresponding to each of the plurality of surfaces, determining the first node information of each node in the plurality of surfaces, and the first cell information of each cell in the plurality of surfaces; based on the expected size information of the roll core grid, the roll core shell information, and the first node information of each node in the plurality of surfaces, determining the second node information of each node in the roll core, and the second cell information of each cell in the roll core; based on the first node information corresponding to each of all nodes in the plurality of surfaces, the first cell information corresponding to each of all cells in the plurality of surfaces, the second node information corresponding to each of all nodes in the roll core, and the second cell information corresponding to each of all cells in the roll core, the grid information of the grid model is determined.

[0025] According to the above technical means, first, based on the battery shell information, the expected size information of the shell grid, and the thickness information corresponding to each of the plurality of surfaces, the first node information of each surface of the shell and the first cell information are generated; then, based on the roll core information, the expected size information of the roll core grid, the second node information and the second cell information inside the roll core are generated, and finally, the grid information of the shell and the roll core is integrated together to form the complete grid information of the grid model of the battery cell. In this way, on the one hand, the accuracy of the structure of the grid model can be guaranteed, and the modeling deviation caused by human design errors can be avoided; on the other hand, through the standardized grid generation process, the modeling efficiency and consistency of the grid model are improved.

[0026] Further, the node information includes node number information and node position information; the cell information includes cell number information; based on the battery shell information, the expected size information of the shell grid, and the thickness information corresponding to each of the plurality of surfaces, the first node information of each node in the plurality of surfaces and the first cell information of each cell in the plurality of surfaces are determined, including: based on the battery shell information, the expected size information of the shell grid, and the thickness information corresponding to each of the plurality of surfaces, the first node number information and the first node position information of each node are determined; based on the battery shell information, the expected size information of the shell grid, the thickness information corresponding to each of the plurality of surfaces, and the first node number information corresponding to each of all nodes in the plurality of surfaces, the first cell number information of each cell in the plurality of surfaces is determined; the first cell number information includes first sub-number information for identifying the cell, and the first node number information corresponding to the nodes constituting the cell.

[0027] According to the above technical means, by defining the first node information of each node in the shell mesh and the first element information of each element, the parameterization degree of the shell mesh is improved, and the management of the shell mesh is simplified, which can facilitate subsequent modification and expansion of the shell mesh on the one hand; 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.

[0028] Further, the target extrusion test data includes xyz target time-deformation-force information of each of the directions, and target deformation-force information of each of the directions; xyz The directions include x a direction, y a direction, and z a direction; the extrusion test information includes xyz first time-deformation-force information of each of the directions; the preprocessing operation on the multiple sets of extrusion test information to determine the target extrusion test data includes: for each set of first time-deformation-force information in each direction, based on the deformation information in the first time-deformation-force information, the first time-deformation-force information is subjected to a duplicate data elimination operation to obtain second time-deformation-force information; for each direction, based on the force information in the multiple sets of second time-deformation-force information, the multiple sets of second time-deformation-force information are subjected to a data screening operation 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; for each direction, the target time-deformation-force information is subjected to a data optimization operation to determine the target deformation-force information; based on xyz the target time-deformation-force information and the target deformation-force information corresponding to each of the directions respectively, the target extrusion test data is determined.

[0029] According to the above technical means, by performing deduplication, screening and optimization processing on the multiple sets of extrusion test information, it is ensured that the target extrusion test information used finally has high representativeness and stability, which can reduce the influence of invalid or noise data on the establishment process of the target battery model on the one hand, and by using the optimized data as the input of the training of the target battery model, the accuracy and reliability of the target battery model are improved.

[0030] Further, the target time-deformation-force information includes first sub-target time-deformation-force information corresponding to each first extrusion rate of the plurality of first extrusion rates, and second sub-target time-deformation-force information corresponding to the second extrusion rate; the first extrusion rate is much greater than the second extrusion rate; the data optimization operation on the target time-deformation-force information is used to determine the target deformation-force information, including: for each first extrusion rate, based on the maximum force information in the first sub-target time-deformation-force information corresponding to the first extrusion rate, the first sub-target time-deformation-force information is normalized to determine the ninth deformation-force information; based on the ninth deformation-force information and the first preset number, the first range sum is determined; based on the maximum force information in the second sub-target time-deformation-force information, the second sub-target time-deformation-force information is normalized to determine the tenth deformation-force information; based on the tenth deformation-force information and the first preset number, the second range sum is determined; based on the plurality of first range sums, the plurality of ninth deformation-force information, the tenth deformation-force information and the second range sum, the target deformation-force information is determined.

[0031] According to the above technical means, the extrusion test information under different extrusion rates is quantitatively evaluated through normalization processing and range analysis on the extrusion test information, and then the target deformation-force information under different extrusion rates is determined. On the one hand, the scale difference between the data under different test conditions can be eliminated through normalization processing, and the comparability of the data is improved; on the other hand, through range analysis, the region with large data fluctuation is identified, so that targeted optimization measures are taken to improve the quality and stability of the data.

[0032] Further, based on the plurality of first range sums, the plurality of ninth deformation-force information, the tenth deformation-force information and the second range sum, the target deformation-force information is determined, including: based on the plurality of first range sums and the second range sum, the data stability of the plurality of ninth deformation-force information is determined; in the case that the data stability of the plurality of ninth deformation-force information meets the target condition, based on the second preset number, the plurality of ninth deformation-force information and the tenth deformation-force information, the target deformation-force information is determined; in the case that the data stability of the plurality of ninth deformation-force information does not meet the target condition, the plurality of ninth deformation-force information is respectively smoothed to obtain a plurality of eleventh deformation-force information; for each eleventh deformation-force information, based on the maximum deformation information in the eleventh deformation-force information, the second preset number and the eleventh deformation-force information, the twelfth deformation-force information is determined; based on the maximum deformation information in the tenth deformation-force information, the second preset number and the tenth deformation-force information, the thirteenth deformation-force information is determined; based on the plurality of twelfth deformation-force information and the thirteenth deformation-force information, the target deformation-force information is determined.

[0033] According to the above technical means, by evaluating the data stability based on the first range sum and the second range sum, and selecting different data processing strategies according to the stability result, unreliable data can be effectively filtered out, and the model accuracy of the target battery cell model can be improved.

[0034] Further, based on the ninth deformation-force information and the first preset number, the first range sum is determined, including: selecting a plurality of fourteenth deformation-force information from the ninth deformation-force information according to the first preset number, and determining the range of force information in each fourteenth deformation-force information; summing all the ranges to determine the first range sum.

[0035] According to the above technical means, by setting a fixed sampling interval, samples are extracted from the ninth deformation-force information, and the range thereof is calculated to evaluate the fluctuation of the data, which can on the one hand quantitatively measure the data stability of the ninth deformation-force information; on the other hand, by fixed interval sampling, the consistency and comparability of the ninth deformation-force information analysis are ensured.

[0036] Further, based on the first grid information, the second grid information and the target extrusion test information, the model information of the initial battery cell model is updated to determine the model information of the first battery cell model, including: based on the first grid information, the battery cell shell information and the target extrusion test information, the target stop information is determined; the target stop information is used to control the stop of the target battery cell model; based on the first grid information, the position information of the pressure head is determined; the position information of the pressure head is used to represent the position of the pressure head for extruding the battery cell on the battery cell; based on the first grid information, the second grid information, the position information of the pressure head, the target stop information, and the target extrusion test information xyz target deformation-force information in each direction, the model information of the initial battery cell model is updated to obtain the model information of the first battery cell model.

[0037] According to the above technical means, by setting the target stop information and the position information of the pressure head and updating them into the model information of the initial battery cell model, the model accuracy of the target battery cell model can be improved, thereby improving the simulation efficiency and result reliability of the target battery cell model, and further supporting the safety evaluation and optimization of the battery pack in the design stage.

[0038] Further, based on the first grid information, the battery cell shell information and the target extrusion test information, the target stop information is determined, including: based on the first grid information and the battery cell shell information, the third node number information corresponding to each direction in the battery cell is determined; the battery cell shell information includes the length information, the height information and the thickness information of the battery cell, and the third node number information is the third node number information corresponding to each direction in the battery cell. xyz xyz ​the number of the node closest to the center point on the face corresponding to each direction; based on the thickness information of the battery cell in the battery cell shell information, and the maximum deformation value in the target deformation-force information in the direction x the maximum deformation value in the target deformation-force information in the direction, to determine a first difference value; based on the length information of the battery cell in the battery cell shell information, and the maximum deformation value in the target deformation-force information in the direction y the maximum deformation value in the target deformation-force information in the direction, to determine a second difference value; based on the height information of the battery cell in the battery cell shell information, and the maximum deformation value in the target deformation-force information in the direction z the maximum deformation value in the target deformation-force information in the direction, to determine a third difference value; based on the first difference value, the second difference value, the third difference value, and xyz the third node number information corresponding to each of the directions, to determine the target stop information.

[0039] According to the above technical means, the target stop information is generated through multi-direction difference value calculation based on the first grid information, the battery cell shell information and the target extrusion test information, so that the running stop condition of the target battery cell model in different directions can be effectively determined, and excessive extrusion of the battery cell is avoided to cause excessive deformation of the battery cell.

[0040] Further, based on the first grid information, the ram position information is determined, including: based on the first grid information, the position of the ram in xyz the position information of the target node on the face of the shell corresponding to each of the directions; the target node is used to represent the center of the face; based on the position information of the target node corresponding to all directions, the ram position information is determined.

[0041] According to the above technical means, the target node is defined and the ram position is determined in combination with the position information of the target node from multiple directions, and this operation mode can improve the simulation accuracy of the battery cell model under the action of external force in multiple directions, and further make the evaluation of the mechanical properties of the battery cell model more reliable.

[0042] The application discloses a kind of determination device of battery cell model, device includes: acquisition module, for obtaining the target information of battery cell;The target information of battery cell includes the size information of battery cell, multiple groups of extrusion test information and the model information of initial battery cell model;First determination module is used to determine the grid information of the grid model of battery cell based on the size information of battery cell;The grid information of grid model includes the first grid information of the shell of battery cell, and the second grid information of the roll core of battery cell;Second determination module is used to determine target extrusion test information by carrying out preprocessing operation to multiple groups of extrusion test information;Preprocessing operation includes at least one of the following: repeated data elimination operation, data screening operation, data optimization operation;Update module is used to update the model information of initial battery cell model based on the first grid information, the second grid information and target extrusion test information, obtains target battery cell model;Wherein, first update unit is used to update the model information of initial battery cell model based on the first grid information, the second grid information and the target extrusion test information, determines the model information of first battery cell model;Second obtaining unit is used to update the model information of first battery cell model by the target parameter corresponding to each direction in the direction to the model information of first battery cell model, obtains target battery cell model. xyz Direction in each direction corresponds to target parameter update to the model information of the first battery cell model, obtains target battery cell model.

[0043] An electronic device includes a memory and a processor, the memory stores a computer program that can run on the processor, and the processor implements part or all of the steps of the above method when executing the program.

[0044] A computer readable storage medium has a computer program stored thereon, and the computer program is executed by a processor to implement part or all of the steps of the above method.

[0045] A computer program product includes a computer program or instructions, and part or all of the steps of the above method are executed by a processor when the computer program or instructions are executed.

[0046] The beneficial effects of the present application are as follows: (1) Firstly, the grid information of the cell grid model is determined through the size information of the cell in the target information, wherein the grid information of the cell grid model includes first grid information for describing the grid of the shell of the cell and second grid information for describing the grid of the winding core of the cell, the grid model is parameterized, the node order, unit direction and node position of the grid model are uniquely determined, different grid models caused by human factors are avoided, the standardization of the grid model is improved, and the generation speed of the grid model is improved. Secondly, the redundant data is removed and the data closest to the actual test result is retained through the preprocessing operation on the multiple groups of extrusion test information, so as to improve the accuracy and reliability in the subsequent modeling process. Finally, 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, so as to generate a target cell model which is closer to the actual mechanical response, which can effectively reduce the manual intervention and improve the modeling efficiency on the one hand, and significantly improve the accuracy and applicability of the target cell model on the other hand, thereby providing a strong support for the safety design of the battery pack of the electric vehicle.

[0047] (2) The credibility of the simulation result of the target cell model is improved to provide a scientific basis for the collision safety design of the battery pack and reduce the misjudgment risk caused by the error of the material parameters.

[0048] (3) By defining the first node information of each node in the shell grid and the first unit information of each unit, the parameterization degree of the shell grid is improved, and the management of the shell grid is simplified, which can facilitate the subsequent modification and expansion of the shell grid on the one hand, and improve the readability and maintainability of the shell grid on the other hand.

[0049] (4) Firstly, 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 a first cell model in an intermediate state. Subsequently, the target parameters in the first cell model are updated, 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 effect of the cell; on the other hand, the simulation result of the first cell model is gradually approximated to the experimental measurement result through iteration, and finally the target cell model is obtained, so that the model accuracy of the target cell model is improved. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 An implementation process schematic of a cell model determination method provided by the present application Figure 1 ; Figure 2 A schematic of a shell of a cell provided by the present application Figure 1 ; Figure 3 A schematic of a housing of a battery cell provided for the present application Figure 2 ; Figure 4 A schematic of a housing of a battery cell provided for the present application Figure 3 ; Figure 5 A schematic of a housing of a battery cell provided for the present application Figure 4 ; Figure 6 A schematic of a housing of a battery cell provided for the present application Figure 5 ; Figure 7 A schematic of a housing of a battery cell provided for the present application Figure 6 ; Figure 8 A schematic of a housing of a battery cell provided for the present application Figure 7 ; Figure 9 A schematic of a jelly-roll of a battery cell provided for the present application Figure 10 An implementation flow of a method for determining a battery cell model provided for the present application Figure 2 ; Figure 11 An implementation flow of a method for determining a battery cell model provided for the present application Figure 3 ; Figure 12 An implementation flow of a method for determining a battery cell model provided for the present application Figure 4 ; Figure 13 An implementation flow of a method for determining a battery cell model provided for the present application Figure 5 ; Figure 14 An implementation flow of a method for determining a battery cell model provided for the present application Figure 6 ; Figure 15 An implementation flow of a method for determining a battery cell model provided for the present application Figure 7 ; Figure 16 An implementation flow of a method for determining a battery cell model provided for the present application Figure 8 ; Figure 17 An implementation flow of a method for determining a battery cell model provided for the present application Figure 9 ; Figure 1 A schematic of a determining device for a battery cell model provided for the present application

[0051] It should be noted that the "first", "second" above are only used to distinguish different schemes, and do not represent the advantages or disadvantages of the schemes or the priority in the implementation process. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be described in further detail below with reference to the drawings, and the described embodiments should not be regarded as limiting the present application. All other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0053] It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present application in a schematic manner, and only the components related to the present application are shown in the diagrams, not the number, shape and size of the components when actually implemented. The actual implementation of each component may be a random change, and the component layout pattern may be more complex.

[0054] The embodiment of the present application provides a method for determining a battery cell model. The method can be executed by an electronic device, for example, a computer, a server, etc. The present application does not limit this. As shown in the method can include steps S100-S130: xyz Step S100: Obtain target information of a 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; In some embodiments, the target information of the battery cell can refer to obtaining the size information of a single battery cell, a plurality of groups of extrusion test information of the single battery cell, and model information of an initial battery cell model of the single battery cell. The size information of the single battery cell can be obtained by measuring the entity of the single battery cell; the plurality of groups of extrusion test information of the single battery cell can be obtained by performing extrusion tests on the single battery cell in different directions, respectively; and the model information of the initial battery cell model of the single battery cell can be obtained by performing a simulation on the single battery cell. x directions, y directions, and z directions, respectively.

[0055] In some embodiments, the size information of the battery cell, the plurality of groups of extrusion test information, and the model information of the initial battery cell model are stored in different files, respectively. By performing a reading operation on all the files, the target information of the battery cell can be obtained.

[0056] For example, the size information of the battery cell is pre-stored in a battery cell size position table. By reading the battery cell size position table, the size information of the battery cell can be obtained. The plurality of groups of extrusion test information are pre-stored in an extrusion test data table. By reading the extrusion test data table, the plurality of groups of extrusion test information can be obtained.

[0057] ​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.

[0058] 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.

[0059] 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.

[0060] The model information of the initial cell model refers to the preliminary cell model built based on experience or existing data before optimization.

[0061] 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. Here, the mesh model is a digital representation formed by dividing the continuous geometric space into a finite number of discrete elements (such as triangles, tetrahedrons, etc.) and nodes (the vertices of the elements).

[0062] In some embodiments, the mesh information can include, but is not limited to, node information and element information, wherein the node information can include node number information and node position information, and the element information can include element number information and node number information of the nodes constituting the element. For example, in the case of modeling the shell of the battery cell with quadrilateral elements, the nodes constituting the element can be N1, N2, N3, and N4. In the case of modeling the jellyroll of the battery cell with hexahedral elements, the nodes constituting the hexahedral element can be N1, N2, N3, N4, N5, N6, N7, and N8.

[0063] In some embodiments, the mesh model of the battery cell includes a first mesh model of the shell (i.e., shell mesh) and a second mesh model of the jellyroll (i.e., jellyroll mesh). It can be understood that the first mesh information is used to describe the first mesh model, and the second mesh information is used to describe the second mesh model.

[0064] It should be noted that the division method of the first mesh model can affect the stability and computational efficiency of the battery cell model. A reasonable mesh density can ensure simulation accuracy without wasting computational resources. Since the structure of the jellyroll 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 the nodes on the left and right sides are one-to-one corresponding, so as to prevent grid distortion or discontinuity during mesh construction.

[0065] Step S120: performing a preprocessing operation on the multiple sets of extrusion test information to determine target extrusion test information; the preprocessing operation includes at least one of the following: repeated data elimination operation, data screening operation, and data optimization operation; It can be understood that there can be repeated items, abnormal values, or low correlation data points in the multiple sets of extrusion test information. Therefore, it is necessary to perform a preprocessing operation on the multiple sets of extrusion test information to obtain high-quality target extrusion test information, thereby improving the model accuracy of the battery cell model. The repeated data elimination operation is used to remove redundant data generated by multiple measurements at the same time point, and only one valid data is retained. The data screening operation is used to select a set of data closest to the true physical behavior according to the mean square deviation or other statistical indicators as the basis for subsequent analysis. The data optimization operation is used to perform interpolation and smoothing processing on the screened data, so that these data are more consistent with the mechanical response law of the material, and the influence of test errors is reduced.

[0066] Step S130: 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 obtain a target battery cell model.

[0067] In some embodiments, the target battery 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 battery cell model.

[0068] It can be understood that the target battery cell model not only contains accurate geometric grid information, but also integrates optimized material parameters (such as target extrusion test information), which can more accurately predict the mechanical response of the battery cell under various working conditions, so that the target battery cell model can be used in the fields of battery pack collision safety design, structure optimization and performance evaluation, and thus the application of the target battery cell model can improve the design efficiency and reduce the experimental cost.

[0069] In the embodiments of the present application, first, the grid information of the grid model of the battery cell is determined through the size information of the battery cell in the target information, wherein the grid information of the grid model includes the first grid information for describing the grid of the shell of the battery cell and the second grid information for describing the grid of the winding core of the battery cell, which realizes the parameterization of the grid model of the battery cell, so that the node order, element direction and node position of the grid model are uniquely determined, and different grid models caused by human factors are avoided, thereby improving the standardization of the grid model and the generation speed of the grid model; second, the pre-processing operation is performed on the multiple sets of extrusion test information to remove redundant data and retain the data closest to the actual test results, which can improve the accuracy and reliability in the subsequent modeling process. Finally, the model information of the initial battery cell model is updated based on the first grid information, the second grid information and the target extrusion test information, so as to generate a target battery cell model closer to the actual mechanical response. In this way, on the one hand, the manual intervention can be effectively reduced and the modeling efficiency can be improved; on the other hand, the accuracy and applicability of the target battery cell model are also significantly improved, which provides a strong support for the safety design of the battery pack.

[0070] In some embodiments, the target information includes multiple sets of shell material information of the shell, and before step S130, the method further includes steps S140 and S150: Step S140: determining 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 the smallest; Here, the plurality of sets of shell material information refers to mechanical property data of different materials used for the shell of the battery cell. In some embodiments, the plurality of sets of shell material information can be determined based on a plurality of repeated tests, each of which generates a set of shell material information, each set of shell material information including a plurality of first data pairs, each data pair consisting of deformation information and force information, and the number of first data pairs being related to the number of data points of each repeated test. For example, the plurality of sets of shell material information can refer to 3 sets of shell material information, which are represented as wherein o = 1, 2, 3, represents 3 sets of repeated tests, and g represents g data points for each test.

[0071] In some embodiments, the shell material information can further include sample size data and a unit system of the sample size data, wherein the sample size data can include but is not limited to width, gauge length, and thickness.

[0072] In some embodiments, the plurality of sets of shell material information can be obtained by performing a plurality of tensile tests on the shell of a single battery cell by referring to a metal material tensile test standard.

[0073] In some embodiments, the plurality of sets of shell material information are pre-stored in a file, and the plurality of sets of shell material information of the battery cell can be obtained by performing a read operation on the file. For example, the plurality of sets of shell material information are pre-stored in a battery cell shell material test data table, and the plurality of sets of shell material information can be obtained by reading the battery cell shell material test data table.

[0074] It can be understood that each set of shell material information includes a plurality of first data pairs, and each data pair includes force information and deformation information corresponding to the force information, and the target shell material information is a set of optimal material parameters selected from the plurality of sets of shell material information. Since the mean square error value corresponding to the force information in the plurality of first data pairs in the target shell material information is the smallest, it can be deduced that the data distribution in the target shell material information is compact, which reflects the stability of the shell material corresponding to the target shell material information.

[0075] Step S150: determining curve information of a target stress-strain curve based on the target shell material information; 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 shell of the battery cell during stress, and intuitively presents the whole process of the shell from elastic deformation to plastic deformation until fracture, which is a key basis for evaluating the mechanical properties of the shell of the battery cell. The curve information of the target stress-strain curve can refer to the data for drawing the target stress-strain curve.

[0076] It can be understood that by determining the curve information of the target stress-strain curve, an important basis can be provided for subsequent modeling of the mechanical behavior of the cell model. For example, in simulation, the target stress-strain curve will be used to calculate the deformation response of the cell in different directions, so as to evaluate the pressure resistance and safety of the cell.

[0077] Correspondingly, the above step S130 can be implemented as: 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, and determining the model information of the first cell model.

[0078] In some embodiments, 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.

[0079] It should be noted that whether the curve information of the target stress-strain curve is updated to the model information of the initial cell model to obtain the model information of the first cell model can be determined according to the degree of simplification of the cell model. For example, if the cell model is simplified into multiple parts such as a cell shell and an internal cell winding, multiple sets of extrusion test information need to be obtained; if the cell model is simplified into only one part, multiple tensile tests on the cell shell are not needed, that is, the target stress-strain curve of the shell does not need to be determined.

[0080] In the embodiments of the present application, first, by screening the multiple sets of shell material information, the set with the minimum 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, the corresponding target stress-strain curve is generated based on the target shell material information, and is updated to the model information of the first cell model, so that the finally 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.

[0081] In some embodiments, the above step S140 can further include steps S141 to S143: Step S141: determining a first type of shell material information in the multiple sets of shell material information, and multiple second types of shell material information; the data amount of the first type of shell material information is greater than the data amount corresponding to each of the multiple second types of shell material information; In some embodiments, the plurality of sets of shell material information can refer to at least two sets of shell material information, each set of shell material information including a plurality of first data pairs, the plurality of sets of shell material information corresponding to a plurality of first data pairs with different data amounts, and the shell material information corresponding to the maximum data amount is determined as the first type of shell material information, so that the data amount of the plurality of first data pairs in the first type of shell material information is greater than the data amount of the plurality of first data pairs in the second type of shell material information.

[0082] For example, taking three sets of shell material information as an example, the three sets of shell material information include first shell material information (the plurality of first data pairs in the first shell material information include: A1-B1, A2-B2, A3-B3), second shell material information (the plurality of first data pairs in the second shell material information include: A11-B11, A12-B12, A13-B13, A14-B14), and third shell material information (the plurality of first data pairs in the third shell material information include: A111-B111, A112-B112, A113-B113, A114-B114, A115-B115), so it can be seen that the first type of shell material information can be the third shell material information, and the plurality of second type of shell material information can be the first shell material information and the second shell material information.

[0083] Step S142: based on the first type of shell material information, respectively interpolating the plurality of second type of shell material information to obtain a plurality of third type of shell material information; the data amount of the first type of shell material information is equal to the data amount corresponding to the plurality of third type of shell material information; Here, the interpolation processing is a numerical method for estimating the value of an unknown data point between known data points to generate a continuous function or data sequence. It can be understood that in this application, the first type of shell material information is used as a reference to interpolate each second type of shell material information, so that the second type of shell material information with smaller data amount is expanded into the third type of shell material information with the same data amount as the first type of shell material information. It should be noted that the interpolation processing method can improve the overall consistency of the data between the first type of shell material information and the plurality of third type of shell material information, and can reduce the error and deviation caused by data mismatch.

[0084] In some embodiments, a target first data pair in the plurality of first data pairs in the first type of shell material information is obtained, wherein the deformation information in the target first data pair is the maximum value in the plurality of first data pairs in the first type of shell material information. Based on the target first data pair, the plurality of first data pairs in each second type of shell material information is interpolated to obtain the plurality of first data pairs in the third type of shell material information .

[0085] For example, the plurality of first data pairs in the third shell material information includes: A111-B111, A112-B112, A113-B113, A114-B114, and A115-B115; the plurality of first data pairs obtained after interpolating the first shell material information includes: A111-B1', A112-B2', A113-B3', A114-B4', and A115-B5'; and the plurality of first data pairs obtained after interpolating the second shell material information includes: A111-B11', A112-B12', A113-B13', A114-B14', and A115-B15'.

[0086] Step S143: determining the target shell material information based on the first shell material information and the plurality of third shell material information.

[0087] In some embodiments, for each shell material information corresponding to the first shell material information and the plurality of third shell material information, the force information in the plurality of first data pairs in the shell material information is subjected to mean value processing to obtain a first force mean value corresponding data pair ; the force information in the plurality of first data pairs in each shell material information is subjected to mean square deviation calculation with the first force mean value to obtain a mean square deviation value corresponding to each shell material information; and based on the mean square deviation values corresponding to all shell material information respectively, the shell material information corresponding to the minimum mean square deviation value is determined as the target shell material information.

[0088] In the embodiments of the present application, first, the second shell material information with a smaller data amount is subjected to interpolation processing by taking the first shell material information with a larger data amount as a reference to generate a plurality of third shell material information, so that the third shell material information is consistent in quantity with the first shell material information, facilitating unified processing. Then, the optimal target shell material information is determined based on the first shell material information and the plurality of third shell material information. Through this method, on the one hand, the high-data-volume shell material information can be fully utilized to supplement the low-data-volume shell material information, improving the overall data quality; on the other hand, the interpolation method is used to fill in the data gaps, so that the shell material information is more complete, thereby improving the accuracy of the simulation results of the target battery cell model under different working conditions, and further improving the accuracy and reliability of the battery pack collision safety evaluation.

[0089] In some embodiments, the above step S150 can include steps S151 to S154: Step S151: determining the curve information of the first stress-strain curve based on the plurality of deformation information and the plurality of force information in the target shell material information; Here, the deformation information refers to the deformation amount of the shell of the battery cell under the action of external force recorded through tensile testing or other forms of mechanical testing, usually expressed in the form of length change or percentage. The deformation information reflects the reversible or irreversible deformation behavior of the shell of the battery cell under different stress conditions.

[0090] The force information refers to the value of the external force applied to the shell of the battery cell under the same test conditions, which is usually expressed in units of Newton (N) or kilo Newton (kN), and is used to reflect the ability of the shell of the battery cell to bear external load when subjected to external force.

[0091] The curve information of the first stress-strain curve includes a plurality of stress information and a plurality of strain information corresponding to the plurality of stress information respectively, wherein the strain information refers to a dimensionless quantity of the degree of deformation of the material, and the strain information is usually determined by the ratio of the deformation information to the original size of the battery cell; the stress information refers to the internal force per unit area, and the stress information is usually determined by the ratio of the force information to the cross-sectional area of the battery cell.

[0092] In this application, by converting the plurality of deformation information and the plurality of force information in the collected target shell material information into the curve information of the first stress-strain curve, the mechanical response of the shell of the battery cell under different loads can be more accurately described, thereby improving the accuracy of subsequent simulation modeling.

[0093] Step S152: determining the first elastic strain information based on the curve information of the first stress-strain curve; Here, the first elastic strain information refers to the maximum strain value of the shell of the battery cell in the elastic stage in the curve information of the first stress-strain curve. The elastic stage refers to the deformation range in which the shell of the battery cell can completely recover to its original state after the external force is removed. The first elastic strain information usually corresponds to the end point of the linear part of the curve information of the first stress-strain curve, that is, the critical point before the shell of the battery cell enters plastic deformation.

[0094] It can be understood that the first elastic strain information can effectively distinguish the elastic behavior and plastic behavior of the shell of the battery cell during the stress process, thereby improving the accuracy of the battery cell model.

[0095] Step S153: 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; The curve information of the first stress-plastic strain curve is the result of correcting the curve information of the first stress-strain curve based on the known first elastic strain information.

[0096] In some embodiments, the plurality of strain information in the curve information of the first stress-strain curve is subtracted by the first elastic strain information respectively, to obtain the curve information of the first stress-plastic strain curve. It can be understood that the first stress-plastic strain curve is used to describe the stress and strain relationship of the shell of the battery cell in the plastic deformation stage, that is, the nonlinear region remaining after the elastic part is removed.

[0097] Step S154: determining the curve information of the target stress-strain curve based on the curve information of the first stress-plastic strain curve.

[0098] In some embodiments, the plastic strain information corresponding to the maximum stress information is obtained from the curve information of the first stress-plastic strain curve ; and the curve information of the first stress-plastic strain curve is numerically processed within the range of the minimum strain information (0) and the maximum strain information (0) , to obtain the curve information of the target stress-strain curve (where g = 1, 2,..., 20). Among them, the plastic strain information corresponding to the maximum stress information obtained from the curve information of the first stress-plastic strain curve is the maximum strain information.

[0099] In an example, the first number of curve information can be selected from the curve information of the first stress-plastic strain curve within the range of the minimum strain information and the maximum strain information , to obtain the curve information of the target stress-strain curve.

[0100] In an example, the curve information of the target stress-strain curve can be obtained by interpolation processing based on the minimum strain information and the maximum strain information in the first number (for example, 18).

[0101] In the embodiments of the present application, first, the first elastic strain information is determined by using the plurality of deformation information and the plurality of force information in the target shell material information, to distinguish the response characteristics of the shell of the battery cell in the elastic stage and the plastic stage. Then, the first stress-plastic strain curve is constructed based on the first elastic strain information and the first stress-strain curve, to describe the behavior of the shell of the battery cell when permanent deformation occurs. Finally, the final target stress-strain curve is generated by combining the maximum stress information of the first stress-plastic strain curve and the curve information of the first stress-plastic strain curve. In this way, on the one hand, through the analysis of the material properties of the shell of the battery cell in stages, the ability to describe the complex mechanical behavior of the target battery cell model can be improved; on the other hand, the mechanical response of the shell of the battery cell under different loading conditions can be accurately described by the target stress-strain curve, and the prediction ability of the target battery cell model is improved, so as to effectively support the collision safety evaluation of the battery pack in the design stage.

[0102] In some embodiments, step S130 can further include step S131 and step S132. Step S131: 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, and determining the model information of the first battery cell model; Step S132: updating the target parameters corresponding to the directions respectively into the model information of the first battery cell model to obtain a target battery cell model. xyz Step S132: updating the target parameters corresponding to the directions respectively into the model information of the first battery cell model to obtain a target battery cell model.

[0103] By updating the target parameters to the model information of the first battery cell model, the key performance indicators of the first battery cell model can be accurately adjusted without changing the overall structure, so that it is more consistent with the actual test data. The above-mentioned updating of the target parameters can significantly improve the fitting effect and generalization ability of the target battery cell model, so that it can be more reliably used for engineering design and safety evaluation.

[0104] In some embodiments, the target parameters can include target strain-stress information and / or target strain rate-scaling factor information, wherein the target strain-stress information is key data for describing the relationship between the strain generated inside the battery cell and the stress suffered when the battery cell is subjected to external load. The target strain-stress information can reflect the mechanical response characteristics of the battery cell in different directions, and is the basis for establishing an accurate battery cell model.

[0105] In some embodiments, xyz The target strain-stress information corresponding to each of the directions respectively includes x The target strain-stress information of the direction, y The target strain-stress information of the direction, z The target strain-stress information of the direction, the target strain-stress information includes a plurality of target strain information and a plurality of target stress information, the plurality of target strain information and the plurality of target stress information correspond to each other one by one, and each target strain information and the first target stress information can constitute a second data pair.

[0106] In some embodiments, x The target strain-stress information of the direction is updated into the model information of the first battery cell model, the target strain-stress information of the direction is updated into the model information of the first battery cell model, and the target strain-stress information of the direction is updated into the model information of the first battery cell model. y The target strain-stress information of the direction is updated into the model information of the first battery cell model, the target strain-stress information of the direction is updated into the model information of the first battery cell model, and the target strain-stress information of the direction is updated into the model information of the first battery cell model. z The target strain-stress information of the direction is updated into the model information of the first battery cell model, wherein the determination manner of the target strain-stress information of each direction is the same, and the specific implementation process can be referred to steps S1321 to S1325 described below.

[0107] In some embodiments, xyzThe 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.

[0108] 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.

[0109] 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. z The 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] In some embodiments, the target parameters include target strain-stress information; step S132 above may include steps S1321 to S1325: Step S1321: For xyz In 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. 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.

[0114] 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... .

[0115] 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 round, the first range can be wherein, f 1 can be a first scaling factor of each iteration round set by the user.

[0116] In some embodiments, the plurality of groups of first strain-stress information can refer to p a group of first strain-stress information, wherein, .

[0117] In some embodiments, in the first iteration round, the plurality of groups of preset first strain-stress information is determined as the plurality of groups of first iteration strain-stress information; in the iteration rounds other than the first iteration round, the plurality of groups of preset first strain-stress information and the third strain-stress information obtained from the last iteration round are determined as the plurality of groups of first iteration strain-stress information.

[0118] Step S1322: For each of the directions, xyz the plurality of groups of first iteration strain-stress information is updated to the model information of the first battery cell model, and the plurality of groups of first deformation-force information is obtained by running the first battery cell model. Here, the first deformation-force information refers to the relationship between the deformation amount exhibited by the first battery cell model and the applied external force under a specific strain condition.

[0119] In some embodiments, the model information of the first battery cell model includes a battery cell extrusion simulation analysis module, in the first iteration, the plurality of groups of first iteration strain-stress information includes p a group of first strain-stress information, the battery cell extrusion simulation analysis module is copied p times, and the strain-stress information in p times of the battery cell extrusion simulation analysis modules is modified in turn to any one of the plurality of groups of first iteration strain-stress information. After the modification is completed, the first battery cell model is controlled to run, so that p the plurality of groups of first deformation-force information wherein, the data amount in each group of deformation-force information.

[0120] In some embodiments, in the iteration rounds other than the first iteration round, the plurality of groups of first iteration strain-stress information includes p a group of first strain-stress information and the third strain-stress information, the battery cell extrusion simulation analysis module is copied p+1 times, and the strain-stress information in p+1The 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.

[0121] 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.

[0122] 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.

[0123] Step S1323: For xyz For 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. 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.

[0124] 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.

[0125] 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.

[0126] 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; 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.

[0127] 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.

[0128] 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.

[0129] Here, the target strain-stress information is updated to the strain-stress information section in the cell extrusion simulation analysis module.

[0130] 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.

[0131] Understandably, by xyzThe target strain-stress information corresponding to each direction is updated to the model information of the first battery cell model, which can make the target battery cell model better match the experimental data, and realize the optimization and correction of the target battery cell model, so that the target battery cell model can more accurately reflect the mechanical response of the battery cell under various load conditions.

[0132] In the embodiments of the present application, for xyz In each iteration round, a plurality of sets of first iteration strain-stress information are generated for each direction, and are applied to the first battery cell model, and the first deformation-force information corresponding to each direction is obtained by simulation of the first battery cell model. When the set termination condition is met, by comparing the differences between the simulation results of the first battery cell model in all iteration rounds and the experimental data, the target strain-stress information with the highest fitting degree with the experimental data is selected as the target parameter. And the xyz The target strain-stress information corresponding to each direction is updated to the first battery cell model to form the final target battery cell model. In this way, on the one hand, the automatic optimization of parameters can be realized, and the time cost of trial and error by human is reduced; on the other hand, the optimal solution is gradually approached through iteration, and the accuracy and stability of the target battery cell model are improved.

[0133] In some embodiments, the above step S1323 can further include steps S200 and S201: Step S200: determining 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; Here, the first approximation model is a type of simplified mathematical model used to predict material behavior. The structure of the first approximation model can include different types such as linear regression, polynomial fitting, neural network, etc., each of which accepts a set of inputs and outputs corresponding prediction results. In the present 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.

[0134] In some embodiments, the plurality of first approximation models can refer to at least two first approximation models, such as 2 first approximation models, 3 first approximation models, or 6 first approximation models.

[0135] In some embodiments, the plurality of sets of first iteration strain-stress information are input into each first approximation model, and through each first approximation model, a plurality of sets of second deformation-force information corresponding to the plurality of sets of first iteration strain-stress information can be obtained; based on the plurality of sets of second deformation-force information obtained by all first approximation models and the plurality of sets of first deformation-force information, a first target approximation model is determined; and based on the first target approximation model, the third strain-stress information is determined.

[0136] 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.

[0137] In some embodiments, a first range corresponding to the next iteration round is determined; multiple first stress information corresponding to the next iteration round is determined based on the first range; and a single set of first strain-stress information is determined based on the multiple first stress information corresponding to the next iteration round and the multiple first strain information.

[0138] In the embodiments of the present application, the multiple sets of first iteration strain-stress information of the current iteration are predicted by introducing multiple first approximation models, and the third strain-stress information is determined based on the multiple sets of second deformation-force information obtained by prediction and the multiple sets of first deformation-force information, and is applied to the next iteration round. Through this method, the optimization process can be accelerated, unnecessary calculation amount can be reduced, and the calculation efficiency of the target strain-stress information can be improved.

[0139] In some embodiments, the above step S200 can further include steps S2001 to S2004: Step S2001: input the multiple sets of first iteration strain-stress information into the preset multiple first approximation models respectively, to determine the multiple sets of second deformation-force information corresponding to the multiple first approximation models respectively; In some embodiments, the multiple sets of first iteration strain-stress information are taken as the input of each first approximation model, and the multiple sets of second deformation-force information are obtained by running the multiple sets of first iteration strain-stress information through each first approximation model. .

[0140] In some embodiments, a set of first iteration strain-stress information corresponds to a set of second deformation-force information. As described above, a set of first iteration strain-stress information includes multiple third data pairs, and multiple fourth data pairs can be obtained through the multiple third data pairs. Each fourth data pair is formed by a single deformation information and a single force information. That is, a set of second deformation-force information includes multiple fourth data pairs.

[0141] Step S2002: determine a first target approximation model from the multiple first approximation models 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; and the mean square error value between the multiple sets of second deformation-force information corresponding to the first target approximation model and the multiple sets of first deformation-force information is the minimum. Here, the first target approximation model is an optimal model selected from the plurality of first approximation models. The selection criterion of the first target approximation model is usually determined according to the minimization of the mean square error value between the prediction result of the output of the first approximation model and the simulation result of the first cell model.

[0142] In some embodiments, for each first approximation model, the second mean square error value between the corresponding second deformation-force information and the first deformation-force information is obtained for each third data pair. and the first deformation-force information The sum of the second mean square error values corresponding to all first approximation models is determined. Based on the sum of the second mean square error values corresponding to all first approximation models, the first approximation model corresponding to the minimum sum of the second mean square error values is determined as the first target approximation model.

[0143] Step S2003: iteratively calculating a plurality of sets of second iteration strain-stress information as input of the first target approximation model, obtaining a plurality of 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 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 and a plurality of second stress information determined based on the second range; Here, the second iteration termination condition can be to stop the iteration process when a certain preset standard is reached.

[0144] In this application, the second iteration termination condition can be that the number of iterations reaches a preset iteration number value, or the mean square error value between the third deformation-force information predicted by the first target approximation model and the fourth deformation-force information is less than a preset threshold value.

[0145] In some embodiments, the second range corresponding to the next iteration round is determined, the plurality of second stress information corresponding to the next iteration round is determined based on the second range corresponding to the next round, and a single set of second strain-stress information is determined based on the plurality of second stress information corresponding to the next iteration round and the plurality of first strain information. The second range corresponding to the next round can be determined based on the second scaling factor, or can be directly set by the user.

[0146] In this application, the second scaling factor can be the same as or different from the first scaling factor, and the second range can be less than or equal to the first range.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] In some embodiments, the target parameter includes target strain rate-scaling factor information; step S132 above may include steps S1326 to S1330: 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. In some embodiments, the single set of first strain rate-scaling coefficient information includes a plurality of first strain rate information and a plurality of first scaling coefficient information, the plurality of strain rate information and the plurality of scaling coefficient information correspond to each other one by one, and a single strain rate information and a single scaling coefficient information can form a fifth data pair, that is, the single set of first strain rate-scaling coefficient information includes a plurality of fifth data pairs.

[0151] In some embodiments, the plurality of first strain rate information preset by the user can be equidistant or non-equidistant first strain information, for example, the plurality of first strain rate information can be .

[0152] In some embodiments, the same number of first scaling coefficient information as the plurality of first strain rate information is selected from the third range. The plurality of first scaling coefficient information should satisfy the second target selection condition, and the second target selection condition can be It should be noted that the third range of each iteration round is different, and the third range gradually decreases with the increase of the iteration round. For example, in the first iteration round, the third range can be , in the second iteration round, the third range can be , wherein f 3 can be the third scaling factor of each iteration round set by the user.

[0153] In some embodiments, the plurality of sets of first strain rate-scaling coefficient information can refer to q a plurality of sets of first strain-stress information, wherein .

[0154] In some embodiments, in the first iteration round, the plurality of sets of first strain rate-scaling coefficient information preset is determined as a plurality of sets of first iteration strain rate-scaling coefficient information; in other iteration rounds except the first iteration round, the plurality of sets of first strain rate-scaling coefficient information preset and the third strain rate-scaling coefficient information obtained from the last iteration round are determined as the plurality of sets of first iteration strain rate-scaling coefficient information.

[0155] Step S1327: for xyz each direction of the direction, the plurality of sets of first iteration strain rate-scaling coefficient information is updated to the model information of the first battery cell model, and through the first battery cell model, a plurality of fifth deformation-force information corresponding to the plurality of first type extrusion rates respectively is obtained; In some embodiments, the model information of the first battery cell model includes a battery cell extrusion simulation analysis module, and in the first iteration, the plurality of sets of first iteration strain rate-scaling coefficient information includes qThe 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.

[0156] For example, multiple first-type extrusion rates can be V 2 and V 3, V The fifth deformation-force information corresponding to 2 can be , V The fifth deformation-force information corresponding to 3 can be .

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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. 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.

[0162] 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.

[0163] 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.

[0164] Step S1329: For xyzFor each of the directions, the target strain rate-scaling factor information is determined from the plurality of sets of the fifth deformation-force information corresponding to the plurality of first type extrusion rates based on all the iteration rounds, and the plurality of sets of the first iteration strain rate-scaling factor information corresponding to all the iteration rounds respectively; the sum of the mean square errors between the plurality of sets of the fifth deformation-force information corresponding to the plurality of first type extrusion rates under the target strain rate-scaling factor information and the plurality of sixth deformation-force information under the plurality of first type extrusion rates is the minimum; the plurality of sixth deformation-force information is obtained by performing the extrusion experiment on the battery cell through the plurality of first type extrusion rates. In some embodiments, the plurality of sixth deformation-force information under the plurality of first type extrusion rates can refer to one sixth deformation-force information corresponding to each type of extrusion rate, so that the plurality of first type extrusion rates correspond to the plurality of sixth deformation-force information.

[0165] In some embodiments, after stopping the iteration, the plurality of sets of the fifth deformation-force information corresponding to the plurality of first type extrusion rates obtained by each iteration round is obtained; the sum of the plurality of third mean square error values between the fifth deformation-force information corresponding to each set of the plurality of first type extrusion rates under each iteration round and the plurality of sixth deformation-force information under the plurality of first type extrusion rates is calculated respectively to obtain the first sum of mean square values to determine the fitting degree between the simulation results of the first battery cell model and the extrusion experiment; the first target sum of mean square values is determined based on the plurality of sets of the fifth deformation-force information corresponding to the plurality of first type extrusion rates; the first target mean square value is the minimum value in the plurality of first sum of mean square values; the second target sum of mean square values is determined based on the plurality of first target sum of mean square values corresponding to all the iteration rounds; the second target sum of mean square values is the minimum value in the plurality of first target sum of mean square values. It can be understood that the first iteration strain rate-scaling factor corresponding to the second target sum of mean square values is the target strain rate-scaling factor information.

[0166] In some embodiments, the sixth deformation-force information corresponding to the plurality of first type extrusion rates can be expressed as and The sixth deformation-force information corresponding to the plurality of first type extrusion rates is measured by performing the extrusion experiment on the battery cell through the plurality of first type extrusion rates, wherein the second type extrusion rate is used to realize the dynamic extrusion of the battery cell.

[0167] For example, the first sub mean square error value between and is obtained, and the second sub mean square error value between and is obtained, and the sum of the first sub mean square error value and the second sub mean square error value is the first sum of mean square values.

[0168] Step S1330: obtaining xyzThe target strain rate-scaling factor information corresponding to each direction is updated into the model information of the first battery cell model to obtain a target battery cell model.

[0169] Here, the target strain rate-scaling factor information corresponding to each direction is updated into the strain rate-scaling factor information in the battery cell extrusion simulation analysis module. xyz

[0170] It can be understood that, by updating the target strain rate-scaling factor information corresponding to each direction into the model information of the first battery cell model, the target battery cell model can better match the experimental data, and the optimization and correction of the target battery cell model are realized, so that the target battery cell model can more accurately reflect the mechanical response of the battery cell under various load conditions. xyz

[0171] In the embodiments of the present application, in each iteration round, a plurality of sets of first iteration target strain rate-scaling factor information are generated and applied to the first battery cell model, and a plurality of fifth deformation-force information corresponding to the first extrusion rates of the first category are obtained through the simulation of the first battery cell model. When the set termination condition is met, by comparing the differences between the simulation results of the first battery cell model of all iteration rounds and the experimental data, the target strain rate-scaling factor information with the highest fitting degree with the experimental data is selected as the target parameter. And the target strain rate-scaling factor information is updated into the first battery cell model to form a final target battery cell model. Figure 2

[0172] In some embodiments, the above step S1328 includes steps S202 and S203: Step S202: determining third strain rate-scaling factor information based on the plurality of sets of fifth deformation-force information corresponding to the plurality of first extrusion rates, the plurality of sets of first iteration strain rate-scaling factor information, and the plurality of second approximate models. Here, the second approximate model is a type of simplified mathematical model used to predict material behavior. The structure of the second approximate model can include linear regression, polynomial fitting, neural network, etc. Each second approximate model accepts a set of inputs and outputs corresponding prediction results. In the present application, the input of the second approximate model is the first iteration strain rate-scaling factor information, and the output of the second approximate model is the plurality of sets of seventh deformation-force information corresponding to the plurality of first extrusion rates.

[0173] ​​​In some embodiments, the plurality of second approximate models can refer to at least two second approximate models, for example, 2 second approximate models, 3 second approximate models, 6 second approximate models.

[0174] In some embodiments, the plurality of first iteration strain rate-scaling factor information is input into each second approximate model, and through each second approximate model, a plurality of groups of seventh deformation-force information respectively corresponding to a plurality of first extrusion rates can be obtained; based on the plurality of groups of seventh deformation-force information respectively corresponding to the plurality of first extrusion rates obtained by all second approximate models and the plurality of groups of fifth deformation-force information respectively corresponding to the plurality of first extrusion rates, a first target approximate model is determined; and based on the first target approximate model, third strain rate-scaling factor information is determined.

[0175] Step S203: The plurality of groups 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 are determined as the plurality of groups of first iteration strain rate-scaling factor information corresponding to the next iteration round.

[0176] In some embodiments, a third range corresponding to the next iteration round is determined; a plurality of first scaling factor information is determined based on the third range corresponding to the next iteration round; and a group of first strain rate-scaling factor information is determined based on the plurality of first scaling factor information corresponding to the next iteration round and the plurality of first strain rate information. The first range corresponding to the next round can be determined based on the third scaling factor or directly set by a user.

[0177] In the embodiments of the present application, the plurality of groups of first iteration strain rate-scaling factor information of the current iteration is predicted by introducing a plurality of second approximate models, and the third strain rate-scaling factor information obtained by the prediction is applied to the next iteration round. Through this method, the optimization process can be accelerated, unnecessary calculation amount can be reduced, and the calculation efficiency of the target strain-stress information can be improved.

[0178] In some embodiments, the above step S202 can further include steps S2005 to S2008: Step S2005: inputting the plurality of groups of first iteration strain rate-scaling factor information into a plurality of preset second approximate models to determine a plurality of groups of seventh deformation-force information respectively corresponding to a plurality of first extrusion rates; In some embodiments, the plurality of groups of first iteration strain rate-scaling factor information is input into each second approximate model, and through each second approximate model based on the plurality of first extrusion rates, the plurality of groups of first iteration strain rate-scaling factor information is run to obtain a plurality of groups of seventh deformation-force information respectively corresponding to a plurality of first extrusion rates.

[0179] For example, the plurality of first extrusion rates can be V 2 and V 3, V 2 the corresponding seventh deformation-force information can be , V 3 the corresponding seventh deformation-force information can be .

[0180] In some embodiments, a set of first iteration strain rate-scaling coefficient information operates under a plurality of first extrusion rates, corresponding to a set of seventh deformation-force information under the plurality of first extrusion rates. As described above, the set of first iteration strain rate-scaling coefficient information includes a plurality of sixth data pairs, and by operating the plurality of sixth data pairs under each first extrusion rate, a plurality of seventh data pairs corresponding to each first extrusion rate can be obtained, and each seventh data pair is formed by a single deformation information and a single force information, that is, the set of seventh deformation-force information under each extrusion rate includes a plurality of seventh data pairs.

[0181] Step S2006: Based on the plurality of sets 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 sets of fifth deformation-force information corresponding to the plurality of first extrusion rates respectively, a second target approximation model is determined from the plurality of second approximation models; the sum of the mean square error values between the plurality of sets of seventh deformation-force information corresponding to the plurality of first extrusion rates respectively under the second target approximation model and the plurality of sets of fifth deformation-force information corresponding to the plurality of first extrusion rates respectively is the minimum; Here, the second target approximation model is an optimal model selected from the plurality of second approximation models. The selection criterion of the second target approximation model is usually to minimize the sum of the mean square error values between the prediction results of the output of the second approximation model and the simulation results of the first battery cell model.

[0182] In some embodiments, for each second approximation model, a second sub-mean square sum is obtained between the fifth deformation-force information and the seventh deformation-force information under the plurality of first extrusion rates corresponding to the same fifth data pair; based on the second sub-mean square sums corresponding to all fifth data pairs respectively, a second mean square sum is determined. Based on the second mean square sums corresponding to all first approximation models respectively, the second approximation model with the minimum second mean square sum is determined as the second target approximation model.

[0183] For example, the second mean square sum can refer to obtaining the third sub-mean square error value between and the fourth sub-mean square error value between , and the sum of the third sub-mean square error value and the fourth sub-mean square error value is the second mean square sum.

[0184] Step S2007: iteratively calculating a plurality of groups of second iteration strain rate-scaling factor information as input of the second target approximation model, obtaining 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 factor information includes a plurality of groups of second strain rate-scaling factor information, the second strain rate-scaling factor information includes a plurality of first strain rate information preset, and a plurality of second scaling factor information determined based on the fourth range; Here, the fourth iteration termination condition can mean stopping the iteration process when a certain preset standard is reached.

[0185] In the present application, the fourth iteration termination condition can be that the number of iterations reaches a preset iteration number value, or the sum of the mean square error values between the plurality of eighth deformation-force information under the plurality of first extrusion rates predicted by the second target approximation model is less than a preset threshold.

[0186] In some embodiments, a fourth range corresponding to the next iteration round is determined; based on the fourth range corresponding to the next round, a plurality of second scaling factor information corresponding to the next iteration round is determined; based on the plurality of second scaling factor information corresponding to the next iteration round and the plurality of first strain information, a group of second strain rate-scaling factor information is determined. Wherein the fourth range corresponding to the next round can be determined based on the fourth scaling factor, or can be directly set by the user.

[0187] In the present application, the fourth scaling factor can be the same as or different from the third scaling factor, and the fourth range can be less than or equal to the third range.

[0188] Step S2008: based on the plurality of groups of eighth deformation-force information corresponding to the plurality of first extrusion rates respectively of all iteration rounds, and the plurality of sixth deformation-force information under the plurality of first extrusion rates, determining third strain rate-scaling factor information from the plurality of groups of second iteration strain rate-scaling factor information corresponding to all iteration rounds respectively; the sum of the mean square error values between the plurality of eighth deformation-force information under the plurality of first extrusion rates corresponding to the third strain rate-scaling factor information and the plurality of sixth deformation-force information under the plurality of first extrusion rates is the minimum.

[0189] In some embodiments, after stopping the iteration, a plurality of groups of eighth deformation-force information corresponding to the plurality of first extrusion rates obtained in each iteration round are obtained; a plurality of third mean square error sums between the eighth deformation-force information corresponding to each of the plurality of first extrusion rates in each iteration round and the sixth deformation-force information under the plurality of first extrusion rates are calculated respectively to obtain a third mean square sum; a third target mean square sum is determined based on the plurality of third mean square sums corresponding to the plurality of groups of eighth deformation-force information under the plurality of first extrusion rates respectively; the third target mean square error is the minimum value in the plurality of third mean square error sums; a fourth target mean square sum is determined based on the plurality of third target mean square sums corresponding to all iteration rounds; and the fourth target mean square sum is the minimum value in the plurality of third target mean square sums. It can be understood that the second iteration strain rate-scaling factor information corresponding to the fourth target mean square sum is the third strain rate-scaling factor information.

[0190] For example, a fifth sub-mean square error value between and is obtained, and a sixth sub-mean square error value between and is obtained, and the sum of the fifth sub-mean square error value and the sixth sub-mean square error value is the third mean square sum.

[0191] In the embodiments of the present application, first, the first iteration strain rate-scaling factor information of the current iteration round is input into a plurality of second approximation models to generate a plurality of seventh deformation-force information under a plurality of first extrusion rates; then, by comparing the differences between the seventh deformation-force information under the plurality of first extrusion rates output by each second approximation model and the actual simulation results (the fifth deformation-force information under the plurality of first 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, and the optimal solution is gradually approached through this iterative method, thereby improving the accuracy and efficiency of the parameter optimization of the strain rate-scaling factor information.

[0192] In some embodiments, the grid information includes node information and element information; the size information includes cell shell information, expected size information of the shell grid, thickness information corresponding to each of the plurality of faces of the shell, expected size information of the jelly roll grid, and jelly roll information; and the step S100 can include steps S101 to S103: Step S101: determining first node information of each node in the plurality of faces and first element information of each element 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; Here, the cell shell information refers to basic geometric parameters of the cell, and in some embodiments, the cell shell information can include but is not limited to a cell shell length (Lx), a cell shell thickness (Ly), and a cell shell height (Lz). y The expected size information of the first mesh model is a preset mesh size according to design requirements, which is used to control the mesh division accuracy of the cell shell. The thickness information corresponding to the plurality of faces respectively describes the material thickness of the shell in different directions. For example, in the case where the shell includes six faces, the thickness information corresponding to the plurality of faces can include a shell front face thickness, a shell back face thickness, a shell left side face thickness, a shell right side face thickness, a shell top face thickness, and a shell bottom face thickness. x z In some embodiments, the first node information includes first node number information and first node position information of the node in a three-dimensional space, and the first unit information describes first node number information and first sub-number information of a unit composed of a plurality of nodes.

[0193] For example, in the case where the shell of the cell is modeled by a quadrilateral unit, the first node number information set constituting the unit can include first node number information of an N1 node, first node number information of an N2 node, first node number information of an N3 node, and first node number information of an N4 node.

[0194]

[0195] Step S102: determining second node information of each node in the roll core and second unit information of each unit in the roll core based on the expected size information of the roll core mesh, the roll core information, and the first node information of each node in the plurality of faces; Here, the roll core information refers to basic geometric parameters of the roll core, and in some embodiments, the roll core information can include but is not limited to a roll core length (Lx), a roll core thickness (Ly), and a roll core height (Lz). The expected size information of the second mesh model is a preset mesh size according to design requirements, which is used to control the mesh division accuracy of the cell roll core. y x z In some embodiments, the second node information includes second node number information and second node position information of the node in a three-dimensional space, and the second unit information describes second node number information and second sub-number information of a unit composed of a plurality of nodes.

[0196]

[0197] ​​​​​For example, in the case of modeling the winding core of the battery cell by using the hexahedral unit, the second node number information set of the unit can include the second node number information of the N1 node, the second node number information of the N2 node, the second node number information of the N3 node, the second node number information of the N4 node, the second node number information of the N5 node, the second node number information of the N6 node, the second node number information of the N7 node, and the second node number information of the N8 node.

[0198] Step S103: determining the grid information of the grid model based on the first node information corresponding to all nodes in the plurality of faces, the first unit information corresponding to all units in the plurality of faces, the second node information corresponding to all nodes in the winding core, and the second unit information corresponding to all units in the winding core.

[0199] In some embodiments, the grid information of the grid model is determined by splicing the first node information corresponding to all nodes in the plurality of faces, the first unit information corresponding to all units in the plurality of faces, the second node information corresponding to all nodes in the winding core, and the second unit information corresponding to all units in the winding core in a target order. The target order can be “first node number information-first node position information-first unit information-second node number information-second node position information-second unit information”.

[0200] For example, the target order can be “first node number-first node position information in the first node position information-first unit information-second node number-second node position information in the second node position information-second unit information”. x coordinate value-first node position information in the first node position information-first unit information-second node number-second node position information in the second node position information-second unit information”. y coordinate value-first node position information in the first node position information-first unit information-second node number-second node position information in the second node position information-second unit information”. z coordinate value-quadrilateral first sub-number information-number of the battery cell shell part to which the quadrilateral belongs-first node number information of the N1 node-first node number information of the N2 node-first node number information of the N3 node-first node number information of the N4 node-battery cell shell thickness-hexahedral second sub-number information-number of the battery cell internal winding core part to which the hexahedral belongs-second node number information of the N1 node-second node number information of the N2 node-second node number information of the N3 node-second node number information of the N4 node-second node number information of the N5 node-second node number information of the N6 node-second node number information of the N7 node-second node number information of the N8 node”. It can be understood that the battery cell includes a battery cell shell and a battery cell winding core, and the number of the battery cell shell part to which the quadrilateral belongs can refer to the first sub-number information, and the number of the battery cell internal winding core part to which the hexahedral belongs can refer to the second sub-number information.

[0201] 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.

[0202] 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: 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; 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.

[0203] Below, with Figure 3 The calculation process for each node on each surface of the battery cell casing shown can be explained, including steps S3121 to S3126: Step S3121: Calculate the mesh node information on the front of the cell casing; 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.

[0204] In some implementations, such as NumC As shown, when calculating the node information of the mesh on the front of the battery cell casing, along... xThe 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.

[0205] The node number in row Z and column X of the grid on the front of the battery cell casing is: (1); 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.

[0206] dx x For the cell casing mesh x The ratio of the directional dimension to the desired size of the cell housing grid, rounded down, is shown in the following formula (2): (2); 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.

[0207] NumC 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): (3); 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.

[0208] The node in row numZ and column numX corresponds to x The coordinates are: (4); in, S Cx This indicates that the quadrilateral unit on the battery cell casing is in x The actual dimensions of the direction.

[0209] S Cx The determination method is shown in the following formula (5): (5); The node in row numZ and column numX corresponds to y The coordinates are: y 1 The node in row numZ and column numX corresponds to z The coordinates are: (6); in, S Cz This indicates that the quadrilateral unit on the battery cell casing is in z The actual dimensions of the direction.

[0210] S Cz The determination method is shown in the following formula (7): (7); in, NumC z Indicates the cell casing mesh in z The number of quadrilateral units distributed in a specific direction.

[0211] dz 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): (8); 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.

[0212] Figure 4 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): (9); 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.

[0213] Step S3122: Calculate the mesh node information of the bottom surface of the cell casing; 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.

[0214] 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 NumC 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.

[0215] The node number in row numY and column numX of the grid on the bottom surface (1-2) of the battery cell casing is: (10); 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.

[0216] The node in row numY and column numX corresponds to x The coordinates are: (11); The node in row numZ and column numX corresponds to y The coordinates are: (12); in, S Cy This indicates the actual size of the quadrilateral unit on the battery cell casing in the y-direction.

[0217] S CyThe determination method is shown in the following formula (13): (13); in, NumC y Indicates the cell casing mesh in y The number of quadrilateral units distributed in a specific direction.

[0218] dy 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): (14); 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.

[0219] Figure 5 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): (15); in, L Indicates 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.

[0220] The z-coordinate of the node in row numZ and column numX is: z 1 Step S3123: Calculate the mesh node information on the left side of the cell casing; like Figure 5 The diagram shows a grid schematic 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.

[0221] 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 6 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.

[0222] The node number in row numZ and column numY of the grid on the left side of the battery cell casing is: (16); 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.

[0223] The node in row numZ and column numY corresponds to x The coordinates are: x 1 The node in row numZ and column numY corresponds to y The coordinates are: (17); The z-coordinate of the node in row numZ and column numY is: (18); Step S3124: Calculate the mesh node information on the back of the cell casing; 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.

[0224] 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 7 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.

[0225] The node number in row Z and column X of the grid on the back of the battery cell casing is: (19); 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).

[0226] The node in row numZ and column numX corresponds to x The coordinates are: (20); The node in row numZ and column numX corresponds to y The coordinates are: (twenty one); The node in row numZ and column numX corresponds to z The coordinates are: (twenty two); Step S3125: Calculate the mesh node information of the top surface of the cell casing; like Figure 7As shown, a grid diagram of the top surface of the battery cell shell is shown, wherein the largest unit of the grid of the top surface of the battery cell shell is labeled as 1-5-10, the rear boundary of the top surface of the battery cell shell is labeled as 1-5-3, the intersection of the two second parallel lines adjacent to and parallel with the rear boundary and the left boundary is labeled as 1-5-6, the right boundary of the top surface of the battery cell shell is labeled as 1-5-4, the second last node on the right boundary is labeled as 1-5-7, the second node on the right boundary is labeled as 1-5-8, the front boundary of the top surface of the battery cell shell is labeled as 1-5-1, the first non-common node of the top surface of the battery cell shell is labeled as 1-5-5, the left boundary of the top surface of the battery cell shell is labeled as 1-5-2, and the first unit on the top surface of the battery cell shell is labeled as 1-5-9.

[0227] In some embodiments, as shown in FIG. 1-5, when calculating the node information of the grid of the top surface of the battery cell shell, the coordinate system is constructed from left to right along the direction of Figure 7 x In some embodiments, as shown in FIG. 1-5, when calculating the node information of the grid of the top surface of the battery cell shell, the coordinate system is constructed from left to right along the direction of y Figure 8 As can be seen, the front boundary (1-5-1) of the top surface (1-5) of the battery cell shell is common with the upper boundary (1-1-3) of the front surface (1-1) of the battery cell shell, and the nodes are shared; the left boundary (1-5-2) of the top surface (1-5) of the battery cell shell is common with the upper boundary (1-3-2) of the left side surface (1-3) of the battery cell shell, and the nodes are shared; and the rear boundary (1-5-3) of the top surface (1-5) of the battery cell shell is common with the upper boundary (1-4-3) of the rear surface (1-4) of the battery cell shell, and the nodes are shared. Taking the direction of x as the row and the direction of y as the column, the top surface grid of the battery cell shell has i rows and j-1 columns of nodes in addition to the common nodes.

[0228] The number of the node of the grid of the top surface of the battery cell shell in the numXth row and the numYth column is: (23). Wherein, N 4 represents the number of the largest node (1-4-7) of the grid of the rear surface of the battery cell shell.

[0229] The coordinates corresponding to the node of the grid of the top surface of the battery cell shell in the numXth row and the numYth column are: x (24). The coordinates corresponding to the node of the grid of the top surface of the battery cell shell in the numXth row and the numYth column are: y (25). The coordinates corresponding to the node of the grid of the top surface of the battery cell shell in the numXth row and the numYth column are: z ​​​​Coordinates are: (26); Step S3126: Calculate the grid node information of the right side surface of the battery cell shell.

[0230] As shown in Figure 8 , a grid schematic diagram of the right side surface of the battery cell shell is shown, wherein the identification of the largest unit of the grid of the right side surface of the battery cell shell is 1-6-10, the identification of the last non-public node of the right side surface of the battery cell shell is 1-6-7, the identification of the rear boundary of the right side surface of the battery cell shell is 1-6-3, the identification of the intersection point between the parallel line adjacent and parallel to the lower boundary and the parallel line adjacent and parallel to the rear boundary is 1-6-8, the identification of the lower boundary of the right side surface of the battery cell shell is 1-6-4, the identification of the first non-public node on the first parallel line adjacent and parallel to the front boundary of the right side surface of the battery cell shell is 1-6-5, the identification of the first unit on the right side surface of the battery cell shell is 1-6-9, the identification of the front boundary of the right side surface of the battery cell shell is 1-6-1, the identification of the last non-public node on the first parallel line adjacent and parallel to the front boundary of the right side surface of the battery cell shell is 1-6-6, and the identification of the upper boundary of the right side surface of the battery cell shell is 1-6-2.

[0231] In some embodiments, as shown in Figure 8 , when calculating the grid node information of the right side surface of the battery cell shell, the coordinate system is constructed from bottom to top along the z direction, and from front to back along the y direction, as Figure 3 can be seen, the front boundary (1-6-1) of the right side surface (1-6) of the battery cell shell is common with the right boundary (1-1-4) of the front surface (1-1) of the battery cell shell, and the nodes are shared; the lower boundary (1-6-4) of the right side surface (1-6) of the battery cell shell is common with the right boundary (1-2-4) of the bottom surface (1-2) of the battery cell shell, and the nodes are shared; the rear boundary (1-6-3) of the right side surface (1-6) of the battery cell shell is common with the right boundary (1-4-4) of the back surface (1-4) of the battery cell shell, and the nodes are shared; the upper boundary (1-6-2) of the right side surface (1-6) of the battery cell shell is common with the right boundary (1-5-4) of the top surface (1-5) of the battery cell shell, and the nodes are shared. With y the direction as row, z the direction as column, then the right side surface grid of the battery cell shell has k-1 rows, j-1 columns of nodes in addition to the public nodes.

[0232] The number of the node on the grid of the right side surface of the battery cell shell in the numZth row and the numYth column is: (27); N5 represents the number of the 2nd last node (1-5-7) on the right boundary of the top surface of the battery cell shell.

[0233] The coordinates of the node corresponding to the numZth row and numYth column of the battery cell shell are: x (28); The coordinates of the node corresponding to the numZth row and numYth column of the battery cell shell are: y (29); The coordinates of the node corresponding to the numXth row and numYth column of the battery cell shell are: z (30); Step S1012: based on the battery cell shell information, the expected size information of the shell grid, the thickness information corresponding to each of the plurality of surfaces, and the first node number information corresponding to all nodes in each of the plurality of surfaces, determine the first cell number information of each cell in the plurality of surfaces; the first cell number information includes first sub-number information for identifying the cell, and first node number information corresponding to the nodes constituting the cell.

[0234] In the following, in the case where the shell includes 6 surfaces, the calculation process of each cell in each surface is described, which can include steps S3131 to S3136.

[0235] Step S3131: calculation of grid cell information of the front surface of the battery cell shell. In some embodiments, as shown in the following, when calculating the grid cell information of the front surface of the battery cell shell, the coordinate system is constructed from left to right along the x direction, and from bottom to top along the y direction. Taking the x direction as the row and the y direction as the column, the front surface grid cell of the battery cell shell has numZ rows and numX columns. It should be noted that this is a coordinate system description in the unit dimension, and the above step S3121 is a coordinate system description in the node dimension, and the number of rows and columns corresponding to the node dimension is one more than the number of rows and columns corresponding to the unit dimension. Figure 4 x z x z k i It should be noted that this is a coordinate system description in the unit dimension, and the above step S3121 is a coordinate system description in the node dimension, and the number of rows and columns corresponding to the node dimension is one more than the number of rows and columns corresponding to the unit dimension.

[0236] The number of the numZth row and numXth column cell on the front surface of the battery cell shell is: (31); wherein, E 0 represents the number of the 1st cell (1-1-9) of the battery cell.

[0237] ​​​​​​​​​Therefore, the numbers of the 4 nodes constituting the quadrilateral unit of the numZth row and the numXth column are wherein, (32); (33); (34); (35); Step S3132: Calculate the grid unit information of the bottom surface of the battery cell shell. In some embodiments, as shown in FIG. 13, when calculating the grid unit information of the bottom surface of the battery cell shell, a coordinate system is constructed from left to right along the x direction and from front to back along the y direction, with the x direction as the row and the y direction as the column, and there are numY rows and numX columns of nodes. Figure 5 x y x y j-1 i

[0238] The number of the unit of the numYth row and the numXth column on the grid of the bottom surface of the battery cell shell is: (36); wherein, E 1 represents the number of the largest unit (1-1-10) on the grid of the front surface of the battery cell shell.

[0239] Therefore, the numbers of the 4 nodes constituting the quadrilateral unit of the numYth row and the numXth column are wherein, When numY=1, N1 is the numXth node among the common nodes of the front surface (1-1) and the bottom surface (1-2) of the battery cell shell; N2 is the numX+1th node among the common nodes of the front surface (1-1) and the bottom surface (1-2) of the battery cell shell; N4 is the number of the 1st non-common node (1-2-5) of the bottom surface (1-2) of the battery cell shell plus numX-1, .

[0240] When numY≠1, the numbers of the 4 nodes of the quadrilateral unit are See the following formula: (37); wherein, N7 represents the number of the largest node (1-2-5) of the grid of the bottom surface (1-2) of the battery cell shell.

[0241] (38); ​​​​​​​(39); (40); Step S3133: Calculate the grid unit information of the left side of the battery cell shell; In some embodiments, as shown in FIG. 13, when calculating the grid unit information of the left side of the battery cell shell, a coordinate system is constructed from bottom to top along the Z direction and from front to back along the Y direction, with the Z direction as the row and the Y direction as the column, a total of numZ rows and numY columns of units. Figure 6 z y y z k-1 j-1

[0242] The number of the unit in the numZth row and the numYth column on the grid of the left side of the battery cell shell is: (41); E 2 represents the number of the largest unit (1-2-10) of the grid of the bottom surface of the battery cell shell.

[0243] Therefore, the numbers of the 4 nodes constituting the quadrilateral unit in the numZth row and the numYth column are N1, N2, N3, and N4, wherein When numZ=1 and numY=1, N1=N0 and N2 are the number of the 1st non-common node (1-2-5) on the bottom surface of the battery cell shell; N3 is the number of the 1st non-common node (1-3-5) on the left side of the battery cell shell; and N4 is the number of the 2nd node on the left boundary (1-1-2) of the front surface of the battery cell shell (the 1st node is actually the 1st node on the left boundary of the grid of the front surface of the battery cell shell).

[0244] When numZ=1 and numY≠1, N1 is the number of the numYth node on the left boundary (1-2-2) of the bottom surface of the battery cell shell; N2 is the number of the numY+1th node on the left boundary (1-2-2) of the bottom surface of the battery cell shell; and N4 is the number of the 1st non-common node (1-2-5) on the bottom surface of the battery cell shell plus .

[0245] When numZ≠1 and numY=1, N1 is the number of the numZth node on the left boundary (1-1-2) of the front surface of the battery cell shell; N2 is the number of the numZ-1th non-common node on the left side of the battery cell shell; N3=N2+1; and N4 is the number of the numZ+1th node on the left boundary (1-1-2) of the front surface of the battery cell shell.

[0246] When numZ≠1 and numY≠1, the numbers of the 4 nodes of the quadrilateral unit are​​​​​​​​​​ Referring to the following formula: (42); wherein, N 8 represents the number of the 1st non-common node (1-3-5) on the left side of the cell shell.

[0247] (43); (44); (45); Step S3134: Grid cell information calculation of the back surface of the cell shell; In some embodiments, as shown in FIG. 13, when calculating the cell information of the grid on the back surface of the cell shell, the coordinate system is constructed from left to right along the x direction and from bottom to top along the z direction, with the x direction as the row and the z direction as the column, a total of numZ rows and numX columns of cells. Figure 7 x z x z k-1 i-1

[0248] The number of the numZth row and numXth column cell on the back surface of the cell shell is: (46); wherein, E 3 represents the number of the largest grid cell (1-3-10) on the left side of the cell shell.

[0249] Then, the numbers of the 4 nodes constituting the quadrilateral cell of the numZth row and numXth column are N1, N2, N3 and N4, wherein, When numZ=1 and numX=1, N1 is the number of the 1st node (1-2-6) on the back boundary (1-2-3) of the bottom surface of the cell shell; N2 is the number of the 2nd node on the back boundary of the bottom surface of the cell shell; N3 is the number of the 1st non-common node (1-4-5) on the back surface of the cell shell; and N4 is the number of the 2nd node (1-3-8) on the back boundary (1-3-3) of the left side of the cell shell (the 1st node is actually the 1st node on the back boundary of the grid on the bottom surface of the cell shell).

[0250] When numZ=1 and numX≠1, N1 is the number of the numXth node on the back boundary (1-2-3) of the bottom surface of the cell shell; N2 is the number of the numX+1th node on the back boundary of the bottom surface of the cell shell; N4 is the number of the 1st non-common node (1-4-5) on the back surface of the cell shell plus ; and N3=N4+1.​​​​​​​​

[0251] When numZ≠1, numX=1, N1 is the number of the numZth node on the back boundary of the left side of the battery cell shell (1-3-3); N2 is the number of the 1st non-common node (1-4-5) on the back of the battery cell shell plus ; ; .

[0252] When numZ≠1, numX≠1, N1 is the number of the 1st non-common node (1-4-5) on the back of the battery cell shell plus ; ; ; .

[0253] Step S3135: Calculate the grid cell information of the top surface of the battery cell shell. In some embodiments, as shown in FIG. 13, when calculating the grid node cell information of the top surface of the battery cell shell, a coordinate system is constructed from left to right along the Figure 8 direction, and from front to back along the x direction, with the y direction as the row and the x direction as the column, a total of z rows and i-1 columns of cells. j

[0254] The number of the numXth row and numYth column cell of the grid on the top surface of the battery cell shell is: (47) ; Wherein, E 4 represents the number of the maximum cell (1-4-10) of the grid on the back of the battery cell shell.

[0255] Then, the numbers of the 4 nodes that make up the quadrilateral cell of the numXth row and numYth column are , wherein, When numY=1, numX=1, N1 is the number of the 1st node (1-1-6) on the upper boundary of the front surface of the battery cell shell (1-1-3); N2 is the number of the 2nd node (1-3-6) on the upper boundary of the left side of the battery cell shell (1-3-2) (the 1st node is actually the 1st node on the upper boundary of the front surface of the battery cell shell); N3 is the number of the 1st non-common node (1-5-5) on the top surface of the battery cell shell; N4 is the number of the 2nd node on the upper boundary of the front surface of the battery cell shell (1-1-3).

[0256] When numY=NumC y ​, when numY = 1, numX ≠ 1, N1 is the number of the numXth node on the upper boundary of the front face of the battery cell shell (1-1-3); N2 is the number of the numX-1th non-common node on the top face of the battery cell shell (1-5); N3 = N2 + 1; and N4 is the number of the numX+1th node on the upper boundary of the front face of the battery cell shell (1-1-3). .

[0257] When numY = 1, numX ≠ 1, N1 is the number of the numXth node on the upper boundary of the front face of the battery cell shell (1-1-3); N2 is the number of the numX-1th non-common node on the top face of the battery cell shell (1-5); N3 = N2 + 1; and N4 is the number of the numX+1th node on the upper boundary of the front face of the battery cell shell (1-1-3).

[0258] When numY = NumC y , numX ≠ 1, N1 is the number of the numXth node on the upper boundary of the front face of the battery cell shell (1-1-3); N2 is the number of the numX-1th non-common node on the top face of the battery cell shell (1-5); N3 = N2 + 1; and N4 is the number of the numX+1th node on the upper boundary of the front face of the battery cell shell (1-1-3). . .

[0259] When numY ≠ 1, numY ≠ NumC y , numX = 1, N1 is the number of the numY-1th node on the upper boundary of the left side of the battery cell shell (1-3); N2 is the number of the numYth node on the upper boundary of the left side of the battery cell shell (1-3) (the 1st node is actually the 1st node on the upper boundary of the front face of the battery cell shell); and N4 is the number of the 1st non-common node (1-5-5) on the top face of the battery cell shell plus . .

[0260] When numY ≠ 1, numY ≠ NumC y , numX ≠ 1, N1 is the number of the 1st non-common node (1-5-5) on the top face of the battery cell shell plus . . . .

[0261] Step S3136: Calculate the grid cell information of the right side surface of the battery cell shell; In some embodiments, as shown in the calculation of the grid node cell information of the right side surface of the battery cell shell, the coordinate system is constructed from bottom to top along the Figure 9 direction, and from front to back along the z direction, with the y direction as the row and the y direction as the column, a total of z rows and k-2 columns of cells. j-2

[0262] The number of the grid cell of the numZth row and the numYth column of the right side surface of the battery cell shell is: (48); wherein, E 5 represents the number of the largest grid cell (1-5-10) of the top surface of the battery cell shell.

[0263] Therefore, the numbers of the 4 nodes constituting the quadrilateral cell of the numZth row and the numYth column are , wherein, When numY=1 and numZ=1, N1 is the number of the 1st node (1-1-8) on the right boundary (1-1-4) of the front surface of the battery cell shell; N2 is the number of the 2nd node on the right boundary (1-1-4) of the front surface of the battery cell shell; N3 is the number of the 1st 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 battery cell shell; and N4 is the number of the 2nd node (1-2-8) on the right boundary (1-2-4) of the bottom surface of the battery cell shell (the 1st node is actually the 1st node on the right boundary of the front surface of the battery cell shell).

[0264] When numY=NumC y and numZ=1, N1 is the number of the last non-common node (1-6-7) on the right side surface of the battery cell shell minus ; N2 is the number of the 2nd node (1-4-8) on the right boundary (1-4-4) of the back surface of the battery cell shell (the 1st node is actually the last node on the right boundary of the bottom surface of the battery cell shell); N3 is the number of the last node (1-2-7) on the right boundary (1-2-4) of the bottom surface (1-2) of the battery cell shell; and N4 is the number of the 2nd last node on the right boundary (1-2-4) of the bottom surface (1-2) of the battery cell shell.

[0265] When numY=NumC y and 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.

[0266] 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 side (1-1) of the cell casing.

[0267] 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... ; .

[0268] 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... ; .

[0269] When numY=NumC y numZ≠1, numZ≠NumC zAt 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). ; .

[0270] 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.

[0271] When numY≠1, numY≠NumC y numZ≠1, numZ≠NumC z At 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... ; ; ; .

[0272] 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.

[0273] 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: 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; In some implementations, such as NumJ 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.

[0274] 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: (49); 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.

[0275] 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): (50); 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.

[0276] 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): (51); in, h Indicates the internal winding core of the battery cell z Orientation dimension (height of the internal winding of the battery cell).

[0277] 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: (52); wherein, S JRx represents the actual size of the internal winding of the battery cell in the x direction.

[0278] S JRx The determination method of is shown in the following formula (53): (53) ; wherein, NumJ x represents the number of hexahedral units in which the mesh of the internal winding of the battery cell is distributed in the x direction.

[0279] Figure 9 x The ratio of the size of the mesh of the internal winding of the battery cell in the x direction to the expected size of the internal winding of the battery cell is rounded down, as shown in the following formula (54): (54) ; wherein, t represents the size of the internal winding of the battery cell in the x direction (the thickness of the internal winding of the battery cell).

[0280] When it is a left side layer node, the coordinates of the node corresponding to the numX layer, numZ row, and numY column are: y (55) ; wherein, S JRy represents the actual size of the internal winding of the battery cell in the y direction.

[0281] S JRy The determination method of is shown in the following formula (56): (56) ; When it is a left side layer node, the coordinates of the node corresponding to the numX layer, numZ row, and numY column are: z (57) ; wherein, S JRz represents the actual size of the internal winding of the battery cell in the z direction.

[0282] S JRz The determination method of is shown in the following formula (58): (58) ; ​​When being a right side layer (1-7-2) node, the numX layer numZ row numY column node corresponding to the numX layer numZ row numY column node x The coordinates are: (59); When being a right side layer node, the numX layer numZ row numY column node corresponding to the numX layer numZ row numY column node y The coordinates are: (60); When being a right side layer node, the numX layer numZ row numY column node corresponding to the numX layer numZ row numY column node z The coordinates are: (61).

[0283] Step S1022: based on the expected size information of the roll core grid, the roll core information and the first node information, and the second node number information corresponding to all nodes respectively, determine the second unit number information of each unit; the second unit number information includes second sub-number information for identifying the unit, and second node number information corresponding to the nodes constituting the unit respectively.

[0284] In some embodiments, as shown in FIG. 1-7, when calculating the unit information of the grid of the internal roll core of the battery cell, a coordinate system is constructed from bottom to top along the xyz direction, from left to right along the z direction, and from front to back along the x direction, so that the y direction is the row, y the direction is the column, z and the direction is the layer. Then, the internal roll core (1-7) of the battery cell has x rows, p columns, and n layers in each layer. m

[0285] The number of the hexahedral unit of the grid of the internal roll core of the battery cell is: (62); wherein, E 6 represents the number of the maximum unit (1-6-10) of the right side of the battery cell shell.

[0286] Then, the numbers of the 8 nodes constituting the hexahedral unit of the numX layer numZ row numY column are , wherein, (63); wherein, N 10 ​The number of the first node (1-7-3) representing the winding core inside the battery cell.

[0287] (64); (65); (66); (67); (68); (69); (70); In the embodiments of the present application, by defining the second node information of each node in the winding core grid and the second unit information of each unit, the parameterization degree of the winding core grid is improved, and the management of the winding core grid is simplified, so that on the one hand, the subsequent modification and expansion of the winding core grid can be facilitated; on the other hand, through the establishment of the second node information and the second unit information of the winding core grid, the readability and maintainability of the winding core grid are improved.

[0288] In some embodiments, the target extrusion test data includes xyz target time-deformation-force information of each of the directions, and target deformation-force information of each of the directions; xyz The directions include x a direction, y a direction, and z a direction; the extrusion test information includes xyz first time-deformation-force information of each of the directions; the step S110 includes steps S111 to S114: 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, a duplicate data elimination operation is performed on the first time-deformation-force information to obtain second time-deformation-force information; Here, the duplicate data elimination operation refers to deleting data points with the same or similar first deformation information and the same time information in each set of first time-deformation-force information.

[0289] It can be understood that the first time-deformation-force information includes first time information, first deformation information and first force information, so that when a plurality of sets of first time-deformation-force information are stored in a target data table, the data table includes a time column, a deformation information column and a force information column. In this scenario, the repeated data elimination operation on the plurality of sets of first time-deformation-force information can be: checking the time column in the target data table; obtaining a first number corresponding to the non-repeated time information in the time column, and a second number corresponding to all the rows of the time column; when the first number is less than the second number, determining the first time-deformation-force information corresponding to the first number as the second time-deformation-force information. For example, x The plurality of sets of second time-deformation-force information in the direction can be represented as ; y The plurality of sets of second time-deformation-force information in the direction can be represented as ; z The plurality of sets of second time-deformation-force information in the direction can be represented as .

[0290] In some embodiments, a single set of first time-deformation-force information includes a plurality of first time information, a plurality of first deformation information and a plurality of first force information, the plurality of first time information, the plurality of first deformation information and the plurality of first force information correspond one-to-one, and 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 a plurality of ninth data pairs.

[0291] Step S112: for each direction, based on the force information in the plurality of sets of second time-deformation-force information, performing a data screening operation on the plurality of sets 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 the smallest; Here, the data screening operation refers to selecting a set of data with the best stability from the plurality of sets of second time-deformation-force information as the target time-deformation-force information. For example, for the direction x , the target time-deformation-force information can be represented as ; for the direction y , the target time-deformation-force information can be represented as ; for the direction z , the target time-deformation-force information can be represented as .

[0292] In some embodiments, based on the force information in the plurality of sets of second time-deformation-force information, referring to the data screening operation in steps S141 to S143 described above, the target time-deformation-force information is determined.

[0293] It can be understood that, in the present application, the force information in the target time-deformation-force information corresponds to the minimum mean square error value, and the smaller the mean square error, the more stable the data, that is, the change of the force information in the target time-deformation-force information is smooth, and the reliability is higher.

[0294] Step S113: For each direction, performing a data optimization operation on the target time-deformation-force information to determine target deformation-force information. Here, the data optimization operation refers to further processing of the selected target time-deformation-force information to eliminate outliers, smooth curves, or adjust data distribution. Through the data optimization operation, the obtained target deformation-force information can be more consistent with the actual physical behavior. Common data optimization methods include interpolation, filtering, fitting, etc.

[0295] Step S114: Based on the target time-deformation-force information and the target deformation-force information corresponding to each of the directions, determining target extrusion test information. Dcoeff The target time-deformation-force information and the target deformation-force information corresponding to each of the directions are determined.

[0296] Here, the target time-deformation-force information and the target deformation-force information corresponding to each of the directions can refer to x the target time-deformation-force information and the target deformation-force information of the direction, y the target time-deformation-force information and the target deformation-force information of the direction, and z the target time-deformation-force information and the target deformation-force information of the direction.

[0297] In the embodiments of the present application, through the de-duplication, screening and optimization processing of multiple sets of extrusion test information, it is ensured that the target extrusion test information used finally has high representativeness and stability. On the one hand, this can reduce the influence of invalid or noise data on the establishment process of the target battery model, and on the other hand, by using the optimized data as the input of the training of the target battery model, the accuracy and reliability of the target battery model are improved.

[0298] In some embodiments, after the above step S112, steps S115 to S117 can also be included: Step S115: For each direction, determining, from the target time-deformation-force information, a plurality of first sub-target time-deformation-force information corresponding to a plurality of first type extrusion rates respectively, and second sub-target time-deformation-force information corresponding to a second type extrusion rate; In some embodiments, the second sub-target time-deformation-force information corresponding to each direction can be expressed as ; and the plurality of first sub-target time-deformation-force information corresponding to each direction can be expressed as , .

[0299] Step S116: For each direction, determine the correlation between the plurality of first sub-target time-deformation-force information and the second sub-target time-deformation-force information, respectively. In some embodiments, the first correlation between the first sub-target time-deformation-force information and the second sub-target time-deformation-force information is calculated. The first correlation between the first sub-target time-deformation-force information and the second sub-target time-deformation-force information is calculated. The second correlation between the first sub-target time-deformation-force information and the second sub-target time-deformation-force information is calculated. The second correlation between the first sub-target time-deformation-force information and the second sub-target time-deformation-force information is calculated. The second correlation between the first sub-target time-deformation-force information and the second sub-target time-deformation-force information is calculated.

[0300] Step S117: For each direction, based on the correlation corresponding to all the first sub-target time-deformation-force information, determine the correlation coefficient between the plurality of first sub-target time-deformation-force information and the second sub-target time-deformation-force information.

[0301] In some embodiments, when the first correlation and the second correlation satisfy a preset correlation threshold, the correlation coefficient is set to 1; when the first correlation and the second correlation do not satisfy the preset correlation threshold, the correlation coefficient is set to 0. Dcoeff xyz In some embodiments, when the first correlation and the second correlation satisfy a preset correlation threshold, the correlation coefficient is set to 1; when the first correlation and the second correlation do not satisfy the preset correlation threshold, the correlation coefficient is set to 0.

[0302] It can be understood that the correlation coefficient corresponding to each direction can be obtained through the above steps S115 to S117.

[0303] In some embodiments, the target time-deformation-force information includes a plurality of first sub-target time-deformation-force information corresponding to a plurality of first extrusion rates, respectively, and a second sub-target time-deformation-force information corresponding to a second extrusion rate; the first extrusion rate is much greater than the second extrusion rate; the above step S113 can include steps S1131 to S1133: Step S1131: For each first extrusion rate, based on the maximum force information in the first sub-target time-deformation-force information corresponding to the first extrusion rate, normalize the first sub-target time-deformation-force information to determine a ninth deformation-force information; based on the ninth deformation-force information and the first preset number, determine a first difference and. In this application, the target time-deformation-force information is divided into two types, which are a plurality of first sub-target time-deformation-force information corresponding to a plurality of first extrusion rates (high speed) and a second sub-target time-deformation-force information corresponding to a second extrusion rate (low speed), wherein the first sub-target time-deformation-force information is used to represent the mechanical response of the battery cell under dynamic extrusion, and the second sub-target time-deformation-force information represents the mechanical response of the battery cell under static extrusion, which can represent the mechanical response of the battery cell under different extrusion rates.

[0304] ​It can be understood that the first sub-target time-deformation-force information includes a plurality of force information, a plurality of time information and a plurality of deformation information, the plurality of force information, the plurality of time information and the plurality of deformation information are one-to-one corresponding, each force information, each time information and each deformation information form a tenth data pair, that is, the first sub-target time-deformation-force information includes a plurality of tenth data pairs. Therefore, from the force information in the plurality of tenth data pairs, the maximum force information can be obtained.

[0305] In some embodiments, the maximum force information in the first sub-target time-deformation-force information is obtained; the first sub-target time-deformation-force information is normalized with the maximum force information as a reference standard to obtain a ninth deformation-force information in a unified dimension scale, for example, V 2 extrusion rate corresponding , and V 3 extrusion rate corresponding It can be understood that the normalization processing can enhance the comparability between groups of data.

[0306] Step S1132: Based on the maximum force information in the second sub-target time-deformation-force information, the second sub-target time-deformation-force information is normalized to determine a tenth deformation-force information; based on the tenth deformation-force information and the first preset number, a second range sum is determined. Here, normalization is a common data standardization method, the purpose is to eliminate the influence caused by the dimension or scale difference due to different test conditions, so that different test data have comparability.

[0307] It can be understood that the second sub-target time-deformation-force information includes a plurality of force information, a plurality of time information and a plurality of deformation information, the plurality of force information, the plurality of time information and the plurality of deformation information are one-to-one corresponding, each force information, each time information and each deformation information form a eleventh data pair, that is, the second sub-target time-deformation-force information includes a plurality of eleventh data pairs. Therefore, from the force information in the plurality of eleventh data pairs, the maximum force information can be obtained.

[0308] In some embodiments, the maximum force information in the second sub-target time-deformation-force information is obtained; the second sub-target time-deformation-force information is normalized with the maximum force information as a reference standard to obtain a tenth deformation-force information in a unified dimension scale, for example, the second type of extrusion rate corresponding .

[0309] Step S1133: Based on a plurality of first range sums, a plurality of ninth deformation-force information, a tenth deformation-force information and a second range sum, a target deformation-force information is determined.

[0310] The steps S1131 to S1133 can obtain the target deformation-force information corresponding to each direction respectively.

[0311] In the embodiments of the present application, the extrusion test information under different extrusion rates is quantitatively evaluated by normalizing and range analysis on multiple sets of extrusion test information, and then the target deformation-force information under different extrusion rates is determined. In this way, on the one hand, the scale difference between data under different test conditions can be eliminated by normalization processing, and the comparability of data is improved. On the other hand, through range analysis, the region with large data fluctuation is identified, so that targeted optimization measures are taken to improve the quality and stability of the data.

[0312] In some embodiments, the step S1133 can further include steps S1133-1 to S1133-3: Step S1133-1: determining the data stability of the multiple ninth deformation-force information based on the multiple first range sums and the second range sum. In some embodiments, a first ratio between each first range sum and the second range sum is obtained. In a case where the first ratio corresponding to each first range sum is greater than a first preset threshold, it is determined that the data stability of the multiple ninth deformation-force information meets a target condition.

[0313] In some embodiments, a first ratio between each first range sum and the second range sum is obtained. In a case where the first ratio corresponding to each first range sum 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 a target condition.

[0314] Step S1133-2: in a case where the data stability of the multiple ninth deformation-force information meets a target condition, determining the target deformation-force information based on the second preset number, the multiple ninth deformation-force information, and the tenth deformation-force information. In some embodiments, for each ninth deformation-force information, a second preset number of first sub deformation-force information is selected from the ninth deformation-force information, and a second preset number of second sub deformation-force information is selected from the tenth deformation-force information. The 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 respectively.

[0315] 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.

[0316] 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.

[0317] 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.

[0318] For example, polynomial formulas are used to process multiple ninth deformation-force information. , By performing fitting, multiple eleventh deformation-force information were obtained. , .

[0319] 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 as the twelfth deformation information with equal intervals between them, and in implementation, the first twelfth deformation information of the twelfth deformation information is , the second twelfth deformation information is , the third twelfth deformation information is , and so on until the 100th twelfth deformation information is . The eleventh deformation-force information is linearly interpolated according to the 100 deformation values of the twelfth deformation to obtain the force information corresponding to the twelfth deformation, and in implementation, the twelfth force information corresponding to is determined , and the twelfth force information corresponding to is determined. Linear interpolation is performed according to the plurality of twelfth deformation information , the twelfth force information corresponding to , and the twelfth force information corresponding to , to obtain the twelfth force information corresponding to each twelfth deformation information, respectively; and the twelfth deformation-force information is determined based on all the twelfth deformation information and the twelfth force information corresponding to each twelfth deformation information, respectively.

[0320] In the embodiments of the present application, by evaluating the data stability based on the first range sum and the second range sum, and selecting different data processing strategies according to the stability results, unreliable data can be effectively filtered out, and the model accuracy of the target battery cell model can be improved.

[0321] In some embodiments, the above step S1131 can further include steps S1131-1 to S1131-2: Step S1131-1: selecting a plurality of fourteenth deformation-force information from the ninth deformation-force information according to a first preset number, and determining the range of force information in each fourteenth deformation-force information; Here, the first preset number refers to a value defined according to system settings or user input parameters, which is used to control the number of data selected for range operation each time. The range represents the difference between the maximum and minimum values in the force information contained in the fourteenth deformation-force information, which is used to measure the fluctuation degree of the force information contained in the fourteenth deformation-force information.

[0322] In some embodiments, the plurality of fourteenth deformation-force information can be sequentially selected in the ninth deformation-force information with the first preset number as the window, and the range of force information in each fourteenth deformation-force information is obtained For example, the ninth deformation-force information can include: W1-D1, W2-D2, W3-D3, W4-D4, W5-D5, W6-D6, W7-D7. In the case of the first preset number being 4, the fourteenth deformation-force information obtained by the first moving window is: W1-D1, W2-D2, W3-D3, W4-D4, and the maximum value and the minimum value are found from D1, D2, D3, D4 and difference operation is performed to obtain the first range value. The second moving window obtains W2-D2, W3-D3, W4-D4, W5-D5, and the maximum value and the minimum value are found from D2, D3, D4, D5 and difference operation is performed to obtain the second range value. The third moving window obtains W3-D3, W4-D4, W5-D5, W6-D6, and the maximum value and the minimum value are found from D3, D4, D5, D6 and difference operation is performed to obtain the third range value. The fourth moving window obtains W4-D4, W5-D5, W6-D6, W7-D7, and the maximum value and the minimum value are found from D4, D5, D6, D7 and difference operation is performed to obtain the fourth range value.

[0323] It can be understood that the ninth deformation-force information includes a plurality of deformation information and a plurality of force information, and the plurality of deformation information and the plurality of force information correspond one by one, so that each deformation information and each force information form a twelfth data pair, that is, the ninth deformation-force information includes a plurality of twelfth data pairs, and the fourteenth deformation-force information is selected from the first preset number of the thirteenth data pairs in the ninth deformation-force information.

[0324] Step S1131-2: Sum all the ranges to determine the first range sum.

[0325] Here, the first range sum is the result of adding all the range values corresponding to the fourteenth deformation-force information, and this index is used to reflect the fluctuation of the overall data.

[0326] For example, the first range value, the second range value, the third range value, and the fourth range value are summed to obtain the first range sum.

[0327] In the embodiments of the present application, by setting a fixed sampling interval, samples are extracted from the ninth deformation-force information, and the range is calculated to evaluate the fluctuation of the data, so that 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 fixed interval sampling.

[0328] In some embodiments, the above step 130 includes steps S131 to S133: 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; 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; 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.

[0329] 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.

[0330] For example, and , and , and Corresponding to each, and Update to the target stop information parameter module.

[0331] 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.

[0332] In some embodiments, step S131 may include steps S1311 to S1315: Step S1311: Based on the first grid information and the cell casing information, determine... xyz The 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; 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.

[0333] In some implementations, the information is determined from the first grid information. x The third node number information corresponding to the direction. Among them, xThe 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.

[0334] 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.

[0335] 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.

[0336] 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; 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. .

[0337] 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.

[0338] 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; 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. .

[0339] 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.

[0340] 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; 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. .

[0341] 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.

[0342] 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.

[0343] 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.

[0344] In some embodiments, step S132 may include steps S1321 and S1322: Step S1321: Based on the first grid information, determine the pressure head at... Figure 10 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; 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).

[0345] 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 , , .

[0346] Step S1322: Determine the pressure head position information based on the position information of the target nodes corresponding to all directions.

[0347] 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.

[0348] The following describes the application of the embodiments of this application in a real-world scenario.

[0349] In order to avoid the risk of internal short circuit caused by structural deformation invasion of the battery pack of the electric vehicle during the collision process, it is necessary to accurately simulate the mechanical properties of the battery pack in the design stage to evaluate the safety of the battery pack. As the smallest energy carrying unit in the battery pack, the accuracy of the simulation of the battery cell will directly determine the accuracy of the safety evaluation of the battery pack.

[0350] The battery cell structure is complex, and shows different mechanical properties in different stress directions, and also shows dynamic effects. The battery cell model generally includes a finite element grid reflecting the structural characteristics of the battery cell and a material model reflecting the mechanical properties of the battery cell. In order to meet the needs of engineering design, the internal structure of the battery cell often uses a macroscopic grid to simplify the simulation of the combination of different microstructures, and a material model is used to approximately simulate the comprehensive mechanical properties shown by the combination of different microstructures inside. At present, the establishment of the battery cell model has the following problems: ① The size of the battery cell is various, and the workload of manually establishing the finite element grid in the finite element pre-processing software is large; ② The material model is relatively simple, and one material model cannot reflect the anisotropy and dynamic effect characteristics of the battery cell at the same time. In the process of use, it is necessary to select the corresponding material model according to the actual stress direction or strain rate range of the battery cell, which leads to inconvenient application; ③ The anisotropy of the material model is defined by the coordinate system or vector, and the movement and rotation of the finite element grid of the battery cell will make the material model no longer match the finite element grid of the battery cell, resulting in incorrect calculation results; ④ There are too many parameters to be identified in the material model, and the simulation working conditions are various. By repeatedly trying and adjusting a certain parameter to obtain a mechanical response close to the test, the accuracy is not high, and the time is consumed.

[0351] The embodiment of the application provides a kind of determination method of battery cell model, as shown in Figure 11 Figure, including steps S300 to S370: Step S300: read input file.

[0352] Here, the input file includes file path parameters, battery cell size parameters, battery cell shell material test parameters, battery cell extrusion test parameters and extrusion head type parameters. Among them, The file path parameters include the absolute path of the source file, the absolute path of the calculation file, and the absolute path of the output file.

[0353] The battery cell size position parameters include the length of the battery cell shell (i.e. y The size), the thickness of the battery cell shell (i.e. x The size), the height of the battery cell shell (i.e. z The size), the front thickness of the battery cell shell and the back thickness of the battery cell shell (perpendicular to the y Axis surface), the left side thickness of the battery cell shell and the right side thickness of the battery cell shell (perpendicular to the x Axis surface), the top thickness of the battery cell shell and the bottom thickness of the battery cell shell (perpendicular to thez the axial surface), the internal jellyroll length of the cell, the internal jellyroll thickness of the cell, the internal jellyroll height of the cell, the desired size of the cell housing mesh, the desired size of the internal jellyroll mesh of the cell, the coordinate value of the first node of the cell mesh x , y , z the coordinate value.

[0354] The cell housing material test parameters are based on the reference metal material tensile test standard, and the deformation-force data obtained from the tensile test (wherein o = 1, 2, 3, representing 3 sets of repeated tests, and g represents g data points for each test), sample size data (such as width, gauge length, thickness) and corresponding unit system.

[0355] The cell extrusion test parameters are the deformation-force data collected when the cell is subjected to x , y , z the time-deformation-force data collected when the cell is subjected to extrusion test in the direction , , (wherein o = 1, 2, 3, representing 3 sets of repeated tests; k = 1, 2, 3, representing 3 different test rates; and g represents g data points for each test), a total of 27 sets of test data.

[0356] The extrusion head type parameters are x , y , z the shape and size of the extrusion head used when the cell is subjected to extrusion test in the three directions, for example, when the extrusion head shape input in the direction x the shape of the extrusion head in the direction is circular, and the size is D30, which means x a spherical head with a diameter of 30 mm is used for extrusion in the direction.

[0357] It should be noted that the cell housing material test parameters are optional, and whether the cell housing material test parameters (i.e., the above-mentioned multiple sets of housing material information) are needed can be determined according to the degree of simplification of the cell model, for example, if the cell model is simplified into several parts such as the cell housing, the internal jellyroll of the cell, etc., then the cell housing material test parameters are needed; if the cell model is simplified into only one part, then the cell housing material test parameters are not needed.

[0358] In some embodiments, reading the input file includes reading the input file parameters into tables, including reading the file path parameter data into a path table, reading the cell size parameters into a cell size position table, reading the cell housing material test parameters into a cell housing 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.

[0359] In some embodiments, asFigure 12 As shown in the above, the step S300 includes steps S301 to S305: Step S301: reading in file path parameters; In some embodiments, the file path parameters are read into a path table, which has 1 column and 3 rows, respectively storing the absolute path of the source file, the absolute path of the calculation file, and the absolute path of the output file.

[0360] Step S302: reading in cell size and position parameters; In some embodiments, the cell size and position parameters are read into a cell size and position table, which has 1 column and 17 rows, respectively storing the cell shell length, the cell shell thickness, the cell shell height, the cell shell front and back thickness, the cell shell left and right side thickness, the cell shell top and bottom thickness, the cell internal winding length, the cell internal winding thickness, the cell internal winding height, the expected size of the cell shell grid, the expected size of the cell internal winding grid, the coordinates of the first node of the cell grid, the coordinates of the last node of the cell grid, the coordinates of the first node of the cell internal winding grid, and the coordinates of the last node of the cell internal winding grid. x , y , z coordinate values.

[0361] Step S303: reading in cell shell material test parameters; In some embodiments, the cell shell material test parameters are read into a cell shell material test data table, which has 8 columns, from left to right, respectively storing the deformation, force, and sample size data of 3 times of cell shell material test, and the unit system.

[0362] Step S304: reading in cell extrusion test parameters; In some embodiments, 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.

[0363] Step S305: reading in extrusion head type parameters; In some embodiments, the extrusion head type parameters are read into an extrusion head type data table, which has 1 column and 6 rows, from top to bottom, respectively storing the x direction extrusion head shape, x direction extrusion head size, y direction extrusion head shape, y direction extrusion head size, z direction extrusion head shape, z direction extrusion head size.

[0364] Step S310: establishing a cell finite element grid model.

[0365] 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.

[0366] In some embodiments, such as Figure 2 As shown, step S310 above includes steps S311 to S314: Step S311: Assigning cell parameters; 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, y 1, 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.

[0367] Step S312: Calculation of cell grid node information; 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 coordinates. For example... Figure 12 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.

[0368] 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.

[0369] Step S313: Calculation of cell grid unit information; 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.

[0370] In some implementations, such as Figure 13 As 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.

[0371] Step S314: Output the finite element mesh model of the battery cell (i.e., the mesh information of the mesh model mentioned above).

[0372] 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 zThe 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.

[0373] 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).

[0374] Here, the stress-strain curve of the battery cell casing is generated based on the test data table of the battery cell casing material.

[0375] In some implementations, such as Figure 14 As shown, step S320 may further include steps S331 and S332: Step S331: Screen test data for cell casing materials; 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. d max 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).

[0376] Step S332: Convert the battery cell casing material test data.

[0377] 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).

[0378] 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.

[0379] Step S330: Preprocess cell test data.

[0380] In some implementations, such as Figure 15 As shown, step S330 may include steps S341 to S344: Step S341: Delete duplicate data (i.e., the duplicate data removal operation described above).

[0381] 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).

[0382] Step S342: Screen the cell test data (i.e., the data screening operation mentioned above).

[0383] 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).

[0384] Step S343: Calculate curve correlation; here, and This represents the dynamic compression test data in the x-direction. quasi-static compression test data in the y direction; and dynamic compression test data in the y direction, quasi-static compression test data in the y direction; and dynamic compression test data in the z direction, quasi-static compression test data in the z direction. The dynamic compression test data and correlation between the quasi-static compression test data . When the correlation is high, the correlation coefficient Dcoeff is set to 1, and when the correlation is low, the correlation coefficient Dcoeff is set to 0. Wherein, the correlation calculation value can be but not limited to the mean square error value, that is, the mean square error between the force value in the dynamic compression test data and the force value in the quasi-static compression test data, when the mean square error is lower than a certain value, it is considered that the dynamic compression test data is close to the quasi-static compression test data, that is, the correlation coefficient Dcoeff is set to 1, at the same time indicating that the battery has no dynamic effect.

[0385] It should be noted that the above may be any one of , , , the above may be any one of , , , the above may be any one of , , . Wherein, , and corresponding relationship, for example, is , is , is .

[0386] Step S344: optimizing the battery test data (i.e. the above data optimization operation).

[0387] Here, the optimized test data is a smoothing and reduction process of the data obtained in the above step S342.

[0388] In implementation, the compression test data , , screened in each direction is normalized according to the maximum value of the respective force value, to obtain , , The ninth deformation-force information is calculated; the range of force (ΔFm) in the fixed displacement window (ΔDis) is calculated, and the range of force in m fixed displacement windows is summed The first range sum and the second range sum are calculated, and when the ratio of the sum of the range of force of the dynamic test data ( ) to the sum of the range of force of the quasi-static test data ( ) is greater than a certain value, it indicates that the dynamic test data fluctuates greatly.

[0389] The dynamic test data with large fluctuations is fitted using, but not limited to, a polynomial formula , to obtain , ; the number of rows of the data , , is checked, and if the number of rows exceeds a certain value, such as 100 rows (i.e., the second preset number), 98 values are inserted as new deformation data at equal intervals between 0 and the maximum deformation value, and the force values are interpolated to form new deformation-force data , , (i.e., the target deformation-force information).

[0390] Step S340: updating the battery extrusion simulation analysis source file.

[0391] Here, the battery extrusion simulation analysis source file includes a calculation file submitted to the solver for operation, a script file for extracting the calculation results, and a test curve text file. Among them, The calculation file submitted to the solver for operation includes a main control file, a battery finite element grid model file, a battery shell material model file, a battery internal roll core equivalent material model file, and an extrusion head model file; the main control file includes three different simulation files corresponding to three different extrusion rates in three directions (xyz), i.e., nine simulation files corresponding to nine extrusion test conditions; the main control file calls the battery finite element grid model file, the battery shell material model file, the battery internal roll core equivalent material model file, and the extrusion head model file through association statements.

[0392] The script file for extracting the calculation results is a file formed according to the format requirements of the solver, which can extract the calculation results to generate the battery deformation-extrusion head reaction force data when running; The test curve text file stores the battery deformation-extrusion head reaction force data, which includes nine files, each representing a direction and a extrusion rate; ​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.

[0393] In some implementations, such as Figure 16 As shown, step S340 may include steps S351 to S357: Step S351: Update the calculation stopping parameters (i.e., the target stopping information mentioned above); 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.

[0394] Step S352: update loading parameters; In implementation, access the absolute path of the source file in the path table; open the main control file in the source file; find the line numbers corresponding to the start and end positions of the loading parameter part in the main control file; re-write the content before the start line of the loading parameter part in the main control file; call the time-deformation-force data obtained after screening the battery test data in step S330 , , , write the time-deformation data in sequence; re-write the content after the end line of the loading parameter part in sequence.

[0395] Step S353: update the parameters of the press head related statement; In implementation, access the absolute path of the source file in the path table; open the main control file in the source file; access the extrusion head shape data table to obtain the shape and size of the extrusion head in each extrusion direction; search for the extrusion head model file name corresponding to the shape and size of the extrusion head under the absolute path where the source file is stored; replace the parameters of the press head related statement in the main control file with the extrusion head model file name.

[0396] Step S354: update the position parameters of the press head; In implementation, access the absolute path of the source file in the path table; open the main control file in the source file; call the assigned battery parameters obtained in step S310 to calculate the positioning parameters of the press head in the x, y, and z directions; find the position parameters of the press head in the main control file and replace them with the new positioning parameters of the press head.

[0397] Among them, the positioning parameters of the press head in the x, y, and z directions are , , when extruding in the z direction; , , when extruding in the x direction; , , when extruding in the y direction.

[0398] Step S355: update the finite element mesh parameters of the battery; In implementation, the absolute path of the source file is accessed in the path table; the cell finite element grid model file in the source file is opened; the starting position and the ending position of the cell grid parameter part with specific mark in the cell finite element grid model file are found respectively corresponding to the line number; the content before the starting line of the cell grid parameter is written in the cell finite element grid model file in the original form; the cell finite element grid model file generated in step S340 is opened, the content is copied, and the content is written in the cell finite element grid model file in the source file in sequence with the previous step; the content after the ending line of the cell grid parameter written in the previous step is written in the original form; and the file is saved.

[0399] Step S356: updating the test curve file for benchmarking; In implementation, the absolute path of the source file is accessed in the path table; the test curve file for benchmarking in the source file is opened; the deformation-force data obtained after the test data is smoothed and reduced in step S340 is called 、 、 , and the original data in the test curve file for benchmarking is replaced.

[0400] Step S357: updating the stress-strain curve; In implementation, the absolute path of the source file is accessed in the path table; the cell shell material model file in the source file is opened; the stress-strain curve in step S320 is called (wherein g=1, 2,..., 20), and the original shell strain-stress information in the cell shell material model in the source file is replaced.

[0401] Step S350: optimizing the static parameters of the equivalent material of the cell internal winding core.

[0402] Here, the quasi-static parameters of the equivalent material of the cell internal winding core are the x-direction strain-stress data pair (that is, the above target strain-stress information), the y-direction strain-stress data pair (that is, the above target strain-stress information), and the z-direction strain-stress data pair (that is, the above target strain-stress information), wherein 2≤ ≤6; the strain is a predefined unequal interval or equal interval number , wherein represents the number of strain-stress data pairs.

[0403] Optimizing the quasi-static parameters of the equivalent material of the cell internal winding core is to find a group of stress values corresponding to a predefined strain, so that the deformation-force data extracted in simulation is as close as possible to the deformation-force data in test. The order of optimizing the quasi-static parameters of the equivalent material of the cell internal winding core is the x-direction strain-stress data pair y-direction strain-stress data strain-stress data in the z-direction .

[0404] In some implementations, such as Figure 17 As shown, step S360 above includes steps S361 to S364: Step S361: First optimization iteration; 1) The first sampling of the stress value to be optimized; 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, .

[0405] 2) Generate the calculation file for the first iteration; 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 (i.e., the first cell model 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.

[0406] 3) Extraction of the calculation results of the first iteration; 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.

[0407] 4) Approximate model selection; 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.

[0408] 5) Stress parameter optimization based on approximate model; 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.

[0409] Step S362: Second optimization iteration; 1) The stress value to be optimized is sampled for the second time; 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 third strain-stress information mentioned above) is used as one of the first sampled values.

[0410] 2) Generate the calculation file for the second iteration; 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.

[0411] 3) Extraction of the results of the second iteration; 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. 4) Approximate model selection; At least three first approximation models are established, and the obtained p groups of sampling values are taken as the input of each first approximation model, and the p groups of predicted deformation-force data are obtained by running each approximation model on the p groups of sampling values (I.e. the above-mentioned multiple groups of second deformation-force information). For each first approximation model, the predicted deformation-force data corresponding to the same sampling value is obtained And the first mean square error value between the p groups of simulated deformation-force data is determined. Based on the first mean square error value corresponding to all approximation models respectively, the first approximation model corresponding to the minimum mean square error value is determined as the first target approximation model.

[0412] 5) Stress value parameter optimization based on the approximation model; The first target approximation model determined in the above 4) is optimized, and the variable range is , the constraint condition is , the design space scaling factor, and the optimization target is the minimum mean square error value between the predicted deformation-force data predicted by the first target approximation model and the test deformation-force data stored in the test curve file . The optimization termination condition is that the number of iterations reaches a set value or the mean square error value between the predicted deformation-force data predicted by the approximation model and the test deformation-force data is less than a set value.

[0413] Step S363: n-th optimization iteration; By analogy, the above first iteration process is repeated, and the third, fourth, and fourth iterations are performed until the optimization termination condition is reached.

[0414] Step S364: x-direction optimization value determination.

[0415] The mean square error value between the simulated deformation-force data extracted from all iteration simulation files and the test deformation-force data is calculated, the simulation folder with the minimum mean square error value is found, and the x-direction strain-stress data pair value in the cell internal roll core equivalent material model file is extracted, which is the optimal x-direction strain-stress data pair , then access the cell internal roll core equivalent material model file stored in the absolute path of the source file, and replace the x-direction strain-stress data pair with .

[0416] Optimize the y-direction strain-stress data pair of the cell internal roll core equivalent material quasi-static parameter , and refer to the x-direction strain-stress data pair of the cell internal roll core equivalent material quasi-static parameter After the optimization is completed, the source file of the equivalent material model file of the internal winding of the battery cell under the absolute path is replaced by the optimal y-direction strain-stress data pair .

[0417] Optimizing the z-direction strain-stress data pair of the equivalent material of the internal winding of the battery cell , referring to the x-direction strain-stress data pair of the optimized equivalent material of the internal winding of the battery cell After the optimization is completed, the source file of the equivalent material model file of the internal winding of the battery cell under the absolute path is replaced by the optimal z-direction strain-stress data pair .

[0418] Step S360: Optimizing the dynamic parameters of the equivalent material of the internal winding of the battery cell.

[0419] Here, the dynamic parameters of the equivalent material of the internal winding of the battery cell are the x-direction strain rate parameter-scaling factor data pair , the y-direction strain rate parameter-scaling factor data pair , and the z-direction strain rate parameter-scaling factor data pair , wherein 2≤ ≤6; the strain rate parameter is a predefined number of unequal intervals or equal intervals , wherein represents the number of strain-stress data pairs.

[0420] Optimizing the dynamic parameters of the equivalent material of the internal winding of the battery cell is to find a set of scaling factor values corresponding to the predefined strain rate parameters, so that the deformation-force data extracted in the simulation is as close as possible to the deformation-force data of the test. Among them, the order of optimizing the quasi-static parameters of the equivalent material of the internal winding of the battery cell is the x-direction strain rate parameter-scaling factor data pair , the y-direction strain rate parameter-scaling factor data pair , and the z-direction strain rate parameter-scaling factor data pair .

[0421] In some embodiments, the correlation coefficient in the x-direction calculated in the above step S330 is obtained, and when Dcoeff=1, then =1, and in this scenario, all the scaling factors in the x-direction strain rate parameter-scaling factor data pair of the equivalent material model file of the internal winding of the battery cell under the source file storage absolute path are replaced by 1; when Dcoeff=0, as shown in Figure 18 The above step S360 includes steps S371 to S374: Step S371: First optimization iteration; 1) the first sampling of the scaling coefficient to be optimized; Here, the sampling is performed in the range (i.e., the third range described above), and after excluding the samples that do not meet the constraint condition , not less than q groups of second sampling values are formed, wherein . .

[0422] 2) generating the first iteration calculation file; Accessing the absolute path of the source file storage, copying the dynamic extrusion simulation analysis related source files of the first and second rates (i.e., the multiple first extrusion rates described above) in the cell extrusion simulation analysis source file obtained in the above step S340 q times, and storing each rate in each folder under the calculation file storage absolute path, and then modifying the strain rate parameter-scaling coefficient data value of each cell internal winding core equivalent material model file in each folder under the calculation file storage absolute path at different rates to one group of the second sampling values.

[0423] 3) first iteration calculation result extraction; Calling the solver to run the calculation file submitted to the solver for operation under the q folders at different rates, and after the calculation is completed, running the script file for extracting the calculation result, and extracting q groups of simulation deformation-force data , (i.e., the multiple groups of the seventh deformation-force information corresponding to the multiple first extrusion rates respectively) at different rates. , wherein represents the number of deformation-force data, and the value is equal to .

[0424] 4) approximate model selection; Establishing not less than three second approximate models, taking the q groups of second sampling values obtained as the input of each second approximate model, and running each second approximate model on the q groups of sampling values to obtain the predicted deformation-force data and (i.e., the multiple groups of the seventh deformation-force information corresponding to the multiple first extrusion rates respectively) at the first and second rates. For each second approximate model, the first mean square error value between the predicted deformation-force data and the simulation deformation-force data corresponding to the first sampling rate of the same sampling value, and the second mean square error value between the predicted deformation-force data and the simulation deformation-force data corresponding to the second sampling rate of the same sampling value are obtained.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.

[0425] 5) Scaling factor optimization based on approximate model; 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 predicted by the second objective approximation model 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 rate of 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.

[0426] Step S372: Second optimization iteration; 1) The scaling factor to be optimized is sampled for the second time; 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.

[0427] 2) Generate the calculation file for the first iteration; 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. 3) Extraction of the calculation results of the first iteration; 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. , .

[0428] 4) Approximate model selection; 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.

[0429] 5) Scaling factor optimization based on approximate model; 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 predicted by the second objective approximation model 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 rate of 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.

[0430] Step S373: The nth optimization iteration; This process is repeated for the second iteration, then for the third, fourth, and so on, until the optimization termination condition is met.

[0431] Step S374: Determine the optimized value in the x-direction.

[0432] Calculate the mean square error value of the 1st rate simulation deformation-force data extracted from all iteration simulation folders and the test deformation-force data (i.e. the above-mentioned 6th deformation-force information) and the 2nd rate simulation deformation-force data and the test deformation-force data , find the simulation folder with the minimum mean square error value, and extract the x-direction strain rate parameter-scaling factor data pair value in the cell internal roll core equivalent material model file, which is the optimal x-direction strain-stress data pair , then access the cell internal roll core equivalent material model file in the source file storage absolute path, and replace the x-direction strain-stress data pair with (i.e. the above-mentioned target strain rate-scaling factor information).

[0433] Optimize the y-direction strain rate parameter-scaling factor data pair of the cell internal roll core equivalent material dynamic parameters , check the correlation coefficient of the y-direction quasi-static and dynamic extrusion test data, when Dcoeff=1, then In this scenario, replace all the scaling factors in the y-direction strain rate parameter-scaling factor data in the cell internal roll core equivalent material model file in the source file storage absolute path with 1; when Dcoeff=0, then optimize the y-direction strain rate parameter-scaling factor data pair of the cell internal roll core equivalent material dynamic parameters according to the steps of optimizing the x-direction strain rate parameter-scaling factor data pair of the cell internal roll core equivalent material dynamic parameters . After optimization, replace the y-direction strain rate parameter-scaling factor data pair in the cell internal roll core equivalent material model file in the source file storage absolute path with the optimal y-direction strain rate parameter-scaling factor data pair .

[0434] Optimize the z-direction strain rate parameter-scaling factor data pair of the cell internal roll core equivalent material dynamic parameters , check the correlation coefficient of the z-direction quasi-static and dynamic extrusion test data, when Dcoeff=1, then In this scenario, replace all the scaling factors in the z-direction strain rate parameter-scaling factor data in the cell internal roll core equivalent material model file in the source file storage absolute path with 1; when Dcoeff=0, then optimize the z-direction strain rate parameter-scaling factor data pair of the cell internal roll core equivalent material dynamic parameters according to the steps of optimizing the x-direction strain rate parameter-scaling factor data pair of the cell internal roll core equivalent material dynamic parameters After the optimization is completed, the source file is stored in the z-direction strain rate parameter-scaling factor data pair of the equivalent material model file of the internal winding core of the battery at an absolute path, and the optimal z-direction strain-stress data pair is replaced .

[0435] Step S370: output the battery model.

[0436] Here, the source file storage absolute path is accessed, the battery finite element grid model file, the battery shell material model file, and the internal winding core equivalent material model file contents are read and copied; a new file is created at the output file storage absolute path, the contents copied in the previous step are opened and written, and finally saved to form a battery model file.

[0437] The embodiments of the application can bring the following beneficial effects: (1) The battery finite element grid is parameterized, the node order, element direction, and position of the finite element grid are uniquely determined, and there is no difference caused by human factors, the standardization is high, and the grid generation speed is faster; (2) The number of optimization iterations is greatly reduced, and the difficulty of identification is reduced; (3) The anisotropy and dynamic effect of the battery are unified in one model, and each direction has independent material parameters to describe the quasi-static and dynamic mechanical properties, and the difference between simulation and test results is minimized, and the battery model can be quickly and accurately obtained through iterative optimization.

[0438] Based on the foregoing embodiments, the embodiments of the application provide a battery model determination device, as shown in xyz The battery model determination device 1800 includes: An acquisition module 1810 is configured to acquire target information of a battery; the target information of the battery includes size information of the battery, a plurality of groups of extrusion test information, and model information of an initial battery model; A first determination module 1820 is configured to determine grid information of a grid model of the battery based on the size information of the battery; the grid information of the grid model includes first grid information of a shell of the battery and second grid information of a winding core of the battery; A second determination module 1830 is configured to perform a preprocessing operation on the plurality of groups of extrusion test information to determine target extrusion test information; the preprocessing operation includes at least one of the following: a repeated data elimination operation, a data screening operation, and a data optimization operation; An update module 1840 is configured to update the model information of the initial battery model based on the first grid information, the second grid information, and the target extrusion test information to obtain a target battery model; The update module includes: a first update unit configured to update the model information of the initial battery 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 model; and a second obtaining unit configured to obtain the model information of the first battery model. xyzThe target parameter corresponding to each direction is updated into the model information of the first battery cell model, and a target battery cell model is obtained.

[0439] In some embodiments, the target information includes a plurality of sets of shell material information of the shell, and the determination apparatus of the battery cell model further includes: a third determination module, configured to determine target shell material information based on the plurality of sets of shell material information, wherein a mean square error value corresponding to force information in the target shell material information is the smallest; a fourth determination module, configured to determine curve information of a target stress-strain curve based on the target shell material information; and the first updating unit is further configured to update 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.

[0440] In some embodiments, the third determination module includes: a first determination unit, configured to determine first shell material information in the plurality of sets of shell material information, and a plurality of second shell material information; a data amount of the first shell material information is greater than data amounts of the plurality of second shell material information respectively; a first obtaining unit, configured to perform interpolation processing on the plurality of second shell material information respectively based on the first shell material information, to obtain a plurality of third shell material information; the data amount of the first shell material information is equal to data amounts of the plurality of third shell material information respectively; and a second determination unit, configured to determine the target shell material information based on the first shell material information and the plurality of third shell material information.

[0441] In some embodiments, the fourth determination module includes: a third determination unit, configured to determine the curve information of the first stress-strain curve based on a plurality of deformation information and a plurality of force information in the target shell material information; a fourth determination unit, configured to determine first elastic strain information based on the curve information of the first stress-strain curve; a fifth determination unit, configured to determine 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 determination unit, configured to determine the curve information of the target stress-strain curve based on the curve information of the first stress-plastic strain curve.

[0442] In some embodiments, the target parameter includes target strain-stress information; and the second obtaining unit includes: a first determination subunit, configured to determine a plurality of first iteration strain-stress information in each iteration round for each direction, wherein the plurality of first iteration strain-stress information includes a plurality of first strain-stress information preset, and a plurality of first stress information determined based on a first range; a first strain information corresponds to a first stress information; and a first running subunit, configured to determine a plurality of second iteration strain-stress information in each iteration round for each direction based on the plurality of first iteration strain-stress information and the plurality of first stress-plastic strain curves. xyz In some embodiments, the target parameter includes target strain-stress information; and the second obtaining unit includes: a first determination subunit, configured to determine a plurality of first iteration strain-stress information in each iteration round for each direction, wherein the plurality of first iteration strain-stress information includes a plurality of first strain-stress information preset, and a plurality of first stress information determined based on a first range; a first strain information corresponds to a first stress information; and a first running subunit, configured to determine a plurality of second iteration strain-stress information in each iteration round for each direction based on the plurality of first iteration strain-stress information and the plurality of first stress-plastic strain curves. xyzThe first update sub-unit is configured to update the target strain-stress information corresponding to each of the xyz directions into the model information of the first battery cell model, to obtain a target battery cell model. xyz The second determination sub-unit is configured to determine, for each of the directions, the plurality of first iteration strain-stress information corresponding to the next iteration round based on the plurality of preset first strain-stress information corresponding to the next iteration round and the plurality of first deformation-force information and the plurality of first iteration strain-stress information corresponding to the current iteration round, until the first iteration termination condition is met. xyz The third determination sub-unit is configured to determine, for each of the directions, the target strain-stress information from the plurality of first iteration strain-stress information corresponding to all the iteration rounds based on the plurality of first deformation-force information corresponding to all the iteration rounds and the fourth deformation-force information, wherein a mean square error value between the first deformation-force information corresponding to the target strain-stress information and the fourth deformation-force information is the smallest, and the fourth deformation-force information is obtained by performing the extrusion experiment on the battery cell at the second type of extrusion rate.

[0443] In some embodiments, the second determination sub-unit is further configured to determine the third strain-stress information based on the plurality of first deformation-force information, the plurality of first iteration strain-stress information and the plurality of preset first approximate models; and determine the plurality of first iteration strain-stress information corresponding to the next iteration round by taking the plurality of preset first strain-stress information corresponding to the next iteration round and the third strain-stress information corresponding to the current iteration round as the plurality of first iteration strain-stress information corresponding to the next iteration round.

[0444] In some embodiments, the second determining subunit is further configured to: input the plurality of groups of first iteration strain-stress information into a plurality of preset first approximation models respectively, to determine a plurality of groups of second deformation-force information respectively corresponding to the plurality of first approximation models; determine a first target approximation model from the plurality of first approximation models based on the plurality of groups of second deformation-force information respectively corresponding to the plurality of first approximation models and the plurality of groups of first deformation-force information, wherein a mean square error value between the plurality of groups of second deformation-force information respectively corresponding to the first target approximation model and the plurality of groups of first deformation-force information is the minimum; perform iteration calculation on the plurality of groups of second iteration strain-stress information as input of the first target approximation model, to obtain a plurality of groups of third deformation-force information through the first target approximation model, until a second iteration termination condition of the first target approximation model is satisfied; and determine third strain-stress information from the plurality of groups of second iteration strain-stress information respectively corresponding to all iteration rounds based on the plurality of groups of third deformation-force information respectively corresponding to all iteration rounds and fourth deformation-force information, wherein a mean square error value between third deformation-force information corresponding to the third strain-stress information and the fourth deformation-force information is the minimum.

[0445] In some embodiments, the target parameter includes target strain rate-scaling coefficient information; the second obtaining unit includes: a fourth determining subunit configured to, for each direction in the plurality of directions, xyz determine, in each iteration round, a plurality of groups of first iteration strain rate-scaling coefficient information, wherein the plurality of groups of first iteration strain rate-scaling coefficient information includes a plurality of preset first strain rate-scaling coefficient information, the first strain rate-scaling coefficient information includes a plurality of preset first strain rate information and a plurality of first scaling coefficient information determined based on a third range, and the first scaling coefficient information corresponds to the first strain rate information; and a second updating subunit configured to, for each direction in the plurality of directions, xyz update the plurality of groups of first iteration strain rate-scaling coefficient information to model information of the first battery cell model, to obtain, through the first battery cell model, a plurality of groups of fifth deformation-force information respectively corresponding to the plurality of first extrusion rates; a fifth determining subunit configured to, for each direction in the plurality of directions, xyz determine, based on the plurality of preset groups of first strain rate-scaling coefficient information corresponding to a next iteration round and the plurality of groups of first iteration strain rate-scaling coefficient information corresponding to a current iteration round and the plurality of groups of fifth deformation-force information respectively corresponding to the plurality of first extrusion rates, the plurality of groups of first iteration strain rate-scaling coefficient information corresponding to the next iteration round, until a third iteration termination condition of iteration is satisfied; and a sixth determining subunit configured to, for each direction in the plurality of directions, xyzFor each of the directions, the target strain rate-scaling factor information is determined from the plurality of sets of the first iteration strain rate-scaling factor information corresponding to all the iteration rounds, based on the plurality of sets of the fifth deformation-force information corresponding to the plurality of first type extrusion rates respectively; the sum of the mean square error values between the plurality of fifth deformation-force information corresponding to the plurality of first type extrusion rates under the target strain rate-scaling factor information and the plurality of sixth deformation-force information under the plurality of first type extrusion rates is the minimum; the plurality of sixth deformation-force information is obtained by performing the extrusion experiment on the battery cell through the plurality of first type extrusion rates; the third updating subunit is configured to update the target strain rate-scaling factor information corresponding to each of the directions into the model information of the first battery cell model, to obtain a target battery cell model. xyz For each of the directions, the target strain rate-scaling factor information is determined from the plurality of sets of the first iteration strain rate-scaling factor information corresponding to all the iteratio...

Claims

1. A method for determining a battery cell model, characterized in that, The method includes: Obtain target information for the battery cell; the target information for the battery cell includes the size information of the battery cell, multiple sets of extrusion test information, and model information of the initial battery cell model; Based on the size information of the battery cell, the mesh information of the battery cell's mesh model is determined; 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. The multiple sets of extrusion test information are preprocessed to determine the target extrusion test information; the preprocessing operation includes at least one of the following: duplicate data removal operation, data filtering operation, and data optimization operation. 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 to obtain the target cell model; The step of 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 to obtain the target cell model includes: 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; Will 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.

2. The method based on claim 1, characterized in that, The target information includes multiple sets of shell material information for the shell, and the method further includes: Based on the multiple sets of shell material information, the target shell material information is determined; the root mean square error value corresponding to the force information in the target shell material information is minimized. Based on the target shell material information, the curve information of the target stress-strain curve is determined; The step of 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, includes: 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, the model information of the initial cell model is updated to obtain the model information of the first cell model.

3. The method based on claim 2, characterized in that, The step of determining the target shell material information based on the multiple sets of shell material information includes: The first type of shell material information and multiple second type shell material information are determined from the 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. Based on the first type of shell material information, interpolation processing is performed on the plurality of second type 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; Based on the first type of shell material information and the plurality of third type shell material information, the target shell material information is determined.

4. The method based on claim 2, characterized in that, The determination of the target stress-strain curve information based on the target shell material information includes: Based on multiple deformation and force information in the target shell material information, the curve information of the first stress-strain curve is determined; Based on the curve information of the first stress-strain curve, the first elastic strain information is determined; Based on the first elastic strain information and the curve information of the first stress-strain curve, the curve information of the first stress-plastic strain curve is determined. Based on the curve information of the first stress-plastic strain curve, the curve information of the target stress-strain curve is determined.

5. The method based on claim 1, characterized in that, The target parameters include target strain-stress information; The 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: Regarding the above xyz In 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; Regarding the above xyz In each direction, the multiple sets of first iterative 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; Regarding the above xyz 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 xyz 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 xyz 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 based on claim 5, characterized in that, The determination of multiple sets of first iterative strain-stress information corresponding to the next iteration round based on multiple sets of preset first strain-stress information corresponding to the next iteration round, multiple sets of first deformation-force information corresponding to the current iteration round, and the multiple sets of first iterative strain-stress information includes: 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, the third strain-stress information is determined; 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, are determined as the multiple sets of first iteration strain-stress information corresponding to the next iteration round.

7. The method based on claim 6, characterized in that, The determination of 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 includes: The multiple sets of first iterative strain-stress information are respectively input into multiple preset first approximation models to determine multiple sets of second deformation-force information corresponding to the multiple first approximation models; 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, a first target approximation model is determined from the multiple first approximation models; the mean square error between the multiple sets of second deformation-force information corresponding to the first target approximation model and the multiple sets of first deformation-force information is minimized. Multiple sets of second-iteration strain-stress information are used as inputs to the first target approximation model for iterative calculation. Multiple sets of third-deformation-force information are obtained through the first target approximation model until the second iteration termination condition of the first target approximation model is met. The multiple sets of second-iteration strain-stress information include multiple sets of second strain-stress information, and the second strain-stress information includes 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 corresponding to all iteration rounds, and the fourth deformation-force information, 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 corresponding to the third strain-stress information and the fourth deformation-force information is minimized.

8. The method based on claim 1, characterized in that, The target parameters include target strain rate-scaling factor information; The 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: Regarding the above 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 a third range; the first scaling coefficient information corresponds to the first strain rate information; Regarding the above xyz In each direction, the multiple sets of first iterative strain rate-scaling coefficient 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 extrusion rates are obtained. Regarding the above 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. Regarding the above xyz 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 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.

9. The method based on claim 8, characterized in that, The determination of multiple sets of first-iteration strain rate-scaling coefficient information corresponding to the next iteration round, based on multiple sets of first-iteration strain rate-scaling coefficient information corresponding to the current iteration round and multiple sets of fifth-deformation-force information corresponding to multiple first-type extrusion rates, includes: Based on the multiple sets of fifth deformation-force information corresponding to the multiple first-type extrusion rates, the multiple sets of first-iteration strain rate-scaling coefficient information, and the multiple preset second approximation models, the third strain rate-scaling coefficient information is determined; 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, are determined as the multiple sets of first iteration strain rate-scaling factor information corresponding to the next iteration round.

10. The method based on claim 9, characterized in that, The determination of the third strain rate-scaling coefficient information based on multiple sets of fifth deformation-force information corresponding to the multiple first-type extrusion rates, the multiple sets of first-iteration strain rate-scaling coefficient information, and multiple preset second approximation models includes: The multiple sets of first iterative strain rate-scaling factor information are input into multiple preset second approximation models to determine multiple sets of seventh deformation-force information corresponding to the multiple first type of extrusion rates; Based on the multiple sets of seventh deformation-force information corresponding to the multiple first-type extrusion rates under the multiple second approximation models, and the multiple sets of fifth deformation-force information corresponding to the multiple first-type extrusion rates, a second target approximation model is determined from the multiple second approximation models; the sum of the root mean square errors between the multiple sets of seventh deformation-force information corresponding to the multiple first-type extrusion rates and the multiple sets of fifth deformation-force information corresponding to the multiple first-type extrusion rates of the second target approximation model is minimized. Multiple sets of second-iteration strain rate-scaling coefficient information are used as inputs to the second target approximation model for iterative calculation. Multiple sets of eighth deformation-force information corresponding to multiple first-type extrusion rates are obtained through the second target approximation model until the fourth iteration termination condition of the second target 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 include multiple preset first strain rate information and multiple second scaling coefficient information determined based on the fourth range. Based on multiple sets of eighth deformation-force information corresponding to multiple first-type extrusion rates in all iteration rounds, and multiple sixth deformation-force information under the multiple first-type extrusion rates, a third strain rate-scaling coefficient information is determined from 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 minimized.

11. The method based on claim 1, characterized in that, 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 step of determining the mesh information of the battery cell's mesh model based on the cell's size information includes: Based on the cell casing information, the expected size information of the casing mesh, and the thickness information corresponding to the multiple surfaces, the first node information of each node in the multiple surfaces and the first unit information of each unit in the multiple surfaces are determined. Based on the expected size information of the core mesh, the core information, and the first node information of each node in the plurality of faces, the second node information of each node in the core and the second unit information of each unit in the core are determined. The mesh information of the mesh model is determined based on the first node information corresponding to all nodes in the plurality of faces, the first unit information corresponding to all units in the plurality of faces, the second node information corresponding to all nodes in the core, and the second unit information corresponding to all units in the core.

12. The method based on claim 11, characterized in that, The node information includes node number information and node location information; the unit information includes unit number information. The determination of the first node information of each node in the plurality of surfaces and the first unit information of each unit in the plurality of surfaces, based on the cell casing information, the expected size information of the casing mesh, and the thickness information corresponding to the plurality of surfaces, includes: Based on the cell casing information, the expected size information of the casing mesh, and the thickness information corresponding to the multiple surfaces, the first node number information and the first node position information of each node are determined; Based on the cell casing information, the expected size information of the casing mesh, the thickness information corresponding to the multiple surfaces, and the first node number information corresponding to all nodes in the multiple surfaces, the first unit number information of each unit in the multiple surfaces is determined; the first unit number information includes the first sub-number information used to identify the unit, and the first node number information corresponding to the nodes that make up the unit.

13. The method based on claim 1, characterized in that, The target compression test data includes xyz The target time-deformation-force information for each direction, and the target deformation-force information for each direction; The xyz Directions include x direction, y direction and z Direction; the compression test information includes xyz First-time deformation-force information for each direction; The preprocessing operation on the multiple sets of extrusion test information to determine the target extrusion test information includes: For each set of first time-deformation-force information in each direction, based on the deformation information in the first time-deformation-force information, a duplicate data removal operation is performed on the first time-deformation-force information to obtain the second time-deformation-force information; For each direction, based on the force information in multiple sets of second time-deformation-force information, a data filtering operation is performed on the 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, data optimization operations are performed 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.

14. The method based on claim 13, characterized in that, 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 data optimization operation on the target time-deformation-force information to determine the target deformation-force information includes: For each type of extrusion rate, based on the maximum force information in the time-deformation-force information of the first sub-target corresponding to the first type of extrusion rate, the time-deformation-force information of the first sub-target is normalized to determine the ninth deformation-force information; based on the ninth deformation-force information and the first preset quantity, the first range is determined. Based on the maximum force information in the second sub-target time-deformation-force information, the second sub-target time-deformation-force information is normalized to determine the tenth deformation-force information; based on the tenth deformation-force information and the first preset quantity, the second range is determined. The target deformation-force information is determined based on multiple first range sums, multiple ninth deformation-force information, the tenth deformation-force information, and the second range sum.

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

16. The method based on claim 14, characterized in that, The determination of the first range based on the ninth deformation-force information and the first preset quantity includes: According to the first preset number, select multiple fourteenth deformation-force information from the ninth deformation-force information, and determine the range of force information in each fourteenth deformation-force information; Sum all the ranges to determine the first range sum.

17. The method based on any one of claims 1 to 16, characterized in that, The step of 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, includes: Based on the first grid information, the cell casing information, and the target extrusion test information, target stop information is determined; the target stop information is used to control the stop operation of the target cell model. Based on the first grid information, the pressure head position information is determined; the pressure head position information represents the position of the pressure head used to compress the battery cell on the battery cell. 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, the model information of the initial cell model is updated to obtain the model information of the first cell model.

18. The method based on claim 17, characterized in that, The step of determining the target stop information based on the first grid information, the cell casing information, and the target compression test information includes: Based on the first grid information and the cell casing information, determine xyz The information includes the third node number corresponding to each direction; the cell casing information includes the cell length, cell height, and cell thickness; and the third node number is related to the cell's position in the direction of the direction. xyz The directions correspond to the number of the nearest node at the center point of the surface; Based on the cell thickness information in the cell casing information, and the target compression test information... x The maximum deformation value in the target deformation-force information along the direction is used to determine the first difference; Based on the cell length information in the cell casing information, and the target compression test information... y The maximum deformation value in the target deformation-force information in the direction is used to determine the second difference; 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; 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.

19. The method based on claim 17, characterized in that, The step of determining the pressure head position information based on the first grid information includes: Based on the first grid information, the pressure head is determined to be in... xyz 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 the position information of the target nodes corresponding to all directions.

20. A device for determining a battery cell model, characterized in that, The device includes: The acquisition module is used to acquire 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 the initial battery cell model; The first determining module 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's casing and the second mesh information of the battery cell's core. The second determining module is used to perform preprocessing operations on the 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. The update module 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; The update module includes: The first update unit 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, and to determine the model information of the first cell model. The second receiving unit is 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.

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

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

23. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 19.

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