A method and system for testing a battery pack

Abstract

The present application relates to the technical field of battery pack testing, and specifically relates to a power battery pack top pressure simulation method and a testing system, which comprises the steps of constructing a battery pack model, a top pressure device model and a support platform model; building finite element models corresponding to each model to form corresponding battery pack finite element models, top pressure device finite element models and support platform finite element models; calling test data and real test result data corresponding to a battery pack top pressure real test from a database; setting a corresponding battery pack top pressure simulation test according to the test data corresponding to the battery pack top pressure real test; outputting simulation result data according to the battery pack top pressure simulation test; judging whether the corresponding simulation result data is reasonable according to the simulation result data and the real test result data; if so, extracting corresponding characteristic parameters according to the corresponding simulation result data and forming a corresponding simulation report.

Description

Technical Field

[0001] This invention relates to the field of battery pack testing technology, specifically to a power battery pack top-pressure simulation method and testing system. Background Technology

[0002] With the rapid development of new energy vehicles, the safety and stability of battery packs, as a core component of electric vehicle power systems, are receiving increasing attention. Battery packs not only bear the crucial task of providing power to the vehicle but also directly affect the overall vehicle safety and user experience. However, battery packs are typically installed under the vehicle body, making them susceptible to various external loads, such as heavy objects accidentally placed by the owner, pressure from passengers' footsteps, and accidents like trampling during maintenance and transportation. These external forces not only threaten the structural safety of the battery pack but may also adversely affect its performance and lifespan.

[0003] To ensure that the battery pack can withstand various external loads and maintain stable operation, the traditional approach is to verify it through physical load testing. However, this method has significant limitations:

[0004] Physical experiments require a large investment in materials and equipment, especially for multiple tests under different working conditions, which keeps the overall cost high.

[0005] From design to manufacturing to actual testing, the entire process is time-consuming and cannot meet the needs of rapid design iteration.

[0006] External loads are often variable and complex, and physical tests cannot fully simulate these working conditions, which may lead to deviations in test results and fail to fully reflect the actual situation.

[0007] Therefore, there is an urgent need for a power battery pack top-pressure simulation method and testing system that can realistically and accurately simulate the response behavior of the battery pack under different external force loads, and solve the problems of high cost, long cycle and difficulty in simulating complex working conditions in the existing technology. Summary of the Invention

[0008] One of the objectives of this invention is to provide a power battery pack top-pressure simulation method and testing system that can realistically and accurately simulate the response behavior of the battery pack under different external force loads, solving the problems of high cost, long cycle and difficulty in simulating complex working conditions in the prior art.

[0009] To achieve the above objectives, a method for simulating the top-voltage load of a power battery pack is provided, comprising the following steps:

[0010] S1. Based on the battery pack, the top pressure device, and the support platform, construct the corresponding battery pack model, top pressure device model, and support platform model;

[0011] S2. Based on the constructed battery pack model, top pressure device model, and support platform model, build the corresponding finite element models for each model to form the corresponding battery pack finite element model, top pressure device finite element model, and support platform finite element model.

[0012] S3. Retrieve the test data and actual test results data corresponding to the actual battery pack top pressure test from the database; Based on the test data corresponding to the actual battery pack top pressure test, the finite element model of the battery pack, the finite element model of the top pressure device, and the finite element model of the support platform, set up the corresponding battery pack top pressure simulation test.

[0013] S4. Based on the battery pack top pressure simulation test and the battery pack top pressure real test, output the corresponding simulation result data;

[0014] S5. Based on the simulation results and the actual experimental results, determine whether the corresponding simulation results are reasonable. If so, extract the corresponding feature parameters and generate the corresponding simulation report. If not, correct each finite element model and re-execute S3 after correction.

[0015] The technical principles and effects of this scheme are as follows: In this scheme, the battery pack model, top-pressure device model, and support platform model are constructed using the battery pack, top-pressure device, and support platform from real-world experiments. Each constructed model is discretized into multiple finite element elements, thus forming the corresponding finite element models of the battery pack, top-pressure device, and support platform. By constructing each model in detail and performing finite element analysis, the various mechanical behaviors of the battery pack under top-pressure conditions can be considered more comprehensively, improving the accuracy of the simulation results. When the simulation results are unreasonable, the finite element models can be corrected in a timely manner, ensuring that the final simulation results are highly consistent with the actual situation.

[0016] Next, based on each finite element model, corresponding battery pack top-pressure simulation tests are set up, and corresponding actual battery pack top-pressure tests are conducted simultaneously to obtain the corresponding simulation result data and actual test result data. By comparing the simulation result data and the actual test result data, the rationality of the corresponding simulation result data is determined. If it is reasonable, the corresponding feature parameters can be extracted to generate a corresponding simulation report. If it is unreasonable, each finite element model is corrected, and simulation and comparison are performed again until it is reasonable.

[0017] By retrieving real experimental data and using it in simulation settings, the simulation conditions are made as close to the actual situation as possible, thereby improving the accuracy of the simulation results.

[0018] In this solution, the finite element model corresponding to the simulation is corrected by comparing the simulation test data with the actual result data, thereby ensuring the accuracy and reliability of the simulation results. It can quickly and accurately simulate the performance of the battery pack in the top pressure test, reduce the need for physical experiments, and reduce costs and time. It can realistically and accurately simulate the response behavior of the battery pack under different external force loads, solving the problems of high cost, long cycle and difficulty in simulating complex working conditions in the existing technology.

[0019] Furthermore, S4 includes the following steps:

[0020] S40. Based on the structural characteristics and key mechanical response parts of the battery pack, determine the most representative feature points of the battery pack, and mark the determined feature points on the finite element model of the battery pack in the top pressure simulation test.

[0021] S41. After determining and marking the corresponding feature points, conduct a corresponding battery pack top-pressure simulation test under the same top-pressure conditions as the actual battery pack top-pressure test. During the battery pack top-pressure simulation test and the actual battery pack top-pressure test, extract the simulation feature point data and actual feature point data corresponding to each feature point under each of the same loading stages, and form their respective simulation result data and actual test result data. The actual test result data is obtained by determining the position of each feature point on the battery pack in the actual battery pack top-pressure test based on the determined feature points, and setting measuring instruments at the positions of each feature point to monitor the corresponding feature points.

[0022] The technical effects and principles of this solution: By selecting the most representative feature points, the system focuses on the key parts of the battery pack, rather than all the details of the entire structure. This significantly reduces the amount of data to be processed and improves analysis efficiency. Focusing on only a small number of feature points makes data analysis more efficient and avoids the complexity brought by massive amounts of data.

[0023] By comparing simulated and real data of feature points under the same loading stage, the accuracy of the simulation can be evaluated more intuitively. If the two are highly consistent, it indicates that the simulation model has a high predictive ability. When discrepancies are found between the simulation results and the real data, they can be quickly corrected by adjusting the finite element model parameters near the feature points, without having to reanalyze the entire model.

[0024] The selection of feature points allows the system to perform "magnifying glass"-like analysis on critical areas, capturing subtle changes and providing more reliable verification evidence. Detailed analysis of feature points can identify potential safety hazards in advance, enabling preventative measures to be taken and ensuring product safety and reliability.

[0025] The process of determining and marking feature points is relatively simple, and users do not need complex finite element modeling knowledge to complete it. At the same time, the setting of measuring instruments in real experiments is also quite intuitive and easy to operate.

[0026] Compared to existing model correction methods that analyze large amounts of global data, this approach only requires focusing on a small number of feature points, reducing data processing workload. Focusing on key areas improves the accuracy and reliability of the analysis. Correcting the model near feature points allows for faster iterative optimization and shortens the development cycle.

[0027] Furthermore, S5 includes:

[0028] S50. Based on the corresponding simulation result data and actual test result data, compare and calculate the simulated feature point data and actual feature point data of each feature point under each loading stage, and calculate the error data corresponding to each feature point under each loading stage; the error data includes the stress error, strain error and displacement error corresponding to the feature point;

[0029] S51. Based on the stress error, strain error, and displacement error corresponding to each feature point under each loading stage, determine whether the corresponding simulation result data is reasonable. If so, extract the corresponding feature parameters based on the corresponding simulation result data and generate the corresponding simulation report. If not, determine the correction type corresponding to each feature point.

[0030] S52. Based on the correction type corresponding to each determined feature point, correct each feature point.

[0031] S53. After completing the correction of each feature point, adjust each finite element model, and re-execute S3 based on the adjusted finite element models.

[0032] Beneficial effects: In this approach, detailed error data analysis accurately identifies the differences between simulation results and actual experimental results, ensuring that each correction is a precise adjustment based on the actual problem. Through multiple iterations, the finite element model is gradually optimized until the simulation results highly match the actual experimental results, ensuring that the final simulation model has high predictive capability.

[0033] Comprehensive verification is performed across multiple dimensions, including stress, strain, and displacement, to ensure the comprehensiveness and accuracy of the simulation results. Detailed analysis of feature points allows for the early identification of potential safety hazards, enabling preventative measures to be taken and ensuring product safety and reliability.

[0034] Based on the error characteristics of feature points, the most suitable correction method is selected, avoiding blind adjustments to the entire model and improving correction efficiency. The system can achieve automated simulation and data analysis based on feature points, reducing the need for manual intervention and improving work efficiency. Simulation and real-world testing can be conducted in parallel, shortening the entire R&D cycle and further improving work efficiency.

[0035] Furthermore, the correction types include model material correction, model geometry correction, test boundary and load correction, and model contact surface correction.

[0036] Beneficial effects: By selecting the most suitable correction method for different error characteristics, the entire model can be adjusted blindly, thus improving correction efficiency.

[0037] Furthermore, S52 includes:

[0038] When the correction type corresponding to a certain feature point is model material correction, the material parameter report provided by the material supplier of the material corresponding to the feature point and the mechanical property test results of the material are retrieved, and the material parameters of the part or region where the feature point is located are adjusted. The material parameters include the material elastic modulus and Poisson's ratio.

[0039] When the correction type corresponding to a certain feature point is model geometry correction, the design drawings and measurement data corresponding to the battery pack are retrieved, and the geometric correction is performed on the part or area where the feature point is located based on the design drawings and measurement data of the battery pack.

[0040] When the correction type corresponding to a certain feature point is test boundary and load correction, the boundary conditions and load distribution in the battery pack top pressure simulation test are adjusted according to the actual applied force and boundary conditions in the actual battery pack top pressure test.

[0041] When the correction type corresponding to a certain feature point is model contact surface correction, the contact conditions in the actual battery pack top pressure test are redefined and updated synchronously in the battery pack top pressure simulation test.

[0042] Beneficial Effects: In this scheme, by precisely adjusting material properties, the simulation results more closely approximate the behavior of actual materials, improving simulation accuracy. It provides engineers with more accurate material selection criteria, avoiding design flaws caused by improper material selection. Ensuring material parameters are consistent with actual conditions enhances the reliability of simulation results. Geometric correction more accurately captures subtle changes in the battery pack under top pressure, improving the credibility of simulation results. Precisely defining the contact surface allows the simulation to more realistically reflect the mechanical behavior of the contact surface, improving the reliability of simulation results. Through multi-dimensional comprehensive verification, it ensures that the simulation results are not only accurate in a single parameter but also comprehensively reflect the mechanical behavior of the battery pack under top pressure. This multi-dimensional approach involves not only diverse correction types but also diverse correction strategies, greatly improving simulation accuracy.

[0043] Furthermore, the correction type also includes mesh partitioning correction;

[0044] S52 further includes:

[0045] When the correction type corresponding to a certain feature point is mesh partitioning correction, the mesh is refined based on the location or region where the feature point is located.

[0046] Beneficial Effects: When the correction type corresponding to a feature point is mesh refinement, the mesh is refined based on the location or region where the feature point is located. Mesh refinement increases the number of elements in a local area, thereby improving the simulation accuracy of that area. Through mesh refinement, subtle changes in the location or region of the feature point, such as stress concentration and crack propagation, can be captured more accurately. This helps to identify potential problems and improve simulation accuracy. Mesh refinement makes stress distribution more detailed, especially in areas with complex geometries or significant variations in material properties, providing more accurate stress analysis results. The refined mesh more realistically reflects the behavior of the actual structure, reducing simulation errors caused by overly coarse meshes and enhancing the reliability of simulation results. By refining the mesh only in specific regions, rather than the entire model, computational resources are saved, and simulation efficiency is improved. This allows for shorter simulation times and improved R&D efficiency while maintaining accuracy.

[0047] The present invention also provides a power battery pack top-pressure simulation test system, which uses the above-described power battery pack top-pressure simulation method. Attached Figure Description

[0048] Figure 1 This is a flowchart of the power battery pack top-pressure simulation method in Embodiment 1 of the present invention;

[0049] Figure 2 This is a schematic diagram of the battery pack model and support platform model in Embodiment 1 of the present invention;

[0050] Figure 3 This is a schematic diagram of the battery pack model, support platform model, and top pressure device model in Embodiment 1 of the present invention;

[0051] Figure 4 This is a shape diagram of the extrusion head in Embodiment 1 of the present invention. Detailed Implementation

[0052] The following detailed description illustrates the specific implementation method:

[0053] Example 1

[0054] A simulation method for top-voltage operation of a power battery pack, basically as follows: Figure 1 , Figure 2 , Figure 3 As shown, it includes the following steps:

[0055] S1. Based on the battery pack, the pressure-pressing device, and the support platform, construct corresponding battery pack models, pressure-pressing device models, and support platform models. In this embodiment, the support platform model is used to simulate the support conditions of the battery pack during the pressure-pressing test. The support platform model should match the battery pack model and be able to simulate the support effect in actual testing.

[0056] S2. Based on the constructed battery pack model, top-pressing device model, and support platform model, the corresponding finite element models are built to form the corresponding battery pack finite element models, top-pressing device finite element models, and support platform finite element models. In this embodiment, the establishment of the corresponding finite element models is based on the actual dimensions and material data of the battery pack, as well as the design parameters of the top-pressing device. Simultaneously, the parameters of the extrusion head corresponding to the extrusion head of the top-pressing device are set. For example, a hemispherical extrusion head with a radius of 100mm is set to extrude the center of the battery pack at a speed of 10m / s. Figure 4 As shown, the extrusion head can be spherical, rectangular, etc., and can also be loaded using a time-displacement curve.

[0057] In this embodiment, the explicit method of central difference time integration is used to calculate the end time t of each node of the structural system at the nth time step. n The acceleration vector is:

[0058]

[0059] In the formula, P is the applied external force vector: F int The internal force vector consists of the following components:

[0060]

[0061] The nodal velocity and displacement vector are calculated using the following two equations:

[0062] v(t n+1 / 2 )=v(t n-1 / 2 )+0.5a(t n )(Δt n-1 +Δt n )

[0063] u(t n+1 )=u(t n )+v(t n+1 / 2 )Δt n

[0064] The definitions of time step and time point are as follows:

[0065] Δt n-1 =(t n -t n-1 ),Δt n =(t n+1 -t n )

[0066] t n-1 / 2 =0.5(t) n +t n-1 ),t n+1 / 2 =0.5(t) n+1 +t n )

[0067] The new geometry is obtained by adding the displacement increment to the initial geometry x0:

[0068] x t+Δt =x0+u t+Δt

[0069] S3. Retrieve the test data and actual test results data corresponding to the actual battery pack top pressure test from the database; Based on the test data corresponding to the actual battery pack top pressure test, the finite element model of the battery pack, the finite element model of the top pressure device, and the finite element model of the support platform, set up the corresponding battery pack top pressure simulation test.

[0070] S4. Based on the battery pack top pressure simulation test, output the corresponding simulation result data;

[0071] S4 includes the following steps:

[0072] S40. Based on the structural characteristics and key mechanical response parts of the battery pack, determine the most representative feature points of the battery pack, and mark the determined feature points on the finite element model of the battery pack in the top pressure simulation test. In this embodiment, feature points can be selected such as apex corners, midpoints of edges, connection points between the main internal support structures and the outer shell, etc., to ensure that the mechanical data of these points can reflect the overall deformation and stress distribution of the battery pack, and that the number of these points is appropriate.

[0073] S41. After determining and marking the corresponding feature points, conduct a corresponding battery pack top-pressure simulation test under the same top-pressure conditions as the actual battery pack top-pressure test. During the battery pack top-pressure simulation test and the actual battery pack top-pressure test, extract the simulation feature point data and actual feature point data corresponding to each feature point under each of the same loading stages, and form their respective simulation result data and actual test result data. The actual test result data is obtained by determining the position of each feature point on the battery pack in the actual battery pack top-pressure test based on the determined feature points, and setting up measuring instruments at the locations of each feature point to monitor the corresponding feature points. At the selected feature point locations, use high-precision strain gauges, displacement sensors, and other measuring instruments to collect the strain values ​​and displacement values ​​of the feature points in the corresponding actual test process, and record the stress change data during the loading process. This can be obtained by arranging miniature pressure sensors near the feature points or by using strain rosette conversion.

[0074] In this embodiment, the simulation test must be consistent with the top pressure conditions corresponding to the real test, that is, the corresponding loading force, loading rate and loading method must be consistent with the real test.

[0075] S5. Based on the simulation results and actual experimental results, determine whether the corresponding simulation results are reasonable. If so, extract the corresponding feature parameters and generate a simulation report. If not, correct each finite element model and re-execute S3 after correction. Continue implementing corresponding model correction measures based on the new error conditions, continuously adjusting model parameters and mesh quality. After each correction, closely monitor the error trends of key feature points, gradually reducing the error values ​​until the stress, strain, and displacement errors of all feature points meet the preset accuracy requirements (e.g., relative stress error controlled within ±10%, absolute displacement error within ±0.5mm, etc.), ensuring that the mechanical response of the model at key locations highly matches the experimental results. After completing the model correction and meeting the accuracy requirements, perform simulation calculations for multiple sets of different top-pressure conditions (including changes in loading force, loading path, loading speed, etc.) and comprehensively compare and verify with the experimental data under the corresponding conditions. In addition to checking the consistency of feature point data, it is also necessary to compare and analyze the overall mechanical performance indicators of the battery pack (such as overall deformation trend, stiffness variation curve, energy absorption characteristics, etc.) to ensure that the model can accurately and reliably simulate the top pressure behavior of the battery pack under various possible operating conditions, providing a precise and effective simulation tool for battery pack design optimization and safety assessment. The feature parameters extracted in this embodiment include stress-strain, intrusion amount, and the magnitude of the top pressure.

[0076] S5 includes:

[0077] S50. Based on the corresponding simulation results and actual experimental results, the simulated feature point data and actual feature point data for each feature point at each loading stage are compared and calculated to obtain the error data corresponding to each feature point at each loading stage. The error data includes the stress error, strain error, and displacement error corresponding to the feature point. The stress error is obtained by subtracting the simulated stress value from the experimental stress value and then dividing by the experimental stress value. In this embodiment, to make the corresponding error data more intuitive, the error data of all feature points are organized, and error distribution curves or charts are plotted to intuitively show the deviation of the model at different positions and loading stages, thereby identifying the key feature points with large errors and their corresponding error types.

[0078] S51. Based on the stress error, strain error, and displacement error corresponding to each feature point under each loading stage, determine whether the corresponding simulation result data is reasonable. If so, extract the corresponding feature parameters based on the corresponding simulation result data and generate the corresponding simulation report. If not, determine the correction type corresponding to each feature point.

[0079] S52. Based on the correction type corresponding to each determined feature point, correct each feature point; the correction type includes model material correction, model geometry correction, test boundary and load correction, model contact surface correction, and mesh generation correction.

[0080] S52 includes:

[0081] When the correction type corresponding to a certain feature point is model material correction, the material parameter report provided by the material supplier of the material corresponding to the feature point and the mechanical property test results of the material are retrieved. The material parameters of the part or region where the feature point is located are adjusted. The material parameters include the material elastic modulus and Poisson's ratio. For example, if the stress error exceeds the standard due to the inaccurate setting of the material elastic modulus at a certain feature point, the detailed material parameter report provided by the material supplier or the relevant material performance database is consulted. Combined with the mechanical property test results of the material sample, such as tensile and compressive tests, the material elastic modulus, Poisson's ratio, yield strength and hardening model parameters of the part or region where the feature point is located are appropriately fine-tuned (e.g., the elastic modulus is adjusted by ±5% each time, and the adjustment direction and magnitude are determined according to the error change trend).

[0082] When the correction type corresponding to a certain feature point is model geometry correction, the design drawings and measurement data corresponding to the battery pack are retrieved. Based on the design drawings and measurement data of the battery pack, the geometric correction is performed on the part or area where the feature point is located. If there is an error in the thickness of the support beam where a certain feature point is located during modeling, the geometric dimension parameters of that part in the model are corrected according to the actual battery pack design drawings and measurement data, the simulation calculation is re-performed, and the change of feature point error is observed.

[0083] When the correction type corresponding to a certain feature point is test boundary and load correction, the boundary conditions and load distribution in the battery pack top pressure simulation test are adjusted according to the actual applied force and boundary conditions in the actual battery pack top pressure test; for example, the actual contact surface of the battery pack may be different, resulting in the load transfer and distribution method being inconsistent with the simulation assumption.

[0084] When the correction type corresponding to a certain feature point is model contact surface correction, the contact conditions in the actual battery pack top-pressure test are redefined and simultaneously updated in the battery pack top-pressure simulation test. In the simulation, the contact surface usually affects load transfer and material deformation behavior. In actual tests, the contact conditions may be different, so it is necessary to redefine the contact model, taking into account factors such as friction and contact stiffness.

[0085] When the correction type corresponding to a feature point is mesh refinement, the mesh is refined based on the location or region where the feature point is located. For example, if the feature point is located in a region with drastic changes in mesh density or an irregular mesh shape, leading to stress concentration or decreased calculation accuracy, the mesh in the region where the feature point is located is refined by using a more reasonable meshing algorithm (such as changing from free meshing to mapped meshing) to make the mesh distribution more uniform and conform to the mechanical properties of the structure, while controlling the increase in the overall mesh count.

[0086] S53. After completing the correction of each feature point, adjust each model and re-execute S3 based on the adjusted models.

[0087] This embodiment also discloses a power battery pack top-pressure simulation test system, which uses the above-described power battery pack top-pressure simulation method.

[0088] The above descriptions are merely embodiments of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, based on the guidance provided in this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for simulating the top voltage of a power battery pack, characterized in that: Includes the following steps: S1. Based on the battery pack, the top pressure device, and the support platform, construct the corresponding battery pack model, top pressure device model, and support platform model; S2. Based on the constructed battery pack model, top pressure device model, and support platform model, build the corresponding finite element models for each model to form the corresponding battery pack finite element model, top pressure device finite element model, and support platform finite element model. S3. Based on the finite element model of the battery pack, the finite element model of the top pressure device, and the finite element model of the support platform, set up the corresponding battery pack top pressure simulation test; Under the same top-pressure conditions as the actual top-pressure test of the battery pack, the battery pack top-pressure simulation test and the actual top-pressure test of the battery pack are carried out simultaneously, and the test data and actual test result data of the actual test are obtained. S4. Based on the battery pack top pressure simulation test, output the corresponding simulation result data; S5. Based on the simulation results data and the actual experimental results data, determine whether the corresponding simulation results data is reasonable. If so, extract the corresponding feature parameters based on the corresponding simulation results data and generate the corresponding simulation report. If not, the finite element model of the battery pack is modified, and S3 is executed again after the modification is completed; S4 includes the following steps: S40. Based on the structural characteristics and key mechanical response parts of the battery pack, determine the most representative feature points of the battery pack, and mark the determined feature points on the finite element model of the battery pack in the top pressure simulation test. S41. After determining and marking the corresponding feature points, conduct a corresponding battery pack top-pressure simulation test under the same top-pressure conditions as the actual battery pack top-pressure test. During the battery pack top-pressure simulation test and the actual battery pack top-pressure test, extract the simulation feature point data and actual feature point data corresponding to each feature point under each of the same loading stages, and form their respective simulation result data and actual test result data. The actual test result data is obtained by determining the position of each feature point on the battery pack in the actual battery pack top-pressure test based on the determined feature points, and setting measuring instruments at the positions of each feature point to monitor the corresponding feature points.

2. The power battery pack top-voltage simulation method according to claim 1, characterized in that: S5 includes: S50. Based on the corresponding simulation result data and real test result data, compare and calculate the simulated feature point data and real feature point data of each feature point under each loading stage, and calculate the error data corresponding to each feature point under each loading stage; the error data includes the stress error, strain error and displacement error corresponding to the feature point; S51. Based on the stress error, strain error, and displacement error corresponding to each feature point under each loading stage, determine whether the corresponding simulation result data is reasonable. If so, extract the corresponding feature parameters based on the corresponding simulation result data and generate the corresponding simulation report. If not, determine the correction type corresponding to each feature point. S52. Based on the correction type corresponding to each determined feature point, correct each feature point. S53. After completing the correction of each feature point, adjust each model and re-execute S3 based on the adjusted models.

3. The power battery pack top-voltage simulation method according to claim 2, characterized in that: The correction types include model material correction, model geometry correction, test boundary and load correction, and model contact surface correction.

4. The power battery pack top-voltage simulation method according to claim 3, characterized in that: S52 includes: When the correction type corresponding to a certain feature point is model material correction, the material parameter report provided by the material supplier of the material corresponding to the feature point and the mechanical property test results of the material are retrieved, and the material parameters of the part or region where the feature point is located are adjusted. The material parameters include the material elastic modulus and Poisson's ratio. When the correction type corresponding to a certain feature point is model geometry correction, the design drawings and measurement data corresponding to the battery pack are retrieved, and the geometric correction is performed on the part or area where the feature point is located based on the design drawings and measurement data of the battery pack. When the correction type corresponding to a certain feature point is test boundary and load correction, the boundary conditions and load distribution in the battery pack top pressure simulation test are adjusted according to the actual applied force and boundary conditions in the actual battery pack top pressure test. When the correction type corresponding to a certain feature point is model contact surface correction, the contact conditions in the actual battery pack top pressure test are redefined and updated synchronously in the battery pack top pressure simulation test.

5. The power battery pack top-voltage simulation method according to claim 4, characterized in that: The correction type also includes grid partitioning correction; S52 further includes: When the correction type corresponding to a certain feature point is mesh partitioning correction, the mesh is refined based on the location or region where the feature point is located.

6. A power battery pack top-voltage simulation test system, characterized in that: A power battery pack top pressure simulation method using any one of claims 1 to 5.

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