Battery pack vibration test method and platform

Abstract

The invention discloses a battery pack vibration test method and platform, and relates to the vibration test related field, and the method comprises the steps: collecting a plurality of vibration scenes, and collecting scene vibration parameters; performing vibration scene retrieval to obtain a plurality of scene occurrence rates, and performing vibration analogue simulation restoration; setting a plurality of test times, and performing vibration test on the battery pack; performing vibration analysis and fusion on the plurality of image vibration acquisition result sets and the plurality of circuit vibration acquisition result sets; performing distribution analysis on the plurality of vibration test analysis result sets to obtain a plurality of test volatility parameters, and performing compensation processing on the plurality of fused vibration test analysis results; and configuring a plurality of scene weights, and carrying out weighted calculation on the plurality of vibration danger levels. The technical problem that the evaluation result of an existing battery pack vibration test is not comprehensive and accurate enough is solved, and the technical effect of improving the comprehensiveness and accuracy of the evaluation result of the vibration test is achieved.

Description

Technical Field

[0001] The present application relates to the field related to vibration testing, and in particular to a battery pack vibration testing method and platform. Background Art

[0002] With the rapid development of electric vehicles and renewable energy storage systems, the safety and reliability of battery packs as their core components are receiving more and more attention. During the use of battery packs, vibration is an environmental factor that cannot be ignored, which may cause damage to the internal structure of the battery pack, loose connections, and even cause serious problems such as short circuits and fires. Therefore, vibration testing of battery packs and evaluating their performance in various vibration scenarios have become important means to ensure the safety and reliability of battery packs. In existing battery pack vibration tests, the method commonly used is based on a single vibration scenario or a preset vibration spectrum. Although this method can evaluate the vibration performance of the battery pack to a certain extent, the analysis of the vibration test results usually stays on the surface and lacks the ability to deeply mine and integrate vibration data, resulting in the vibration test evaluation results being not comprehensive and accurate.

[0003] In the current relevant technologies, battery pack vibration testing has the technical problem that the evaluation results are not comprehensive and accurate enough. Summary of the invention

[0004] The present application provides a battery pack vibration testing method and platform, which collects multiple vibration scenarios and vibration parameters of the battery pack during assembly and operation, performs vibration scenario retrieval and simulation restoration, obtains multiple simulated vibration test scenarios and scenario simulation degrees, sets the number of tests according to the scenario occurrence rate and simulation degree, performs vibration testing, collects image and circuit vibration data, analyzes and fuses the vibration data, obtains vibration test analysis results and fused vibration test analysis results, configures scenario weights according to scenario occurrence rate, simulation degree and test volatility parameters, performs weighted calculation on vibration hazard levels, obtains vibration test results of the battery pack, and other technical means, comprehensively collects and analyzes the performance of the battery pack in different vibration scenarios, and achieves the technical effect of improving the comprehensiveness and accuracy of vibration test evaluation results by deeply mining and fusing vibration data.

[0005] The present application provides a battery pack vibration test method, comprising: Collect multiple vibration scenarios during the assembly and operation of the battery pack, and collect scenario vibration parameters in the multiple vibration scenarios, wherein each scenario vibration parameter includes vibration parameters of the X-axis, Y-axis and Z-axis; perform vibration scenario retrieval according to the multiple scenario vibration parameters, obtain multiple scenario occurrence rates of the multiple vibration scenarios, and perform vibration simulation restoration according to the multiple scenario vibration parameters to obtain multiple simulated vibration test scenarios and multiple scenario simulation degrees; set multiple test times for the multiple simulated vibration test scenarios according to the multiple scene occurrence rates and the multiple scene simulation degrees, perform vibration tests on the battery pack in the multiple simulated vibration test scenarios according to the multiple test times, and obtain multiple image vibration collection result sets and multiple electric a set of road vibration collection results; according to the occurrence rates of the multiple scenes and the simulation degrees of the multiple scenes, performing vibration analysis and fusion on the multiple image vibration collection result sets and the multiple circuit vibration collection result sets to obtain multiple vibration test analysis result sets and multiple fused vibration test analysis results; performing distribution analysis on the multiple vibration test analysis result sets respectively to obtain multiple test volatility parameters, and performing compensation processing on the multiple fused vibration test analysis results in combination with the simulation degrees of the multiple scenes to obtain multiple vibration hazard levels; according to the occurrence rates of the multiple scenes, the simulation degrees of the multiple scenes and the multiple test volatility parameters, configuring multiple scene weights, performing weighted calculation on the multiple vibration hazard levels, and obtaining the vibration test result of the battery pack.

[0006] In a possible implementation, vibration scene retrieval is performed according to multiple scene vibration parameters, multiple scene occurrence rates of the multiple vibration scenes are obtained, and vibration simulation restoration is performed according to the multiple scene vibration parameters to obtain multiple simulated vibration test scenes and multiple scene simulation degrees, and the following processing is performed: Based on historical vibration scenes collected in historical time, a vibration scene database is constructed; a search is performed in the vibration scene database according to multiple scene vibration parameters to obtain multiple scene occurrence rates; vibration simulation and restoration are performed according to the multiple scene vibration parameters to obtain multiple simulated vibration test scenes; the difference amplitudes between the simulated vibration parameters in the multiple simulated vibration test scenes and the vibration parameters of multiple scenes are calculated to obtain multiple scene simulation degrees.

[0007] In a possible implementation, according to the occurrence rates of the multiple scenarios and the simulation degrees of the multiple scenarios, multiple test times of the multiple simulated vibration test scenarios are set, and the battery pack is subjected to vibration testing according to the multiple test times under the multiple simulated vibration test scenarios, and the following processing is performed: Obtain a preset number of tests; calculate an average scene occurrence rate and an average scene simulation degree according to the multiple scene occurrence rates and the multiple scene simulation degrees; allocate and calculate multiple test ratios according to the ratios of each corresponding scene occurrence rate and each scene simulation degree to the average scene occurrence rate and the average scene simulation degree; perform correction calculations on the preset number of tests according to the multiple test ratios to obtain multiple test times; perform vibration tests on the battery pack in the multiple simulated vibration test scenarios according to the multiple test times, and after the tests are completed, perform image acquisition and circuit information acquisition on the battery pack to obtain multiple image vibration acquisition result sets and multiple circuit vibration acquisition result sets.

[0008] In a possible implementation, according to the occurrence rates of the multiple scenes and the simulation degrees of the multiple scenes, vibration analysis and fusion are performed on the multiple image vibration collection result sets and the multiple circuit vibration collection result sets, and the following processing is performed: A vibration analysis channel is constructed and embedded in a vibration test platform, wherein the vibration analysis channel includes an image vibration analysis path and a circuit vibration analysis path, wherein the image vibration analysis path and the circuit vibration analysis path respectively include P image vibration analysis branches and P circuit vibration analysis branches, where P is an integer greater than 1; according to the occurrence rates of the multiple scenes and the simulation degrees of the multiple scenes, a plurality of analysis branch numbers are calculated and set, wherein the scene occurrence rates are positively correlated with the number of analysis branches, and the scene simulation degrees are positively correlated with the number of analysis branches; the plurality of image vibration acquisition result sets and the plurality of circuit vibration acquisition result sets are respectively input into the image vibration analysis branches and the circuit vibration analysis branches within the plurality of analysis branch numbers for analysis, and a plurality of image vibration analysis result sets and a plurality of circuit vibration analysis result sets are obtained through majority voting processing, wherein both the image vibration analysis results and the circuit vibration analysis results include battery pack damage levels; weighted calculations are performed on the plurality of image vibration analysis result sets and the plurality of circuit vibration analysis result sets to obtain a plurality of vibration test analysis result sets; and the mean of the plurality of vibration test analysis result sets is calculated to obtain a plurality of fused vibration test analysis results.

[0009] In a possible implementation, a vibration analysis channel is constructed to perform the following processing: According to the historical data of battery pack vibration test, a sample image vibration collection result set, a sample circuit vibration collection result set and a sample vibration analysis result set are collected, and combined to obtain image vibration analysis training data and circuit vibration analysis training data; 40%-60% of the data are randomly selected from the image vibration analysis training data to train the first image vibration analysis branch in the image vibration analysis path; 40%-60% of the data are randomly selected from the image vibration analysis training data again to train the second image vibration analysis branch in the image vibration analysis path; continue training to obtain P image vibration analysis branches and obtain an image vibration analysis path; according to the circuit vibration analysis training data, train to obtain P circuit vibration analysis branches and obtain a circuit vibration analysis path.

[0010] In a possible implementation, distribution analysis is performed on the multiple vibration test analysis result sets respectively to obtain multiple test volatility parameters, and compensation processing is performed on the multiple fused vibration test analysis results in combination with the multiple scene simulation degrees, and the following processing is performed: Perform distribution discreteness analysis on the multiple vibration test analysis result sets respectively to obtain multiple test volatility parameters; calculate and obtain multiple scenario compensation coefficients based on the multiple scenario simulation degrees, and calculate and obtain multiple compensation coefficients in combination with the multiple test volatility parameters; use the multiple compensation coefficients to perform compensation calculation processing on the multiple fused vibration test analysis results to obtain multiple vibration hazard levels.

[0011] In a possible implementation, multiple scene weights are configured according to the multiple scene occurrence rates, multiple scene simulation degrees and multiple test volatility parameters, the multiple vibration hazard levels are weightedly calculated, the vibration test results of the battery pack are obtained, and the following processing is performed: According to the occurrence rates of the multiple scenes, multiple occurrence rate weights are allocated and calculated, wherein the size of the scene occurrence rate is positively correlated with the size of the occurrence rate weight; according to the simulation degrees of the multiple scenes, multiple simulation weights are allocated and calculated, wherein the size of the scene simulation degree is positively correlated with the size of the simulation weight; according to the multiple test volatility parameters, multiple test weights are allocated and calculated, wherein the size of the test volatility parameter is negatively correlated with the size of the test weight; according to the multiple occurrence rate weights, multiple simulation weights and multiple test weights, a weight normalization calculation configuration is performed to obtain multiple scene weights, and the multiple vibration hazard levels are weightedly calculated to obtain the vibration test results of the battery pack.

[0012] The present application also provides a battery pack vibration test platform, comprising: A scene vibration parameter acquisition module, the scene vibration parameter acquisition module is used to acquire multiple vibration scenes during the assembly and operation of the battery pack, and acquire scene vibration parameters in the multiple vibration scenes, wherein each scene vibration parameter includes vibration parameters of the X-axis, Y-axis and Z-axis; a vibration simulation and restoration module, the vibration simulation and restoration module is used to perform vibration scene retrieval according to the multiple scene vibration parameters, obtain multiple scene occurrence rates of the multiple vibration scenes, and perform vibration simulation and restoration according to the multiple scene vibration parameters to obtain multiple simulated vibration test scenes and multiple scene simulation degrees; a vibration test module, the vibration test module is used to set multiple test times for the multiple simulated vibration test scenes according to the multiple scene occurrence rates and the multiple scene simulation degrees, perform vibration tests on the battery pack according to the multiple test times under the multiple simulated vibration test scenes, and obtain multiple image vibration acquisition result sets and multiple A circuit vibration collection result set; a vibration analysis and fusion module, the vibration analysis and fusion module is used to perform vibration analysis and fusion on the multiple image vibration collection result sets and the multiple circuit vibration collection result sets according to the multiple scene occurrence rates and the multiple scene simulation degrees, so as to obtain multiple vibration test analysis result sets and multiple fused vibration test analysis results; a compensation processing module, the compensation processing module is used to perform distribution analysis on the multiple vibration test analysis result sets respectively, obtain multiple test volatility parameters, and perform compensation processing on the multiple fused vibration test analysis results in combination with the multiple scene simulation degrees to obtain multiple vibration hazard levels; a vibration test result acquisition module, the vibration test result acquisition module is used to configure multiple scene weights according to the multiple scene occurrence rates, the multiple scene simulation degrees and the multiple test volatility parameters, perform weighted calculation on the multiple vibration hazard levels, and obtain the vibration test result of the battery pack.

[0013] A battery pack vibration testing method and platform proposed in the present application first collects multiple vibration scenes during the assembly and operation of the battery pack, and collects scene vibration parameters in the multiple vibration scenes, wherein each scene vibration parameter includes vibration parameters of the X-axis, Y-axis and Z-axis, and then performs vibration scene retrieval based on the multiple scene vibration parameters to obtain multiple scene occurrence rates of the multiple vibration scenes, and performs vibration simulation restoration based on the multiple scene vibration parameters to obtain multiple simulated vibration test scenes and multiple scene simulation degrees, and then sets multiple test times for multiple simulated vibration test scenes based on the multiple scene occurrence rates and the multiple scene simulation degrees, and performs vibration tests on the battery pack according to multiple test times in multiple simulated vibration test scenes to obtain multiple image vibration acquisition result sets and multiple circuits. A set of vibration collection results is obtained, and then according to the occurrence rates of multiple scenes and the simulation degrees of multiple scenes, vibration analysis and fusion are performed on multiple image vibration collection result sets and multiple circuit vibration collection result sets to obtain multiple vibration test analysis result sets and multiple fused vibration test analysis results. Then, distribution analysis is performed on the multiple vibration test analysis result sets respectively to obtain multiple test volatility parameters. Combined with the simulation degrees of multiple scenes, compensation processing is performed on the multiple fused vibration test analysis results to obtain multiple vibration hazard levels. Finally, according to the occurrence rates of multiple scenes, the simulation degrees of multiple scenes and the test volatility parameters, multiple scene weights are configured, and weighted calculation is performed on multiple vibration hazard levels to obtain the vibration test results of the battery pack, thereby achieving the technical effect of improving the comprehensiveness and accuracy of the vibration test evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention are briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the platform according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic flow chart of a battery pack vibration testing method provided in an embodiment of the present application.

[0016] Figure 2 A schematic structural diagram of a battery pack vibration test platform provided in an embodiment of the present application.

[0017] Explanation of the reference numerals: scene vibration parameter acquisition module 10 , vibration simulation and restoration module 20 , vibration test module 30 , vibration analysis and fusion module 40 , compensation processing module 50 , vibration test result acquisition module 60 . DETAILED DESCRIPTION

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0019] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0020] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, platform, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0021] The present application embodiment provides a battery pack vibration test method, such as Figure 1 As shown, the method includes: Step S100, collect multiple vibration scenarios during the assembly and operation of the battery pack, and collect scenario vibration parameters within the multiple vibration scenarios, wherein each scenario vibration parameter includes vibration parameters of the X-axis, Y-axis and Z-axis. Specifically, determine the various operating environments that the battery pack may face after being assembled, that is, vibration scenarios, such as different road conditions (highways, mountain roads, bumpy roads, etc.), different speeds, different load conditions, etc. Install corresponding test equipment and vibration sensors to collect vibration data of the battery pack in different vibration scenarios. The sensor should be able to simultaneously measure the vibration of the X-axis (horizontal lateral), Y-axis (horizontal longitudinal) and Z-axis (vertical direction). In the test environment, start the test equipment and record the vibration data of the battery pack in different scenarios, such as frequency, amplitude, phase, etc., wherein the scenarios may include smooth driving, rapid acceleration, rapid deceleration, turning, passing uneven roads, etc. Repeat the above process to ensure that sufficient vibration data is collected in each test environment for subsequent analysis.

[0022] Step S200, according to multiple scene vibration parameters, perform vibration scene retrieval, obtain multiple scene occurrence rates of the multiple vibration scenes, and perform vibration simulation restoration according to the multiple scene vibration parameters to obtain multiple simulated vibration test scenes and multiple scene simulation degrees. Specifically, vibration data is collected from the historical data set of battery pack assembly operation, which can be derived from past tests, actual operation records or simulation experiments, and the collected historical data is sorted, including removing duplicates, correcting erroneous data, standardizing formats, etc., to ensure the consistency and accuracy of the data. According to the vibration characteristics (such as frequency, amplitude, duration, etc.) in the historical data, cluster analysis, pattern recognition and other methods are used to retrieve and classify the vibration scenes. These characteristics reflect different operating conditions or environmental factors, such as different road conditions, different speeds, different loads, etc., and each classified vibration scene is assigned a unique identifier for subsequent reference and analysis. The number of occurrences of each classified vibration scene in the historical data set is counted, and the occurrence rate of each vibration scene is calculated, that is, the proportion of the number of occurrences of the vibration scene to the total number of occurrences of all vibration scenes. This proportion reflects the relative frequency or importance of the vibration scene in actual operation.

[0023] According to the collected scene vibration parameters (vibration data of X-axis, Y-axis, and Z-axis) in multiple vibration scenarios, a vibration simulation model is established. The vibration simulation model is used to simulate the vibration behavior of the battery pack in different vibration scenarios. Parameters corresponding to the actual vibration scenario are set in the vibration simulation model, and the simulation program is run to restore each vibration scenario. The simulation degree is evaluated for each simulated vibration test scenario. The simulation degree refers to the accuracy of the vibration simulation model in simulating the actual vibration scenario. According to the comparison between the simulation results and the actual data, a simulation degree value is assigned to each simulated vibration test scenario. This value can be a quantitative indicator (such as a similarity coefficient) or a qualitative description (such as "high simulation degree", "medium simulation degree", etc.).

[0024] In a possible implementation, according to multiple scene vibration parameters, vibration scene retrieval is performed to obtain multiple scene occurrence rates of the multiple vibration scenes, and vibration simulation restoration is performed according to the multiple scene vibration parameters to obtain multiple simulated vibration test scenes and multiple scene simulation degrees. Step S200 further includes step S210, based on the historical vibration scenes collected in the historical time, a vibration scene database is constructed. Specifically, vibration data is collected from the vibration monitoring system in the historical time period (such as the past few years, months or weeks), and these data come from different types of equipment, battery packs in different locations or under different operating conditions. The collected data is cleaned to remove noise, outliers, duplicate data, etc. to ensure the accuracy and consistency of the data. Feature parameters of the vibration scene, such as frequency, amplitude, duration, phase, etc., are extracted from the cleaned data, and the vibration scene is classified according to the feature parameters, and a unique identifier or label is assigned to each classified scene, and the classified and marked vibration scene data is stored in the vibration scene database. Step S220, according to the multiple scene vibration parameters, the vibration scene database is searched to obtain multiple scene occurrence rates. Specifically, multiple scene vibration parameters to be retrieved are input, and retrieval algorithms (such as similarity matching, distance measurement, etc.) are applied to search for scenes matching the input parameters in the vibration scene database. The number of occurrences of each matching scene is counted, and its occurrence rate (i.e., the proportion of the number of occurrences of the scene to the total number of occurrences of the scene) is calculated. The scene occurrence rate refers to the frequency or proportion of a vibration scene in the historical data set.

[0025] Step S230, perform vibration simulation and restoration according to the vibration parameters of the multiple scenarios to obtain multiple simulated vibration test scenarios. Specifically, a simulation model is constructed according to the physical properties and vibration characteristics of the battery pack, and the simulation model can simulate the dynamic response of the battery pack under different vibration scenarios. Set multiple scenario vibration parameters (such as frequency, amplitude, etc.) as input conditions of the simulation model, run the simulation model, simulate the vibration behavior of the battery pack under the set vibration parameters, and output simulation results, including time series data of the simulated vibration test scenario, vibration waveform diagram, etc., wherein the simulated vibration test scenario is a virtual vibration scenario obtained through simulation, which is used to evaluate the performance of the battery pack under different vibration conditions. Step S240, calculate the difference amplitude between the simulated vibration parameters in the multiple simulated vibration test scenarios and the vibration parameters of the multiple scenarios, and obtain the simulation degree of multiple scenarios. Specifically, compare the simulated vibration parameters in the simulated vibration test scenario with the original scenario vibration parameters, calculate the difference amplitude between the simulated parameters and the original parameters, and use absolute error, relative error or other suitable measurement methods. The simulation degree (an indicator that measures the accuracy of the simulation model in simulating the actual vibration scene) is evaluated based on the magnitude of the difference. The smaller the difference, the higher the simulation degree and the closer the simulation result is to the actual situation; the larger the difference, the lower the simulation degree. This implementation method can quickly obtain the required vibration scene data by building a vibration scene database, achieving the technical effect of improving the efficiency of retrieval and simulation.

[0026] Step S300, according to the occurrence rates of the multiple scenes and the simulation degrees of the multiple scenes, set multiple test times of the multiple simulated vibration test scenes, perform vibration tests on the battery pack according to the multiple test times under the multiple simulated vibration test scenes, and obtain multiple image vibration acquisition result sets and multiple circuit vibration acquisition result sets. Specifically, according to the scene occurrence rate and scene simulation degree of each simulated vibration test scene, calculate the test weight of the vibration scene. The test weight can be the weighted sum of the scene occurrence rate and the scene simulation degree, or obtained by other reasonable weight allocation algorithms. Based on the test weight, the number of tests (the number of times the battery pack is vibrated) is allocated to each simulated vibration test scene, wherein the higher the scene occurrence rate and the higher the simulation degree, the higher the test number of the vibration scene.

[0027] In the simulation environment, each simulated vibration test scenario is loaded in turn according to the assigned number of tests to simulate the effect of vibration on the battery pack, and the image vibration data and circuit vibration data of the battery pack during the simulation process are recorded. The image vibration data and circuit vibration data collected in each simulated vibration test scenario are sorted out to form an image vibration acquisition result set and a circuit vibration acquisition result set, respectively. Among them, the image vibration acquisition result set is a simulation data set of the battery pack morphology changes obtained by simulating the image acquisition device in the simulated vibration test, which contains image data at multiple time points; the circuit vibration acquisition result set is a simulation data set of the battery pack electrical performance changes obtained by simulating the circuit data acquisition system in the simulated vibration test, which contains data on circuit parameters such as voltage and current. These result sets are used for subsequent vibration analysis and fusion to evaluate the performance and safety of the battery pack under simulated vibration conditions.

[0028] In a possible implementation, according to the occurrence rates of the multiple scenarios and the simulation degrees of the multiple scenarios, multiple test times of the multiple simulated vibration test scenarios are set, and the battery pack is subjected to vibration test according to the multiple test times in the multiple simulated vibration test scenarios. Step S300 further includes step S310, obtaining the preset test times. Specifically, before starting the test, a total preset test times is defined according to the limitations of test resources, time and cost. This number is a preliminary estimate and is used for subsequent allocation according to the importance and simulation degree of the scene. Step S320, according to the occurrence rates of the multiple scenarios and the simulation degrees of the multiple scenarios, the average scene occurrence rate and the average scene simulation degree are calculated. Specifically, the arithmetic mean of the occurrence rates and simulation degrees of all vibration scenarios is calculated respectively to obtain the average scene occurrence rate and the average scene simulation degree. The average scene occurrence rate is used to measure the prevalence of the scene occurrence, and the average scene simulation degree is used to measure the overall accuracy of the simulation scene. Step S330, according to the ratio of each corresponding scene occurrence rate and each scene simulation degree to the average scene occurrence rate and the average scene simulation degree, multiple test ratios are allocated and calculated. Specifically, for each vibration scenario, calculate the ratio of its occurrence rate to the average scenario occurrence rate, and the ratio of its simulation degree to the average scenario simulation degree. Multiply the above two ratios (or perform weighted summation according to actual needs) to obtain the test ratio of each vibration scenario, which is the ratio value used to allocate the number of tests.

[0029] Step S340, according to the multiple test ratios, the preset test times are corrected and calculated to obtain multiple test times. Specifically, the preset test times are allocated according to the test ratios of each vibration scene to obtain the specific test times of each simulated vibration test scene. Since the test times must be integers, the allocation results need to be rounded or rounded. Step S350, according to the multiple test times, the battery pack is subjected to vibration testing in the multiple simulated vibration test scenes, and after the test is completed, the battery pack is subjected to image acquisition and circuit information acquisition to obtain multiple image vibration acquisition result sets and multiple circuit vibration acquisition result sets. Specifically, according to the allocated test times, the battery pack is subjected to vibration testing in each simulated vibration test scene, and during or after the test, the battery pack is subjected to data acquisition to obtain image vibration acquisition results and circuit vibration acquisition results, and the collected data is organized into multiple image vibration acquisition result sets and multiple circuit vibration acquisition result sets. This implementation method reasonably allocates test resources by comprehensively considering the scene occurrence rate and simulation degree, so that the test is more focused on key scenes with high occurrence frequency and high simulation degree, thereby achieving the technical effect of ensuring the comprehensiveness and effectiveness of the vibration test.

[0030] Step S400, based on the occurrence rates of the multiple scenes and the simulation degrees of the multiple scenes, the multiple image vibration collection result sets and the multiple circuit vibration collection result sets are subjected to vibration analysis and fusion, to obtain multiple vibration test analysis result sets and multiple fused vibration test analysis results. Specifically, for each simulated vibration test scene, the image vibration collection results are analyzed using image processing technology (such as edge detection, shape recognition, texture analysis, etc.) to identify the deformation, cracks, displacement and other characteristics of the battery pack during the vibration process. At the same time, the circuit vibration collection results under each simulated vibration test scene are analyzed to monitor the changes in key parameters such as voltage, current, and resistance of the battery pack, and evaluate its electrical performance under vibration conditions.

[0031] Different weights are assigned to the above image analysis and circuit analysis results according to the occurrence rate and simulation degree of each vibration scenario. Scenes with high occurrence rate and high simulation degree are given higher weights. The weighted image analysis and circuit analysis results are integrated to generate a vibration test analysis result set for each simulated vibration test scenario. The vibration test analysis result set contains all key performance indicators and characteristics of the battery pack during the vibration process under the vibration scenario.

[0032] The vibration test analysis result set is subjected to data fusion, for example, by calculating the mean value, and based on the data fusion results, multiple fused vibration test analysis results are generated, including the overall performance evaluation, fault prediction, life prediction, etc. of the battery pack under vibration conditions.

[0033] In a possible implementation, according to the occurrence rates of the multiple scenes and the simulation degrees of the multiple scenes, the multiple image vibration collection result sets and the multiple circuit vibration collection result sets are subjected to vibration analysis and fusion, and step S400 further includes step S410, constructing a vibration analysis channel, embedded in the vibration test platform, the vibration analysis channel includes an image vibration analysis path and a circuit vibration analysis path, the image vibration analysis path and the circuit vibration analysis path respectively include P image vibration analysis branches and P circuit vibration analysis branches, and P is an integer greater than 1. Specifically, two parallel vibration analysis channels (for analyzing and processing vibration test data) are constructed inside the vibration test platform: an image vibration analysis path (a path specifically used to process an image vibration collection result set) and a circuit vibration analysis path (a path specifically used to process a circuit vibration collection result set). Each vibration analysis path is provided with multiple vibration analysis branches (P, sub-paths or processing units in the vibration analysis path, used to perform specific analysis tasks), and these vibration analysis branches are used to process data from different simulated vibration test scenes in parallel. P is an integer greater than 1, indicating the number of branches, which can be adjusted according to actual needs.

[0034] Step S420, according to the occurrence rates of the multiple scenes and the simulation degrees of the multiple scenes, calculate and set to obtain multiple numbers of analysis branches, wherein the size of the scene occurrence rate is positively correlated with the size of the number of analysis branches, and the size of the scene simulation degree is positively correlated with the size of the number of analysis branches. Specifically, according to the occurrence rate and simulation degree of each simulated vibration test scene, the number of analysis branches under the image vibration analysis path and the circuit vibration analysis path is dynamically calculated and set. The higher the scene occurrence rate and the higher the simulation degree, the more analysis branches are allocated to ensure a more refined analysis. For example, the number of analysis branches (such as P / 2) can be pre-set, and for a specific simulated vibration test scene, according to the statistical relationship between its scene occurrence rate and scene simulation degree and all simulated vibration test scenes, a comprehensive quantitative analysis of the scene occurrence rate and scene simulation degree is performed, and a distribution coefficient of the number of analysis branches for the simulated vibration test scene is determined, and this distribution coefficient is multiplied by the preset number of analysis branches and rounded to determine the number of analysis branches that are finally set. Step S430, respectively input the multiple image vibration collection result sets and the multiple circuit vibration collection result sets into the image vibration analysis branches and the circuit vibration analysis branches within the number of the multiple analysis branches for analysis, and obtain multiple image vibration analysis result sets and multiple circuit vibration analysis result sets through majority voting processing, wherein the image vibration analysis results and the circuit vibration analysis results both include the battery pack damage level. Specifically, the multiple image vibration collection result sets and the multiple circuit vibration collection result sets are respectively input into the corresponding analysis branches, each analysis branch performs analysis independently, and the results are processed through the majority voting mechanism to obtain stable image vibration analysis result sets and circuit vibration analysis result sets, which contain the battery pack damage level information (an indicator for evaluating the degree of damage to the battery pack during the vibration test). Among them, the majority voting processing makes a final decision by counting the analysis results of the majority analysis branches, for example, taking the mode or mean of the analysis results of the majority analysis branches as the final decision, so as to improve the accuracy and stability of the results. Step S440, weighted calculation is performed on the multiple image vibration analysis result sets and the multiple circuit vibration analysis result sets to obtain multiple vibration test analysis result sets. Specifically, a weighted calculation can be performed on each image vibration analysis result set and circuit vibration analysis result set according to the scene occurrence rate and simulation degree, and the size of the weight is proportional to the scene occurrence rate and simulation degree to ensure that the results of important vibration scenes occupy a larger proportion in the final analysis. Step S450, calculate the mean of the multiple vibration test analysis result sets to obtain multiple fused vibration test analysis results. Specifically, calculate the mean of each vibration test analysis result set to obtain a fused vibration test analysis result. The fused vibration test analysis result reflects the overall analysis result under the simulated vibration test scenario, providing a comprehensive perspective for the performance evaluation of the battery pack.This implementation method significantly improves the accuracy and efficiency of vibration analysis by constructing multiple analysis branches to process data in parallel. By dynamically adjusting the number of analysis branches according to the scene occurrence rate and simulation degree, the analysis process is made more flexible and adaptable. The majority voting mechanism is used to process the analysis results, which reduces the impact of accidental errors and noise, achieving the technical effect of improving the stability and reliability of vibration analysis results.

[0035] In a possible implementation, a vibration analysis channel is constructed, and step S410 further includes step S411, collecting a sample image vibration collection result set, a sample circuit vibration collection result set, and a sample vibration analysis result set according to the historical data of the battery pack vibration test, and combining them to obtain image vibration analysis training data and circuit vibration analysis training data. Specifically, the data of the battery pack vibration test is retrieved from the historical database, including image data (such as vibration videos or pictures captured by a camera), circuit data (such as voltage and current changes in the circuit during vibration, etc.), and corresponding vibration analysis results (such as battery pack damage level, etc.). The collected image vibration data, circuit vibration data and their analysis results are respectively sorted into sets, namely, a sample image vibration collection result set, a sample circuit vibration collection result set, and a sample vibration analysis result set. The image data and the corresponding analysis results are combined into image vibration analysis training data, and similarly, the circuit data and the corresponding analysis results are combined into circuit vibration analysis training data. These data are used for subsequent model training. Step S412, randomly extract 40%-60% of the data in the image vibration analysis training data to train the first image vibration analysis branch in the image vibration analysis path. Specifically, 40%-60% of the data is randomly selected from the image vibration analysis training data as the training set, and the remaining data can be used as a validation set or a test set. The first branch model in the image vibration analysis path is trained using the selected training set data. This model can be based on a deep learning framework, such as a convolutional neural network (CNN), to extract features from images and predict vibration analysis results.

[0036] Step S413, randomly extract 40%-60% of the data in the image vibration analysis training data again, and train the second image vibration analysis branch in the image vibration analysis path; Step S414, continue training to obtain P image vibration analysis branches, and obtain the image vibration analysis path. Specifically, repeat the process of step S412 until P different image vibration analysis branches are trained, and each image vibration analysis branch can adopt a different network structure, parameter or training strategy to increase the accuracy and robustness of the final image vibration analysis path. The trained P image vibration analysis branches are combined into an overall path, i.e., the image vibration analysis path, by majority voting. Step S415, according to the circuit vibration analysis training data, train to obtain P circuit vibration analysis branches, and obtain the circuit vibration analysis path. Specifically, similar to the image vibration analysis, train P circuit vibration analysis branches, and these analysis branches can be based on different machine learning or deep learning algorithms, such as time series analysis, regression model, etc., to adapt to the characteristics of the circuit data, and combine the trained circuit vibration analysis branches into a circuit vibration analysis path. In this implementation, different analysis branches use different training data, algorithms or strategies and have different adaptability to different types of vibration signals or noises, thus achieving the technical effect of enhancing the robustness of the entire vibration analysis system.

[0037] Step S500, respectively perform distribution analysis on the multiple vibration test analysis result sets to obtain multiple test volatility parameters, and perform compensation processing on the multiple fused vibration test analysis results in combination with the multiple scene simulation degrees to obtain multiple vibration hazard levels. Specifically, perform statistical analysis on each vibration test analysis result set, and calculate its mean, standard deviation, maximum value, minimum value and other statistics to describe the distribution of the data. Based on the distribution statistics results, calculate the test volatility parameters of each vibration test analysis result set, and the test volatility parameters may include the coefficient of variation (the ratio of the standard deviation to the mean), the interquartile range (Q3-Q1), etc., which are used to quantify the discreteness or volatility of the data and evaluate the stability and reliability of the test results. According to the test volatility parameters and the scene simulation degree, formulate a compensation strategy, and apply the compensation strategy to correct or adjust the fused vibration test analysis results, including data smoothing, outlier removal, result weighting and other processing methods to eliminate the influence of simulation errors and test errors and improve the reliability of the results. Based on the fused vibration test analysis results after compensation processing and combined with the preset hazard level classification standards, each result is divided into different vibration hazard levels to evaluate the impact of vibration on the battery pack.

[0038] In a possible implementation, the plurality of vibration test analysis result sets are respectively subjected to distribution analysis to obtain a plurality of test volatility parameters, and the plurality of fused vibration test analysis results are compensated in combination with the plurality of scene simulation degrees. Step S500 further includes step S510, wherein the plurality of vibration test analysis result sets are respectively subjected to distribution discreteness analysis to obtain a plurality of test volatility parameters. Specifically, a distribution discreteness analysis is performed on each vibration test analysis result set, including calculating statistics such as the standard deviation, variance, coefficient of variation, and interquartile range of the data to quantify the discreteness or volatility of the data, and the volatility parameters of each vibration test analysis result set are determined according to the results of the distribution discreteness analysis for subsequent compensation processing. Step S520, wherein a plurality of scene compensation coefficients are calculated according to the plurality of scene simulation degrees, and a plurality of compensation coefficients are calculated in combination with the plurality of test volatility parameters. Specifically, the compensation coefficient of each simulated vibration test scene is calculated according to the scene simulation degree, and the higher the simulation degree of the scene, the smaller the compensation coefficient; and the lower the simulation degree of the scene, the larger the compensation coefficient. Combine the test volatility parameter with the scene compensation coefficient to calculate the compensation coefficient of each vibration test analysis result. For example, the test volatility parameter is used as a weight factor, multiplied with the scene compensation coefficient or other forms of combined operations are performed. Step S530, using the multiple compensation coefficients, the multiple fused vibration test analysis results are compensated and calculated to obtain multiple vibration hazard levels. Specifically, according to the obtained compensation coefficients, the multiple fused vibration test analysis results are compensated and calculated. For example, the original value of each fused vibration test analysis result is multiplied by the corresponding compensation coefficient to obtain the compensated result. Based on the compensated fused vibration test analysis results, combined with the preset vibration hazard level classification standard, each result is divided into different vibration hazard levels. This implementation method performs compensation processing by integrating multiple factors (test volatility, scene simulation degree), so that the evaluation results are more robust. Even in the case of unstable test conditions or low simulation degree, a more reliable result can be obtained through a reasonable compensation strategy, thereby achieving the technical effect of improving the accuracy of vibration hazard level assessment.

[0039] Step S600, according to the occurrence rates of the multiple scenarios, the simulation degrees of the multiple scenarios and the multiple test volatility parameters, multiple scenario weights are configured, and the multiple vibration hazard levels are weightedly calculated to obtain the vibration test results of the battery pack. Specifically, a weight allocation strategy is formulated according to the importance of the scenario occurrence rate, the scenario simulation degree and the test volatility parameters. For example, the higher the scenario occurrence rate, the higher the simulation degree and the smaller the test volatility, the greater the weight. By multiplication, weighted summation, normalization and other methods, the scenario occurrence rate, simulation degree and test volatility parameters are converted into specific weight values, the weight of each simulated vibration test scenario is applied to its corresponding vibration hazard level, all weighted vibration hazard levels are summarized or integrated, and the overall vibration test results of the battery pack are obtained. The results are output in the form of reports, charts or other forms for reference by decision makers, wherein the vibration test results of the battery pack may include detailed test data, weight distribution, calculation process and final evaluation conclusions and suggestions. The embodiment of the present application adopts technical means such as collecting multiple vibration scenarios and vibration parameters of the battery pack during assembly and operation, performing vibration scenario retrieval and simulation restoration, obtaining multiple simulated vibration test scenarios and scenario simulation degrees, setting the number of tests according to the scenario occurrence rate and simulation degree, performing vibration testing, and collecting image and circuit vibration data, analyzing and fusing the vibration data, obtaining vibration test analysis results and fused vibration test analysis results, configuring scenario weights according to the scenario occurrence rate, simulation degree and test volatility parameters, performing weighted calculation on the vibration hazard level, and obtaining vibration test results of the battery pack, etc., comprehensively collecting and analyzing the performance of the battery pack in different vibration scenarios, and achieving the technical effect of improving the comprehensiveness and accuracy of the vibration test evaluation results by deeply mining and fusing vibration data.

[0040] In a possible implementation, multiple scene weights are configured according to the occurrence rates of the multiple scenes, the simulation degrees of the multiple scenes, and the multiple test volatility parameters, and the multiple vibration hazard levels are weightedly calculated to obtain the vibration test results of the battery pack. Step S600 further includes step S610, according to the occurrence rates of the multiple scenes, multiple occurrence rate weights are allocated and calculated, wherein the size of the scene occurrence rate is positively correlated with the size of the occurrence rate weight. Specifically, the scene occurrence rates are sorted or graded, and based on the sorting or grading results, an occurrence rate weight is allocated to each simulated vibration test scene, and the scene with a higher occurrence rate is assigned a greater weight to reflect its importance in the overall evaluation. Step S620, according to the simulation degrees of the multiple scenes, multiple simulation weights are allocated and calculated, wherein the size of the scene simulation degree is positively correlated with the size of the simulation weight. Specifically, according to the scene simulation degree, the simulated vibration test scenes are divided into different levels, such as high simulation degree, medium simulation degree, and low simulation degree. Different simulation weights are allocated to simulated vibration test scenes of different levels, and the simulated vibration test scenes with a higher simulation degree are assigned a greater weight. Step S630, according to the multiple test volatility parameters, multiple test weights are allocated and calculated, wherein the size of the test volatility parameter is negatively correlated with the size of the test weight. Specifically, according to the size of the test volatility parameter, a test weight is allocated for each simulated vibration test scenario. The smaller the test volatility parameter (i.e., the more stable the test result), the larger the test weight; and vice versa, to reflect the stability and reliability of the test results. Step S640, according to the multiple occurrence rate weights, multiple simulation weights and multiple test weights, a weight normalization calculation configuration is performed to obtain multiple scenario weights, and the multiple vibration hazard levels are weightedly calculated to obtain the vibration test results of the battery pack. Specifically, for each simulated vibration test scenario, the corresponding occurrence rate weight, simulation weight and test weight are normalized so that each weight factor can be compared and calculated on a unified scale. For example, first add all the weights (occurrence rate weight, simulation weight, test weight) of all simulated vibration test scenarios together to get a sum. For each specific simulated vibration test scenario, add their three weights together and divide them by the sum calculated previously. In this way, the weight of each simulated vibration test scenario is normalized to a unified scale, and subsequent weighted calculations can be performed. Use the normalized weights to perform weighted calculations on multiple vibration hazard levels. The specific calculation method can be a simple weighted summation or other complex weighted evaluation model. The result of the weighted calculation is output as the vibration test result of the battery pack. This result combines the importance, simulation degree and stability of the test results of multiple simulated vibration test scenarios, and is therefore more comprehensive and accurate.This implementation method takes into account the scenario occurrence rate, simulation degree and test volatility parameters and assigns weights to them respectively, comprehensively reflecting the impact of different simulated vibration test scenarios and test results on the overall evaluation, thereby achieving the technical effect of improving the accuracy and reliability of battery pack vibration test results.

[0041] In the above, refer to Figure 1 A battery pack vibration test method according to an embodiment of the present invention is described in detail. Figure 2 A battery pack vibration test platform according to an embodiment of the present invention is described.

[0042] A battery pack vibration test platform according to an embodiment of the present invention is used to solve the technical problem that the evaluation results of the existing battery pack vibration test are not comprehensive and accurate enough, so as to achieve the technical effect of improving the comprehensiveness and accuracy of the vibration test evaluation results. A battery pack vibration test platform includes: a scene vibration parameter acquisition module 10, a vibration simulation restoration module 20, a vibration test module 30, a vibration analysis and fusion module 40, a compensation processing module 50, and a vibration test result acquisition module 60.

[0043] The scene vibration parameter acquisition module 10 is used to acquire multiple vibration scenes during the assembly and operation of the battery pack, and to acquire scene vibration parameters in the multiple vibration scenes, wherein each scene vibration parameter includes vibration parameters of the X-axis, Y-axis and Z-axis; the vibration simulation and restoration module 20 is used to perform vibration scene retrieval according to the multiple scene vibration parameters, obtain multiple scene occurrence rates of the multiple vibration scenes, and perform vibration simulation and restoration according to the multiple scene vibration parameters to obtain multiple simulated vibration test scenes and multiple scene simulation degrees; the vibration test module 30 is used to set multiple test times for the multiple simulated vibration test scenes according to the multiple scene occurrence rates and the multiple scene simulation degrees, and perform vibration tests on the battery pack according to the multiple test times under the multiple simulated vibration test scenes to obtain multiple image vibration acquisition result sets and multiple A set of circuit vibration collection results; a vibration analysis and fusion module 40 is used to perform vibration analysis and fusion on the multiple image vibration collection result sets and the multiple circuit vibration collection result sets according to the multiple scene occurrence rates and the multiple scene simulation degrees, so as to obtain multiple vibration test analysis result sets and multiple fused vibration test analysis results; a compensation processing module 50 is used to perform distribution analysis on the multiple vibration test analysis result sets respectively, to obtain multiple test volatility parameters, and to perform compensation processing on the multiple fused vibration test analysis results in combination with the multiple scene simulation degrees, so as to obtain multiple vibration hazard levels; a vibration test result acquisition module 60 is used to configure multiple scene weights according to the multiple scene occurrence rates, the multiple scene simulation degrees and the multiple test volatility parameters, to perform weighted calculation on the multiple vibration hazard levels, and to obtain the vibration test result of the battery pack.

[0044] The specific configuration of the vibration simulation restoration module 20 will be described in detail below. As described above, according to multiple scene vibration parameters, vibration scene retrieval is performed to obtain multiple scene occurrence rates of the multiple vibration scenes, and vibration simulation restoration is performed according to the multiple scene vibration parameters to obtain multiple simulated vibration test scenes and multiple scene simulation degrees. The vibration simulation restoration module 20 may further include: a vibration scene database construction unit is used to construct a vibration scene database based on historical vibration scenes collected in historical time; a multiple scene occurrence rate acquisition unit is used to search in the vibration scene database according to multiple scene vibration parameters to obtain multiple scene occurrence rates; a multiple simulated vibration test scene acquisition unit is used to perform vibration simulation restoration according to the multiple scene vibration parameters to obtain multiple simulated vibration test scenes; a difference amplitude calculation unit is used to calculate the difference amplitudes between the simulated vibration parameters and the multiple scene vibration parameters in the multiple simulated vibration test scenes to obtain multiple scene simulation degrees.

[0045] The specific configuration of the vibration test module 30 will be described in detail below. As described above, according to the multiple scene occurrence rates and multiple scene simulation degrees, multiple test times of the multiple simulated vibration test scenes are set, and the battery pack is subjected to vibration test according to the multiple test times in the multiple simulated vibration test scenes. The vibration test module 30 may further include: a preset test number acquisition unit for acquiring the preset test number; a mean value calculation unit for calculating the average scene occurrence rate and the average scene simulation degree according to the multiple scene occurrence rates and the multiple scene simulation degrees; multiple test ratio calculation units for allocating and calculating multiple test ratios according to the ratio of each corresponding scene occurrence rate and each scene simulation degree to the average scene occurrence rate and the average scene simulation degree; a preset test number correction unit for correcting the preset test number according to the multiple test ratios to obtain multiple test times; a vibration test unit for performing vibration test on the battery pack in the multiple simulated vibration test scenes according to the multiple test times, and after the test is completed, performing image acquisition and circuit information acquisition on the battery pack to obtain multiple image vibration acquisition result sets and multiple circuit vibration acquisition result sets.

[0046] Below, the specific configuration of the vibration analysis and fusion module 40 will be described in detail. As described above, according to the multiple scene occurrence rates and the multiple scene simulation degrees, the multiple image vibration acquisition result sets and the multiple circuit vibration acquisition result sets are subjected to vibration analysis and fusion, and the vibration analysis and fusion module 40 may further include: a vibration analysis channel construction unit is used to construct a vibration analysis channel, embedded in the vibration test platform, the vibration analysis channel includes an image vibration analysis path and a circuit vibration analysis path, the image vibration analysis path and the circuit vibration analysis path include P image vibration analysis branches and P circuit vibration analysis branches, respectively, and P is an integer greater than 1; a multiple analysis branch number setting unit is used to calculate and set the multiple analysis branch numbers according to the multiple scene occurrence rates and the multiple scene simulation degrees, wherein the size of the scene occurrence rate is positively correlated with the size of the analysis branch number. The size of the scene simulation degree is positively correlated with the size of the number of analysis branches; the majority voting processing unit is used to input the multiple image vibration acquisition result sets and the multiple circuit vibration acquisition result sets into the image vibration analysis branches and the circuit vibration analysis branches within the multiple analysis branch numbers for analysis, and through majority voting processing, multiple image vibration analysis result sets and multiple circuit vibration analysis result sets are obtained, wherein the image vibration analysis results and the circuit vibration analysis results both include battery pack damage levels; the weighted calculation unit is used to perform weighted calculation on the multiple image vibration analysis result sets and the multiple circuit vibration analysis result sets to obtain multiple vibration test analysis result sets; the mean calculation unit is used to calculate the mean of the multiple vibration test analysis result sets to obtain multiple fused vibration test analysis results.

[0047] Among them, a vibration analysis channel is constructed, and the vibration analysis channel construction unit may further include: a training data acquisition subunit is used to collect a sample image vibration acquisition result set, a sample circuit vibration acquisition result set and a sample vibration analysis result set according to the historical data of the battery pack vibration test, and combine them to obtain image vibration analysis training data and circuit vibration analysis training data; an image vibration analysis path acquisition subunit is used to randomly extract 40%-60% of the data in the image vibration analysis training data, train the first image vibration analysis branch in the image vibration analysis path, randomly extract 40%-60% of the data in the image vibration analysis training data again, train the second image vibration analysis branch in the image vibration analysis path, continue training to obtain P image vibration analysis branches, and obtain an image vibration analysis path; a circuit vibration analysis path acquisition subunit is used to train to obtain P circuit vibration analysis branches according to the circuit vibration analysis training data, and obtain a circuit vibration analysis path.

[0048] The specific configuration of the compensation processing module 50 will be described in detail below. As described above, the distribution analysis is performed on the multiple vibration test analysis result sets respectively to obtain multiple test volatility parameters, and the compensation processing is performed on the multiple fused vibration test analysis results in combination with the multiple scene simulation degrees. The compensation processing module 50 may further include: a distribution discreteness analysis unit for performing distribution discreteness analysis on the multiple vibration test analysis result sets respectively to obtain multiple test volatility parameters; multiple compensation coefficient acquisition units for calculating and obtaining multiple scene compensation coefficients according to the multiple scene simulation degrees, and calculating and obtaining multiple compensation coefficients in combination with the multiple test volatility parameters; a compensation calculation processing unit for using the multiple compensation coefficients to perform compensation calculation processing on the multiple fused vibration test analysis results to obtain multiple vibration hazard levels.

[0049] Below, the specific configuration of the vibration test result acquisition module 60 will be described in detail. As described above, according to the multiple scene occurrence rates, multiple scene simulation degrees and multiple test volatility parameters, multiple scene weights are configured, and the multiple vibration hazard levels are weightedly calculated to obtain the vibration test results of the battery pack. The vibration test result acquisition module 60 may further include: multiple occurrence rate weight allocation calculation units are used to allocate and calculate multiple occurrence rate weights according to the multiple scene occurrence rates, wherein the size of the scene occurrence rate and the size of the occurrence rate weight are positively correlated; multiple simulation weight allocation calculation units are used to allocate and calculate multiple simulation weights according to the multiple scene simulation degrees, wherein the size of the scene simulation degree and the size of the simulation weight are positively correlated; multiple test weight allocation calculation units are used to allocate and calculate multiple test weights according to the multiple test volatility parameters, wherein the size of the test volatility parameter and the size of the test weight are negatively correlated; the weighted calculation unit is used to perform weight normalization calculation configuration according to the multiple occurrence rate weights, multiple simulation weights and multiple test weights, obtain multiple scene weights, perform weighted calculation on the multiple vibration hazard levels, and obtain the vibration test results of the battery pack.

[0050] A battery pack vibration test platform provided in an embodiment of the present invention can execute a battery pack vibration test method provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0051] Although the present application makes various references to certain modules in the platform according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be implemented; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0052] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A battery pack vibration test method, characterized in that: The method comprises: Collecting multiple vibration scenarios during the battery pack assembly operation, and collecting scenario vibration parameters within the multiple vibration scenarios, wherein each scenario vibration parameter includes vibration parameters of the X-axis, the Y-axis, and the Z-axis; According to a plurality of scene vibration parameters, a vibration scene search is performed to obtain a plurality of scene occurrence rates of the plurality of vibration scenes, and according to the plurality of scene vibration parameters, a vibration simulation restoration is performed to obtain a plurality of simulated vibration test scenes and a plurality of scene simulation degrees; According to the occurrence rates of the multiple scenes and the simulation degrees of the multiple scenes, multiple test times of the multiple simulated vibration test scenes are set, and vibration tests are performed on the battery pack according to the multiple test times under the multiple simulated vibration test scenes to obtain multiple image vibration acquisition result sets and multiple circuit vibration acquisition result sets; According to the occurrence rates of the multiple scenes and the simulation degrees of the multiple scenes, vibration analysis and fusion are performed on the multiple image vibration acquisition result sets and the multiple circuit vibration acquisition result sets to obtain multiple vibration test analysis result sets and multiple fused vibration test analysis results; Performing distribution analysis on the multiple vibration test analysis result sets respectively to obtain multiple test volatility parameters, and performing compensation processing on the multiple fused vibration test analysis results in combination with the multiple scene simulation degrees to obtain multiple vibration hazard levels; According to the occurrence rates of the multiple scenarios, the simulation degrees of the multiple scenarios and the multiple test volatility parameters, multiple scenario weights are configured, and the multiple vibration hazard levels are weightedly calculated to obtain the vibration test results of the battery pack.

2. The battery pack vibration test method according to claim 1, characterized in that: According to multiple scene vibration parameters, vibration scene retrieval is performed to obtain multiple scene occurrence rates of the multiple vibration scenes, and vibration simulation restoration is performed according to the multiple scene vibration parameters to obtain multiple simulated vibration test scenes and multiple scene simulation degrees, including: Build a vibration scenario database based on historical vibration scenarios collected over a historical period; Searching the vibration scene database according to the vibration parameters of the multiple scenes to obtain the occurrence rates of the multiple scenes; Perform vibration simulation and restoration according to the vibration parameters of the multiple scenarios to obtain multiple simulated vibration test scenarios; The difference amplitudes between the simulated vibration parameters in the multiple simulated vibration test scenarios and the vibration parameters of the multiple scenarios are calculated to obtain the simulation degrees of the multiple scenarios.

3. The battery pack vibration test method according to claim 1, characterized in that: According to the occurrence rates of the multiple scenarios and the simulation degrees of the multiple scenarios, multiple test times of the multiple simulated vibration test scenarios are set, and vibration tests are performed on the battery pack according to the multiple test times in the multiple simulated vibration test scenarios, including: Get the preset number of tests; According to the multiple scene occurrence rates and the multiple scene simulation degrees, calculating and obtaining an average scene occurrence rate and an average scene simulation degree; According to the ratio of each corresponding scene occurrence rate and each scene simulation degree to the average scene occurrence rate and the average scene simulation degree, multiple test ratios are allocated and calculated; According to the multiple test ratios, the preset test times are corrected and calculated to obtain multiple test times; According to the multiple test times, vibration tests are performed on the battery pack under the multiple simulated vibration test scenarios. After the tests are completed, image acquisition and circuit information acquisition are performed on the battery pack to obtain multiple image vibration acquisition result sets and multiple circuit vibration acquisition result sets.

4. The battery pack vibration test method according to claim 1, characterized in that: According to the multiple scene occurrence rates and the multiple scene simulation degrees, vibration analysis and fusion are performed on the multiple image vibration collection result sets and the multiple circuit vibration collection result sets, including: Constructing a vibration analysis channel, embedded in the vibration test platform, the vibration analysis channel including an image vibration analysis path and a circuit vibration analysis path, the image vibration analysis path and the circuit vibration analysis path respectively including P image vibration analysis branches and P circuit vibration analysis branches, where P is an integer greater than 1; According to the multiple scene occurrence rates and the multiple scene simulation degrees, a calculation setting is performed to obtain multiple numbers of analysis branches, wherein the size of the scene occurrence rate is positively correlated with the size of the number of analysis branches, and the size of the scene simulation degree is positively correlated with the size of the number of analysis branches; Inputting the plurality of image vibration collection result sets and the plurality of circuit vibration collection result sets into the image vibration analysis branches and the circuit vibration analysis branches within the plurality of analysis branch numbers for analysis respectively, and obtaining a plurality of image vibration analysis result sets and a plurality of circuit vibration analysis result sets through majority voting, wherein the image vibration analysis results and the circuit vibration analysis results both include a battery pack damage level; Performing weighted calculation on the multiple image vibration analysis result sets and the multiple circuit vibration analysis result sets to obtain multiple vibration test analysis result sets; The average values ​​of the plurality of vibration test analysis result sets are calculated to obtain a plurality of fused vibration test analysis results.

5. The battery pack vibration test method according to claim 4, characterized in that: Build a vibration analysis channel, including: According to the historical data of battery pack vibration test, a sample image vibration collection result set, a sample circuit vibration collection result set and a sample vibration analysis result set are collected, and image vibration analysis training data and circuit vibration analysis training data are obtained by combining them; Randomly extracting 40%-60% of the data in the image vibration analysis training data to train the first image vibration analysis branch in the image vibration analysis path; Again randomly extracting 40%-60% of the data in the image vibration analysis training data to train the second image vibration analysis branch in the image vibration analysis path; Continue training to obtain P image vibration analysis branches and obtain image vibration analysis paths; According to the circuit vibration analysis training data, P circuit vibration analysis branches are obtained through training, and a circuit vibration analysis path is obtained.

6. The battery pack vibration test method according to claim 1, characterized in that: Performing distribution analysis on the multiple vibration test analysis result sets respectively to obtain multiple test volatility parameters, and performing compensation processing on the multiple fused vibration test analysis results in combination with the multiple scene simulation degrees, including: Performing distribution discreteness analysis on the plurality of vibration test analysis result sets respectively to obtain a plurality of test volatility parameters; Calculate and obtain multiple scene compensation coefficients according to the multiple scene simulation degrees, and calculate and obtain multiple compensation coefficients in combination with the multiple test volatility parameters; The plurality of compensation coefficients are used to perform compensation calculation processing on the plurality of fused vibration test analysis results to obtain a plurality of vibration hazard levels.

7. The battery pack vibration testing method according to claim 1, characterized in that: According to the occurrence rates of the multiple scenarios, the simulation degrees of the multiple scenarios and the multiple test volatility parameters, multiple scenario weights are configured, and the multiple vibration hazard levels are weightedly calculated to obtain the vibration test results of the battery pack, including: According to the plurality of scene appearance rates, a plurality of appearance rate weights are obtained by allocation calculation, wherein the size of the scene appearance rate is positively correlated with the size of the appearance rate weight; According to the multiple scene simulation degrees, multiple simulation weights are obtained by allocation and calculation, wherein the magnitude of the scene simulation degree is positively correlated with the magnitude of the simulation weight; According to the multiple test volatility parameters, multiple test weights are obtained by allocation and calculation, wherein the magnitude of the test volatility parameter is negatively correlated with the magnitude of the test weight; According to the multiple occurrence rate weights, multiple simulation weights and multiple test weights, a weight normalization calculation configuration is performed to obtain multiple scene weights, and a weighted calculation is performed on the multiple vibration hazard levels to obtain a vibration test result of the battery pack.

8. A battery pack vibration test platform, characterized in that: The platform is used to implement a battery pack vibration test method according to any one of claims 1 to 7, and the platform comprises: A scene vibration parameter acquisition module, the scene vibration parameter acquisition module is used to acquire multiple vibration scenes during the assembly and operation of the battery pack, and acquire scene vibration parameters in the multiple vibration scenes, wherein each scene vibration parameter includes vibration parameters of the X-axis, Y-axis and Z-axis; A vibration simulation and restoration module, the vibration simulation and restoration module is used to perform vibration scene retrieval according to multiple scene vibration parameters, obtain multiple scene occurrence rates of the multiple vibration scenes, and perform vibration simulation and restoration according to the multiple scene vibration parameters to obtain multiple simulated vibration test scenes and multiple scene simulation degrees; A vibration test module, wherein the vibration test module is used to set a plurality of test times of the plurality of simulated vibration test scenarios according to the plurality of scene occurrence rates and the plurality of scene simulation degrees, perform vibration tests on the battery pack according to the plurality of test times under the plurality of simulated vibration test scenarios, and obtain a plurality of image vibration acquisition result sets and a plurality of circuit vibration acquisition result sets; A vibration analysis and fusion module, wherein the vibration analysis and fusion module is used to perform vibration analysis and fusion on the multiple image vibration collection result sets and the multiple circuit vibration collection result sets according to the multiple scene occurrence rates and the multiple scene simulation degrees, to obtain multiple vibration test analysis result sets and multiple fused vibration test analysis results; A compensation processing module, the compensation processing module is used to perform distribution analysis on the multiple vibration test analysis result sets respectively to obtain multiple test volatility parameters, and to perform compensation processing on the multiple fusion vibration test analysis results in combination with the multiple scene simulation degrees to obtain multiple vibration hazard levels; A vibration test result acquisition module is used to configure multiple scenario weights according to the multiple scenario occurrence rates, multiple scenario simulation degrees and multiple test volatility parameters, perform weighted calculation on the multiple vibration hazard levels, and obtain the vibration test results of the battery pack.

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