Battery pack test method, storage medium and electronic equipment

Abstract

The invention discloses a battery pack test method, a storage medium and electronic equipment, and relates to the field of batteries. The method comprises the following steps: carrying out a charge-discharge test on a to-be-tested battery pack, and obtaining long-cycle test data of the to-be-tested battery pack; performing test condition analysis on the long-cycle test data to check whether the to-be-tested battery pack has an abnormal point, and outputting an abnormal point check result; and inputting the long-loop test data into a preset algorithm program under the condition that the abnormal point checking result is passed, and obtaining a test performance report of the to-be-tested battery pack according to the preset algorithm program. According to the invention, the problem of low long-cycle test efficiency of the battery pack in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the technical field of batteries, and in particular, to a battery pack testing method, a storage medium, and an electronic device. Background Art

[0002] With the wide application of renewable energy and the rapid development of electric vehicle technology, energy storage batteries, as core energy storage and power components, have attracted much attention for their performance and safety. Long cycle testing is an important means to evaluate the reliability and stability of energy storage batteries under long-term use or extreme conditions.

[0003] On the one hand, in the prior art, the long cycle test period needs to last for several months to several years, and a set of detailed battery state data, such as voltage, current, temperature, voltage difference, etc., is recorded for each frame during the test. The amount of test data accumulated is huge. Traditional methods rely on engineers to manually sort out this data, and then conduct statistics, graphing, and analysis, and finally form a test report. This process not only has a huge workload and takes a long time, but also mainly adopts manual processing methods, so the test efficiency is low.

[0004] On the other hand, during the long cycle test process of the prior art, when testing equipment such as an electrical cabinet or a battery management system (BMS) collects data such as voltage and temperature, due to factors such as software bugs and electromagnetic interference, there may be situations such as electrical cabinet process step jump faults or upper and lower limit protection faults, and data distortion in BMS data collection, resulting in the inability to accurately capture the individual cell voltages of the battery completely, thus there is a risk of overcharging or over-discharging. To avoid battery safety accidents caused by this risk, test engineers also need to manually check the test data regularly, which further increases the workload and reduces the test efficiency.

[0005] Therefore, the above two reasons lead to a low efficiency of the long cycle test of the battery pack in the prior art. Summary of the Invention

[0006] The main purpose of the present application is to provide a battery pack testing method, a storage medium, and an electronic device to solve the problem of low efficiency of the long cycle test of the battery pack in the related art.

[0007] To achieve the above object, according to one aspect of the present application, a battery pack testing method is provided. The method includes: performing charge and discharge tests on a battery pack to be tested, and obtaining long cycle test data of the battery pack to be tested; performing test condition analysis on the long cycle test data to check whether there are abnormal points in the battery pack to be tested, and outputting the abnormal point check result; in the case where the abnormal point check result passes, inputting the long cycle test data into a preset algorithm program, and obtaining a test performance report of the battery pack to be tested according to the preset algorithm program.

[0008] Further, perform a test condition analysis on the long-cycle test data to check whether there are abnormal points in the battery pack to be tested, and output the abnormal point check result, including: obtaining the pre-set charge and discharge test step parameters; determining whether the long-cycle test data belongs to the preset interval of the charge and discharge test step parameters, and if so, output that the abnormal point check result of the battery pack to be tested passes.

[0009] Further, obtain the test performance report of the battery pack to be tested according to the preset algorithm program, including: obtaining multiple performance index algorithms in the preset algorithm program; determining multiple performance index results corresponding to the long-cycle test data according to all the performance index algorithms; generating the test performance report of the battery pack to be tested according to all the performance index results.

[0010] Further, generating the test performance report of the battery pack to be tested according to all the performance index results includes: obtaining the preset weight ratio table, where the preset weight ratio table includes the target weight corresponding to each performance index result; determining the weighted results corresponding to all the performance index results according to all the target weights in the preset weight ratio table; generating the test performance report of the battery pack to be tested according to all the weighted results.

[0011] Further, before obtaining multiple performance index algorithms in the preset algorithm program, it also includes: obtaining the new interface address of the preset performance index algorithm as the sub-algorithm to be added to the preset performance index algorithm, where the preset performance index algorithm is any one of the performance index algorithms in the preset algorithm program; performing accuracy verification on the sub-algorithm to be added to the preset performance index algorithm according to the labeled data set; if the verification passes, updating the preset performance index algorithm according to the sub-algorithm to be added to the preset performance index algorithm.

[0012] Further, performing accuracy verification on the sub-algorithm to be added to the preset performance index algorithm according to the labeled data set includes: adding the sub-algorithm to be added to the preset performance index algorithm to the existing sub-algorithm set of the preset performance index algorithm to obtain a new sub-algorithm set; performing different weighted ratios on the multiple sub-algorithms in the new sub-algorithm set to form multiple sub-algorithm weighted combinations, and determining the accuracy of all the sub-algorithm weighted combinations according to the labeled data set; if the sub-algorithm weighted combination with the highest accuracy contains the sub-algorithm to be added, output that the verification passes.

[0013] Further, after determining the performance index results corresponding to the long-cycle test data according to the performance index algorithm, the method also includes: determining the preset change index of the battery pack to be tested in a single cycle according to the performance index results, where the preset change index includes at least one of the capacity efficiency change rate, energy efficiency change rate, monomer voltage difference change rate, and single-body temperature difference change rate; obtaining the change rate threshold corresponding to the preset change index, and determining whether the preset change index exceeds the change rate threshold, and if so, sending a change overrun warning signal.

[0014] Further, after obtaining the test performance report of the battery pack to be tested according to the preset algorithm program, the method further includes: generating a performance index curve graph according to the test performance report; predicting a trend prediction curve of the performance index curve graph by using a non-linear electrochemical algorithm; and generating a test conclusion for the battery pack to be tested according to the trend prediction curve.

[0015] To achieve the above object, according to another aspect of the present application, there is provided a battery pack test device, including: a data acquisition unit, configured to perform charge and discharge tests on the battery pack to be tested and obtain long-cycle test data of the battery pack to be tested; an abnormality troubleshooting unit, configured to perform test condition analysis on the long-cycle test data to troubleshoot whether there are abnormal points in the battery pack to be tested and output an abnormal point troubleshooting result; and a report acquisition unit, configured to input the long-cycle test data into a preset algorithm program and obtain a test performance report of the battery pack to be tested according to the preset algorithm program when the abnormal point troubleshooting result is passed.

[0016] Further, the abnormality troubleshooting unit includes: a parameter reading module, configured to obtain preset charge and discharge test step parameters; and an abnormality determination module, configured to determine whether the long-cycle test data belongs to a preset interval of the charge and discharge test step parameters, and if so, output that the abnormal point troubleshooting result of the battery pack to be tested is passed.

[0017] Further, the report acquisition unit includes: an algorithm reading module, configured to obtain multiple performance index algorithms in the preset algorithm program; an index calculation module, configured to determine multiple performance index results corresponding to the long-cycle test data according to all the performance index algorithms; and a report generation module, configured to generate a test performance report of the battery pack to be tested according to all the performance index results.

[0018] Further, the report generation module includes: a table acquisition sub-module, configured to obtain a preset weight ratio table, where the preset weight ratio table includes target weights corresponding to each performance index result; a weighted calculation sub-module, configured to determine weighted results corresponding to all the performance index results according to all the target weights in the preset weight ratio table; and a weighted generation sub-module, configured to generate a test performance report of the battery pack to be tested according to all the weighted results.

[0019] Further, the report acquisition unit further includes: an interface acquisition module, configured to acquire a new interface address of a preset performance metric algorithm as a sub-algorithm to be added to the preset performance metric algorithm before acquiring multiple performance metric algorithms in the preset algorithm program, where the preset performance metric algorithm is any one of the performance metric algorithms in the preset algorithm program; a verification module, configured to perform accuracy verification on the sub-algorithm to be added to the preset performance metric algorithm according to the labeled data set; and an update module, configured to update the preset performance metric algorithm according to the sub-algorithm to be added to the preset performance metric algorithm if the verification passes.

[0020] Further, the verification module includes: an addition sub-module, configured to add the sub-algorithm to be added to the preset performance metric algorithm to the existing sub-algorithm set of the preset performance metric algorithm to obtain a new sub-algorithm set; an accuracy calculation sub-module, configured to perform different weighted ratios on multiple sub-algorithms in the new sub-algorithm set to form multiple weighted combinations of sub-algorithms, and determine the accuracy of all weighted combinations of sub-algorithms according to the labeled data set; and a verification output sub-module, configured to output that the verification passes if the weighted combination of sub-algorithms with the highest accuracy contains the sub-algorithm to be added.

[0021] Further, the report acquisition unit further includes: a change index module, configured to determine a preset change index of the battery pack to be tested in a single cycle according to the performance metric result, where the preset change index includes at least one of a capacity efficiency change rate, an energy efficiency change rate, a single-cell voltage difference change rate, and a single-cell temperature difference change rate; and an overlimit judgment module, configured to obtain a change rate threshold corresponding to the preset change index, determine whether the preset change index exceeds the change rate threshold, and if it exceeds, send a change overlimit warning signal.

[0022] Further, the device further includes: a curve generation unit, configured to generate a performance metric curve graph according to the test performance report; a curve prediction unit, configured to use a non-linear electrochemistry algorithm to predict a trend prediction curve of the performance metric curve graph; and a test conclusion unit, configured to generate a test conclusion for the battery pack to be tested according to the trend prediction curve.

[0023] To achieve the above object, according to another aspect of the present application, there is provided a computer-readable storage medium, where the storage medium includes a stored program, and the program executes the battery pack test method of any one of the above.

[0024] To achieve the above object, according to another aspect of the present application, there is provided an electronic device, where the electronic device includes one or more processors and a memory, and the memory is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the battery pack test method of any one of the above.

[0025] Through this application, the following steps are adopted: performing charge and discharge tests on the battery pack to be tested, and obtaining long-cycle test data of the battery pack to be tested; analyzing the test working conditions of the long-cycle test data to check whether there are abnormal points in the battery pack to be tested, and outputting the result of abnormal point check; in the case where the result of abnormal point check is passed, inputting the long-cycle test data into a preset algorithm program, and obtaining a test performance report of the battery pack to be tested according to the preset algorithm program, which solves the problem of low efficiency of long-cycle testing of battery packs in the related art. Through the above steps, after collecting the long-cycle test data of the battery pack to be tested, the accuracy of the test data is ensured through test working condition analysis, laying a foundation for subsequent report generation, and then using the preset algorithm program to generate a test performance report, significantly shortening the time-consuming for generating the test performance report, and thus improving the test efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings constituting a part of this application are used to provide a further understanding of this application. The schematic embodiments and descriptions thereof of this application are used to explain this application and do not constitute an improper limitation to this application. In the drawings:

[0027] Figure 1 is a flowchart of a battery pack testing method provided by an embodiment of this application;

[0028] Figure 2 is a flowchart of accuracy verification in an optional battery pack testing method provided by an embodiment of this application;

[0029] Figure 3 is a schematic diagram of a battery pack testing device provided by an embodiment of this application;

[0030] Figure 4 is a schematic diagram of an electronic device provided by an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The following will describe this application in detail with reference to the drawings and in combination with the embodiments.

[0032] In order to enable those skilled in the art to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0033] It should be noted that the terms "first", "second", etc. in the description, claims and the above-mentioned drawings of the present application are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so as to implement the embodiments of the present application described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or devices.

[0034] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this disclosure are all information and data that have been authorized by the user or fully authorized by all parties.

[0035] The present application will be described below in conjunction with preferred implementation steps. Figure 1 is a flowchart of a battery pack testing method provided according to an embodiment of the present application, as Figure 1 shown, the method includes the following steps:

[0036] Step S101, perform charge and discharge tests on the battery pack to be tested, and obtain long-cycle test data of the battery pack to be tested.

[0037] For example, a energy storage battery to be tested is determined as the battery pack to be tested, and the energy storage battery includes a plurality of battery cells. Perform charge and discharge operations on the battery pack to be tested, and obtain key parameters of the battery pack to be tested during the charge and discharge process through sensors. The key parameters include voltage, current and temperature, and transmit these key parameters to the database platform. In the database platform, perform unified automatic conversion of data formatting on these key parameters from different working condition test devices, and store the converted data in a standardized database as long-cycle test data. For example, specifically use the test temperature, charge and discharge current, current cycle number, charge capacity, discharge capacity, and cell voltage as long-cycle test data. These data record the instant state of the battery pack during the long-cycle test and are important bases for generating a battery pack test performance report.

[0038] Step S102, perform test working condition analysis on the long-cycle test data to check whether there are abnormal points in the battery pack to be tested, and output the abnormal point check result.

[0039] For example, in a database platform, there is a threshold alarm calculation module. The threshold alarm calculation module is called to perform a test condition analysis on the long-cycle test data. If the result of the test condition analysis shows that there are no abnormal points in the battery pack to be tested, the abnormal point troubleshooting result is passed; otherwise, the abnormal point troubleshooting result is not passed, and an abnormal warning is output to quickly locate the data abnormal point.

[0040] Step S103, when the abnormal point troubleshooting result is passed, input the long-cycle test data into a preset algorithm program, and obtain a test performance report of the battery pack to be tested according to the preset algorithm program.

[0041] For example, when the abnormal point troubleshooting result is passed, it indicates that the long-cycle test data of the battery pack to be tested is accurate. Call the preset algorithm program to automatically calculate the performance index results corresponding to the long-cycle test data. The performance indexes may include the capacity, capacity efficiency, energy, energy efficiency, cell temperature, single-cell voltage, single-cell voltage difference, etc. of each working step. Aggregate the performance index results as the test performance report.

[0042] For example, the preset algorithm program may include a capacity attenuation model. After inputting the long-cycle test data into the capacity attenuation model, the long-term cycle life of the battery pack to be tested can be automatically output. The preset algorithm program may also include other performance index algorithms to calculate the corresponding performance index results. After collecting all the performance index results, the performance index results output by these preset algorithm programs can be input into a preset report template to generate a test performance report. It should be noted that the preset algorithm program is used as a callable underlying algorithm component in this application. The improvement point of this application lies in the overall solution of generating a test performance report based on long-cycle test data.

[0043] Through the above steps, after collecting the long-cycle test data of the battery pack to be tested, the accuracy of the test data is ensured through the test condition analysis, laying a foundation for the subsequent report generation. Then, use the preset algorithm program to generate a test performance report, shortening the time for test engineers to manually organize the long-cycle test data, statistically analyze and form a test performance report. Therefore, the generation time of the test performance report can be significantly reduced, thereby improving the test efficiency.

[0044] To improve the efficiency of the test condition analysis, optionally, perform a test condition analysis on the long-cycle test data to check whether there are abnormal points in the battery pack to be tested, and the output of the abnormal point troubleshooting result includes: obtaining the pre-set charge and discharge test working step parameters; determining whether the long-cycle test data belongs to the preset interval of the charge and discharge test working step parameters. If it belongs, output that the abnormal point troubleshooting result of the battery pack to be tested is passed.

[0045] For example, before performing charge and discharge tests on a battery pack under test, set the charge and discharge test step parameters corresponding to the battery pack under test. The charge and discharge test step parameters include, but are not limited to, charge and discharge voltage ranges, current limits, temperature conditions, and charge and discharge rates. For example, for a certain battery pack under test, set its charge and discharge voltage range to 2.5V to 3.65V. During the analysis of the test conditions, compare the long-cycle test data collected with the pre-set charge and discharge test step parameters to determine whether the long-cycle test data falls within the preset range of the charge and discharge test step parameters, that is, whether any single-cell voltage falls within the preset range of 2.5V to 3.65V. If so, output that the result of troubleshooting the abnormal points of the battery pack under test is passed, indicating that there are no abnormal points in the battery pack under test under the current test conditions and subsequent steps can be continued. Otherwise, if any single-cell voltage is less than 2.5V or greater than 3.65V, mark it as an abnormal point and output an abnormal warning to further check the status of the battery pack under test and prevent inaccurate data situations.

[0046] Through the above solution, it is possible to effectively and timely detect and eliminate abnormal conditions of the battery pack, avoiding inaccurate data problems caused by abnormal battery packs. At the same time, it also reduces the need for manual intervention, improves the efficiency of test condition analysis, and then improves the automation level and efficiency of the entire test process, increases the reliability of the test, and improves the test efficiency.

[0047] To improve the accuracy of the test performance report, optionally, the test performance report of the battery pack under test obtained according to the preset algorithm program includes: obtaining multiple performance index algorithms in the preset algorithm program; determining multiple performance index results corresponding to the long-cycle test data according to all the performance index algorithms; and generating the test performance report of the battery pack under test according to all the performance index results.

[0048] For example, call the preset algorithm program. The preset algorithm program integrates multiple performance index algorithms for calculating the performance of the battery pack, such as capacity performance index algorithm, capacity efficiency performance index algorithm, energy efficiency performance index algorithm, energy performance index algorithm, cell temperature performance index algorithm, single-cell voltage performance index algorithm, and single-cell voltage difference performance index algorithm. Based on these performance index algorithms, the performance index results corresponding to the long-cycle test data can be automatically calculated. After obtaining all the performance index results, integrate these performance index results to obtain the test performance report.

[0049] Through the above solution, the test performance report can be automatically generated, ensuring the accuracy and timeliness of the test performance report, and improving the overall efficiency of the test and the automation level of data processing.

[0050] To improve the accuracy of the test performance report, optionally, generating a test performance report for the battery pack to be tested based on all performance metric results includes: obtaining a preset weight ratio table, where the preset weight ratio table includes the target weight corresponding to each performance metric result; determining the weighted results corresponding to all performance metric results based on all the target weights in the preset weight ratio table; and generating a test performance report for the battery pack to be tested based on all the weighted results.

[0051] For example, multiple performance metric results can be as follows: the capacity retention rate is 85%, the energy efficiency is 88%, the maximum temperature difference is 5°C (ideally as small as possible), and the change rate of the monomer voltage difference is 1.2% / cycle (ideally as low as possible). The preset weight ratio table can be as follows: the target weight of the capacity retention rate is 40%, the target weight of the energy efficiency is 30%, the target weight of the maximum temperature difference is 20%, and the target weight of the change rate of the monomer voltage difference is 10%. Each target weight can be multiplied by the corresponding performance metric result to obtain the weighted result corresponding to this performance metric result, and then summing all the weighted results can obtain the overall score of 61.52%, which is used as one of the contents in the test performance report.

[0052] In summary, through the above weighting method, the coupled analysis of multiple performance metric results is achieved, and the obtained test performance report can more accurately reflect the comprehensive performance level of the battery pack, improving the accuracy of the test performance report.

[0053] To improve the accuracy of the test, optionally, before obtaining multiple performance metric algorithms in the preset algorithm program, it further includes: obtaining a new interface address of the preset performance metric algorithm as the sub-algorithm to be added to the preset performance metric algorithm, where the preset performance metric algorithm is any one of the performance metric algorithms in the preset algorithm program; performing accuracy verification on the sub-algorithm to be added to the preset performance metric algorithm based on the labeled dataset; if the verification passes, updating the preset performance metric algorithm based on the sub-algorithm to be added to the preset performance metric algorithm.

[0054] For example, the preset performance metric algorithm in the preset algorithm program is set to an updatable algorithm. During the development and iteration of the preset algorithm program, new algorithms are continuously provided. The new algorithms provide services in the form of interfaces and are used to more precisely evaluate the performance metrics of the battery pack to be tested. This new algorithm is the sub-algorithm to be added. The interface address is obtained to call the sub-algorithm to be added in the preset algorithm program. The interface address includes the IP and port number, such as 192.168.10.112:8878, where 192.168.10.112 is the IP and 8878 is the port number. To ensure the accuracy of the sub-algorithm to be added, this embodiment uses the labeled dataset to perform accuracy verification on it. The labeled dataset is obtained by labeling historical test data and thus contains the true performance metrics under different long-cycle test data. By comparing the calculation results of the sub-algorithm to be added with the true performance metrics, the accuracy of the sub-algorithm to be added can be determined. If the result of the accuracy verification passes, the sub-algorithm to be added is integrated into the preset algorithm program to update the original performance metric algorithm. After the update, the preset algorithm program will include a more precise performance evaluation ability, thereby improving the quality of the test performance report. The update of the performance metric algorithm can be completed in the form of interface replacement. Assume that the preset performance metric algorithm calls the sub-algorithm at 192.168.10.112:8876 before the update and is replaced by calling the sub-algorithm at 192.168.10.112:8878 after the update.

[0055] Through the above solution, not only the continuous optimization and update of the preset performance metric algorithm are ensured, but also the accuracy of the sub-algorithm to be added is ensured through a strict verification mechanism, thereby improving the accuracy of the entire test. In addition, by using the new interface address to add the sub-algorithm to be added, the flexibility and scalability of the preset performance metric algorithm are also improved.

[0056] Figure 2 It is the flowchart of the accuracy verification in the optional battery pack test method provided by the embodiment of the present application. As Figure 2 shown, to improve the accuracy of the test, optionally, the accuracy verification of the sub-algorithm to be added to the preset performance metric algorithm based on the labeled dataset includes the following steps:

[0057] Step S201, add the sub-algorithm to be added to the preset performance metric algorithm into the existing sub-algorithm set of the preset performance metric algorithm to obtain a new sub-algorithm set.

[0058] For example, if the existing sub - algorithm set of the preset performance index algorithm is [a1, a2, a3], then the preset performance index algorithm is obtained by weighting the three sub - algorithms a1, a2, and a3 before update. That is, for the long - loop test data x, input x into the a1 sub - algorithm to get y1, input x into the a2 sub - algorithm to get y2, input x into the a3 sub - algorithm to get y3, then the performance index result calculated by the preset performance index algorithm is the weighted sum of y1, y2, and y3. The sub - algorithm to be added is a4, and adding the sub - algorithm to be added to the existing sub - algorithm set gives a new sub - algorithm set [a1, a2, a3, a4].

[0059] Step S202: Perform different weighting ratios on multiple sub - algorithms in the new sub - algorithm set to form multiple sub - algorithm weighted combinations, and determine the accuracy of all sub - algorithm weighted combinations based on the labeled data set.

[0060] For example, perform different weighting ratios on all sub - algorithms in the new sub - algorithm set to form multiple sub - algorithm weighted combinations. Assume that the result obtained by inputting x into the a4 sub - algorithm is y4. Then, according to different weighting ratios, the sub - algorithm weighted combination can be (10%y1 + 20%y2 + 30%y3 + 40%y4), or (30%y2 + 50%y3 + 20%y4), or (55%y2 + 45%y4). Use the labeled data set to compare the calculation results of all sub - algorithm weighted combinations to determine the accuracy of all sub - algorithm weighted combinations, and determine the sub - algorithm weighted combination with the highest accuracy. If the sub - algorithm weighted combination with the highest accuracy contains a4, which can be (30%y2 + 30%y3 + 40%y4) or (100%y4), then output the result that the sub - algorithm to be added passes the verification. In other words, only when adding the sub - algorithm to be added to the sub - algorithm set can provide a positive contribution is it determined to pass the verification, and the accuracy of the sub - algorithm weighted combination containing a4 is higher than that of the sub - algorithm weighted combination without a4.

[0061] Step S203: If the sub - algorithm weighted combination with the highest accuracy contains the sub - algorithm to be added, then output that it passes the verification.

[0062] For example, in the case where the accuracy verification is a weighted combination, the preset performance index algorithm is also a weighted combination algorithm of multiple sub - algorithms. The update of the preset performance index algorithm is to use the sub - algorithm weighted combination with the highest accuracy as the updated preset performance index algorithm, and at the same time use the sub - algorithms in the sub - algorithm weighted combination with the highest accuracy as the new existing sub - algorithm set.

[0063] Through the above solution, the sub-algorithm weighted combination method is used to verify the sub-algorithm to be added. Such a verification mechanism helps to deeply determine the effect of the sub-algorithm to be added (for the case where only a4 cannot directly improve the accuracy of the preset performance index algorithm, but the accuracy of the preset performance index algorithm can be improved after a4 is weighted and combined with the existing sub-algorithm set, the above solution can capture the possibility of such accuracy improvement), so as to ensure the update effect of the preset performance index algorithm, improve the accuracy of generating performance index results using the performance index algorithm, and further improve the accuracy of the test.

[0064] To improve the security of the test, optionally, after determining the performance index result corresponding to the long-cycle test data according to the performance index algorithm, the battery pack test method of the embodiment of the present application further includes: determining a preset change index of the battery pack to be tested in a single cycle according to the performance index result, where the preset change index includes at least one of a capacity efficiency change rate, an energy efficiency change rate, a cell voltage difference change rate, and a cell temperature difference change rate; obtaining a change rate threshold corresponding to the preset change index, and determining whether the preset change index exceeds the change rate threshold. If it exceeds, a change limit warning signal is issued.

[0065] For example, after calculating the capacity efficiency, energy efficiency, cell voltage difference, and cell temperature difference of the battery pack to be tested corresponding to the long-cycle test data, further calculate the change rates of these performance indexes in the current single cycle, that is, the rate at which the performance indexes change with the number of cycles. The change rate of any one performance index can be the quotient of the change amount of the performance index result and the performance index result of the previous cycle. The change amount of the performance index result is the difference between the performance index result of the current cycle and the performance index result of the previous cycle. For example, the calculation method of the capacity efficiency change rate is to first calculate the difference between the capacity efficiency of the current cycle and the capacity efficiency of the previous cycle, and then divide the difference by the capacity efficiency of the previous cycle. The preset change index can be one or more of the capacity efficiency change rate, the energy efficiency change rate, the cell voltage difference change rate, and the cell temperature difference change rate. The change rate threshold corresponding to the preset change index is used to distinguish the performance change of the battery pack to be tested from abnormal attenuation. If the preset change index exceeds the corresponding change rate threshold, a change limit warning signal is issued. The change limit warning signal can be that the battery pack to be tested shows accelerated attenuation to prompt the test risk.

[0066] Through the above solution, the present application not only checks for abnormal points through test condition analysis before generating the test performance report, but also detects whether the preset change index exceeds the limit after the test performance report is generated. Such a dual detection mechanism helps to ensure the security of the test.

[0067] To improve the effectiveness of the test method of the present application, optionally, after obtaining the test performance report of the battery pack to be tested according to the preset algorithm program, the battery pack test method of the embodiments of the present application further includes: generating a performance index curve graph according to the test performance report; predicting the trend prediction curve of the performance index curve graph by using the non-linear electrochemistry algorithm; generating a test conclusion for the battery pack to be tested according to the trend prediction curve.

[0068] For example, the performance index results of the battery pack to be tested are included in the test performance report. A performance index curve graph is generated according to the performance index results. For example, a curve graph of capacity efficiency versus cycle number is generated based on the capacity efficiency, showing the curve of the battery pack capacity efficiency decreasing with the increase of the cycle number in the long cycle test. The non-linear electrochemistry algorithm is a prediction model based on the battery electrochemistry principle, which can consider the complex non-linear reactions inside the battery and more accurately predict the decay trend of the battery performance over time or cycle number. The existing performance index results are processed by using the non-linear electrochemistry algorithm to generate a trend prediction curve for predicting the subsequent trend of the performance index curve graph, so as to reflect the expected changes in the performance of the battery pack to be tested in future cycles or use. The preset conclusion template is called, and the performance index results, the performance index curve graph, and the trend prediction curve are embedded into the corresponding positions of the preset conclusion template to generate a test conclusion for the battery pack to be tested.

[0069] Through the above solution, a further test conclusion including forward-looking prediction can be obtained, which not only includes the performance in the current test cycle, but also can predict the future performance change trend, helps to adjust the test strategy and optimize the battery pack design scheme in time, and improves the effectiveness of the test method.

[0070] In summary, for the battery pack test method provided by the embodiments of the present application, the charge and discharge test is performed on the battery pack to be tested, and the long cycle test data of the battery pack to be tested is obtained; the test working conditions of the long cycle test data are analyzed to check whether there are abnormal points in the battery pack to be tested, and the abnormal point check result is output; when the abnormal point check result is passed, the long cycle test data is input into the preset algorithm program, and the test performance report of the battery pack to be tested is obtained according to the preset algorithm program, which solves the problem of low efficiency of the long cycle test of the battery pack in the related technology. Through the above steps, after collecting the long cycle test data of the battery pack to be tested, the accuracy of the test data is ensured through the test working condition analysis, which lays a foundation for the subsequent report generation, and then the test performance report is generated by using the preset algorithm program, significantly shortening the generation time of the test performance report, and thus improving the test efficiency.

[0071] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0072] The embodiment of the present application also provides a battery pack testing device. It should be noted that the battery pack testing device in the embodiment of the present application can be used to execute the battery pack testing method provided by the embodiment of the present application. The following introduces the battery pack testing device provided by the embodiment of the present application.

[0073] Figure 3 is a schematic diagram of a battery pack testing device according to an embodiment of the present application. As Figure 3 shown, the device includes: a data acquisition unit 301, an abnormality troubleshooting unit 302, and a report acquisition unit 303.

[0074] The data acquisition unit 301 is used to perform charge and discharge tests on the battery pack to be tested and obtain long-cycle test data of the battery pack to be tested.

[0075] The abnormality troubleshooting unit 302 is used to perform test condition analysis on the long-cycle test data to troubleshoot whether there are abnormal points in the battery pack to be tested and output the troubleshooting result of the abnormal points.

[0076] The report acquisition unit 303 is used to, when the troubleshooting result of the abnormal points is passed, input the long-cycle test data into a preset algorithm program and obtain a test performance report of the battery pack to be tested according to the preset algorithm program.

[0077] The battery pack testing device provided by the embodiment of the present application performs charge and discharge tests on the battery pack to be tested through the data acquisition unit 301 and obtains long-cycle test data of the battery pack to be tested; the abnormality troubleshooting unit 302 performs test condition analysis on the long-cycle test data to troubleshoot whether there are abnormal points in the battery pack to be tested and outputs the troubleshooting result of the abnormal points; the report acquisition unit 303, when the troubleshooting result of the abnormal points is passed, inputs the long-cycle test data into a preset algorithm program and obtains a test performance report of the battery pack to be tested according to the preset algorithm program, solving the problem of low efficiency in the long-cycle test of the battery pack in the related art. After collecting the long-cycle test data of the battery pack to be tested, the accuracy of the test data is ensured through test condition analysis, laying a foundation for subsequent report generation, and then using the preset algorithm program to generate a test performance report, significantly shortening the generation time of the test performance report, and thus improving the test efficiency.

[0078] Optionally, in the battery pack testing device provided in the embodiments of the present application, the anomaly troubleshooting unit 302 includes: a parameter reading module, configured to obtain the pre-set charge and discharge test step parameters; an anomaly determination module, configured to determine whether the long-cycle test data belongs to a preset interval of the charge and discharge test step parameters, and if so, output that the anomaly point troubleshooting result of the battery pack to be tested passes.

[0079] Optionally, in the battery pack testing device provided in the embodiments of the present application, the report acquisition unit 303 includes: an algorithm reading module, configured to obtain a plurality of performance index algorithms in the preset algorithm program; an index calculation module, configured to determine a plurality of performance index results corresponding to the long-cycle test data according to all the performance index algorithms; a report generation module, configured to generate a test performance report of the battery pack to be tested according to all the performance index results.

[0080] Optionally, the report generation module includes: a table acquisition sub-module, configured to obtain a preset weight ratio table, where the preset weight ratio table includes the target weight corresponding to each performance index result; a weighted calculation sub-module, configured to determine the weighted results corresponding to all the performance index results according to all the target weights in the preset weight ratio table; a weighted generation sub-module, configured to generate a test performance report of the battery pack to be tested according to all the weighted results.

[0081] Optionally, in the battery pack testing device provided in the embodiments of the present application, the report acquisition unit 303 further includes: an interface acquisition module, configured to obtain a new interface address of a preset performance index algorithm as a sub-algorithm to be added to the preset performance index algorithm before obtaining a plurality of performance index algorithms in the preset algorithm program, where the preset performance index algorithm is any one of the performance index algorithms in the preset algorithm program; a verification module, configured to perform accuracy verification on the sub-algorithm to be added to the preset performance index algorithm according to the labeled data set; an update module, configured to update the preset performance index algorithm according to the sub-algorithm to be added to the preset performance index algorithm if the verification passes.

[0082] Optionally, in the battery pack testing device provided in the embodiments of the present application, the verification module includes: an addition sub-module, configured to add the sub-algorithm to be added to the preset performance index algorithm to the existing sub-algorithm set of the preset performance index algorithm to obtain a new sub-algorithm set; an accuracy calculation sub-module, configured to perform different weighted ratios on a plurality of sub-algorithms in the new sub-algorithm set to form a plurality of sub-algorithm weighted combinations, and determine the accuracy of all the sub-algorithm weighted combinations according to the labeled data set; a verification output sub-module, configured to output that the verification passes if the sub-algorithm to be added is included in the sub-algorithm weighted combination with the highest accuracy.

[0083] Optionally, in the battery pack testing device provided in the embodiments of the present application, the report acquisition unit 303 further includes: a change index module, configured to determine a preset change index of the battery pack to be tested in a single cycle according to the performance index result, where the preset change index includes at least one of a capacity efficiency change rate, an energy efficiency change rate, a monomer voltage difference change rate, and a single body temperature difference change rate; an overlimit judgment module, configured to obtain a change rate threshold corresponding to the preset change index, determine whether the preset change index exceeds the change rate threshold, and if it exceeds, send out a change overlimit warning signal.

[0084] Optionally, in the battery pack testing device provided in the embodiments of the present application, the device further includes: a curve generation unit, configured to generate a performance index curve graph according to the test performance report; a curve prediction unit, configured to use a non-linear electrochemistry algorithm to predict a trend prediction curve of the performance index curve graph; a test conclusion unit, configured to generate a test conclusion for the battery pack to be tested according to the trend prediction curve.

[0085] The battery pack testing device includes a processor and a memory. The above data acquisition unit 301, anomaly troubleshooting unit 302, report acquisition unit 303, etc. are all stored in the memory as program units, and the corresponding functions are implemented by the processor executing the above program units stored in the memory.

[0086] The processor contains a kernel, and the kernel is used to retrieve the corresponding program unit from the memory. One or more kernels can be set, and the battery pack is tested by adjusting the kernel parameters.

[0087] The memory may include non-permanent memory in a computer-readable medium, forms such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.

[0088] The embodiments of the present application provide a computer-readable storage medium, on which a program is stored, and when the program is executed by a processor, the battery pack testing method is implemented.

[0089] The embodiments of the present application provide a processor, and the processor is used to run a program, where when the program runs, the battery pack testing method is executed.

[0090] As Figure 4As shown in the figure, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program stored on the memory and executable on the processor. When the processor executes the program, the following steps are implemented: performing charge and discharge tests on the battery pack to be tested, and obtaining long-cycle test data of the battery pack to be tested; performing test condition analysis on the long-cycle test data to check whether there are abnormal points in the battery pack to be tested, and outputting the abnormal point check result; in the case where the abnormal point check result is passed, inputting the long-cycle test data into a preset algorithm program, and obtaining a test performance report of the battery pack to be tested according to the preset algorithm program.

[0091] When the processor executes the program, the following steps are also implemented: performing test condition analysis on the long-cycle test data to check whether there are abnormal points in the battery pack to be tested, and outputting the abnormal point check result, including: obtaining the preset charge and discharge test step parameters; determining whether the long-cycle test data belongs to the preset interval of the charge and discharge test step parameters, and if so, outputting that the abnormal point check result of the battery pack to be tested is passed.

[0092] When the processor executes the program, the following steps are also implemented: obtaining the test performance report of the battery pack to be tested according to the preset algorithm program, including: obtaining multiple performance index algorithms in the preset algorithm program; determining multiple performance index results corresponding to the long-cycle test data according to all the performance index algorithms; generating a test performance report of the battery pack to be tested according to all the performance index results.

[0093] When the processor executes the program, the following steps are also implemented: obtaining a preset weight ratio table, where the preset weight ratio table includes the target weight corresponding to each performance index result; determining the weighted result corresponding to all the performance index results according to all the target weights in the preset weight ratio table; generating a test performance report of the battery pack to be tested according to all the weighted results.

[0094] When the processor executes the program, the following steps are also implemented: before obtaining multiple performance index algorithms in the preset algorithm program, it also includes: obtaining a new interface address of the preset performance index algorithm as the sub-algorithm to be added to the preset performance index algorithm, where the preset performance index algorithm is any one of the performance index algorithms in the preset algorithm program; performing accuracy verification on the sub-algorithm to be added to the preset performance index algorithm according to the labeled data set; if the verification passes, updating the preset performance index algorithm according to the sub-algorithm to be added to the preset performance index algorithm.

[0095] When the processor executes the program, the following steps are also implemented: performing accuracy verification on the sub-algorithm to be added of the preset performance index algorithm according to the labeled data set, including: adding the sub-algorithm to be added of the preset performance index algorithm into the existing sub-algorithm set of the preset performance index algorithm to obtain a new sub-algorithm set; performing different weighted ratios on multiple sub-algorithms in the new sub-algorithm set to form multiple weighted combinations of sub-algorithms, and determining the accuracy of all the weighted combinations of sub-algorithms according to the labeled data set; if the weighted combination of sub-algorithms with the highest accuracy contains the sub-algorithm to be added, outputting that the verification is passed.

[0096] When the processor executes the program, the following steps are also implemented: after determining the performance index result corresponding to the long-cycle test data according to the performance index algorithm, the method further includes: determining a preset change index of the battery pack to be tested in a single cycle according to the performance index result, where the preset change index includes at least one of a capacity efficiency change rate, an energy efficiency change rate, a monomer voltage difference change rate, and a single-body temperature difference change rate; obtaining a change rate threshold corresponding to the preset change index, and determining whether the preset change index exceeds the change rate threshold, and if it exceeds, sending a change-overlimit warning signal.

[0097] When the processor executes the program, the following steps are also implemented: after obtaining the test performance report of the battery pack to be tested according to the preset algorithm program, the method further includes: generating a performance index curve graph according to the test performance report; predicting a trend prediction curve of the performance index curve graph by using a non-linear electrochemistry algorithm; generating a test conclusion for the battery pack to be tested according to the trend prediction curve.

[0098] The present application also provides a computer program product, which is suitable for executing a program initialized with the following method steps when executed on a data processing device: performing charge and discharge tests on a battery pack to be tested, and obtaining long-cycle test data of the battery pack to be tested; performing test condition analysis on the long-cycle test data to check whether there are abnormal points in the battery pack to be tested, and outputting an abnormal point check result; in the case where the abnormal point check result is passed, inputting the long-cycle test data into a preset algorithm program, and obtaining a test performance report of the battery pack to be tested according to the preset algorithm program.

[0099] When executed on a data processing device, it is also suitable for executing a program initialized with the following method steps: performing test condition analysis on the long-cycle test data to check whether there are abnormal points in the battery pack to be tested, and outputting an abnormal point check result, including: obtaining preset charge and discharge test step parameters; determining whether the long-cycle test data belongs to a preset interval of the charge and discharge test step parameters, and if it belongs, outputting that the abnormal point check result of the battery pack to be tested is passed.

[0100] When executed on a data processing device, it is also suitable for executing a program initialized with the following method steps: obtaining a test performance report of the battery pack to be tested according to the preset algorithm program, including: obtaining a plurality of performance index algorithms in the preset algorithm program; determining a plurality of performance index results corresponding to the long cycle test data according to all the performance index algorithms; generating a test performance report of the battery pack to be tested according to all the performance index results.

[0101] When executed on a data processing device, it is also suitable for executing a program initialized with the following method steps: obtaining a test performance report of the battery pack to be tested according to the preset algorithm program, including: obtaining a preset weight ratio table, where the preset weight ratio table includes the target weight corresponding to each performance index result; determining the weighted results corresponding to all performance index results according to all the target weights in the preset weight ratio table; generating a test performance report of the battery pack to be tested according to all the weighted results.

[0102] When executed on a data processing device, it is also suitable for executing a program initialized with the following method steps: before obtaining a plurality of performance index algorithms in the preset algorithm program, it further includes: obtaining a new interface address of the preset performance index algorithm as the sub-algorithm to be added to the preset performance index algorithm, where the preset performance index algorithm is any one of the performance index algorithms in the preset algorithm program; performing accuracy verification on the sub-algorithm to be added to the preset performance index algorithm according to the labeled data set; if the verification passes, updating the preset performance index algorithm according to the sub-algorithm to be added to the preset performance index algorithm.

[0103] When executed on a data processing device, it is also suitable for executing a program initialized with the following method steps: performing accuracy verification on the sub-algorithm to be added to the preset performance index algorithm according to the labeled data set, including: adding the sub-algorithm to be added to the preset performance index algorithm to the existing sub-algorithm set of the preset performance index algorithm to obtain a new sub-algorithm set; performing different weighted ratios on the multiple sub-algorithms in the new sub-algorithm set to form multiple sub-algorithm weighted combinations, and determining the accuracy of all the sub-algorithm weighted combinations according to the labeled data set; if the sub-algorithm weighted combination with the highest accuracy contains the sub-algorithm to be added, outputting that the verification passes.

[0104] When executed on a data processing device, it is also suitable for executing a program initialized with the following method steps: After determining the performance index result corresponding to the long-cycle test data according to the performance index algorithm, the method further includes: According to the performance index result, determining a preset change index of the battery pack to be tested in a single cycle, where the preset change index includes at least one of a capacity efficiency change rate, an energy efficiency change rate, a single-cell voltage difference change rate, and a single-cell temperature difference change rate; obtaining a change rate threshold corresponding to the preset change index, and determining whether the preset change index exceeds the change rate threshold. If it exceeds, a change-overlimit warning signal is issued.

[0105] When executed on a data processing device, it is also suitable for executing a program initialized with the following method steps: After obtaining the test performance report of the battery pack to be tested according to the preset algorithm program, the method further includes: Generating a performance index curve graph according to the test performance report; predicting a trend prediction curve of the performance index curve graph by using a non-linear electrochemistry algorithm; generating a test conclusion for the battery pack to be tested according to the trend prediction curve.

[0106] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0107] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0108] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the processes in Figure 1one or more processes and / or blocks Figure 1 the functions specified in one or more blocks.

[0109] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more processes and / or blocks Figure 1 the one or more blocks.

[0110] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0111] The memory may include non-permanent memory in the computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

[0112] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can store information by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0113] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0114] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0115] The above are only the embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A battery pack testing method, characterized in that, Including: Performing charge and discharge tests on the battery pack to be tested, and obtaining long-cycle test data of the battery pack to be tested; Performing test condition analysis on the long-cycle test data to check whether there are abnormal points in the battery pack to be tested, and outputting an abnormal point check result; When the abnormal point check result is passed, inputting the long-cycle test data into a preset algorithm program, and obtaining a test performance report of the battery pack to be tested according to the preset algorithm program.

2. The method according to claim 1, wherein Performing test condition analysis on the long-cycle test data to check whether there are abnormal points in the battery pack to be tested, and outputting an abnormal point check result includes: Obtaining preset charge and discharge test step parameters; Determining whether the long-cycle test data belongs to a preset interval of the charge and discharge test step parameters, and if so, outputting that the abnormal point check result of the battery pack to be tested is passed.

3. The method according to claim 1, wherein Obtaining a test performance report of the battery pack to be tested according to the preset algorithm program includes: Obtaining multiple performance index algorithms in the preset algorithm program; Determining multiple performance index results corresponding to the long-cycle test data according to all the performance index algorithms; Generating a test performance report of the battery pack to be tested according to all the performance index results.

4. The method according to claim 3, wherein Generating a test performance report of the battery pack to be tested according to all the performance index results includes: Obtaining a preset weight ratio table, where the preset weight ratio table includes target weights corresponding to each performance index result; Determining weighted results corresponding to all the performance index results according to all the target weights in the preset weight ratio table; Generating a test performance report of the battery pack to be tested according to all the weighted results.

5. The method according to claim 3, wherein Before obtaining multiple performance index algorithms in the preset algorithm program, it further includes: Obtaining a new interface address of a preset performance index algorithm as a sub-algorithm to be added to the preset performance index algorithm, where the preset performance index algorithm is any one of the performance index algorithms in the preset algorithm program; Performing accuracy verification on the sub-algorithm to be added to the preset performance index algorithm according to a labeled data set; If the verification is passed, updating the preset performance index algorithm according to the sub-algorithm to be added to the preset performance index algorithm.

6. The method according to claim 5, wherein Performing accuracy verification on the sub-algorithm to be added to the preset performance index algorithm according to a labeled data set includes: Adding the sub-algorithm to be added to the preset performance index algorithm to an existing sub-algorithm set of the preset performance index algorithm to obtain a new sub-algorithm set; Performing different weighted ratios on multiple sub-algorithms in the new sub-algorithm set to form multiple sub-algorithm weighted combinations, and determining the accuracy of all the sub-algorithm weighted combinations according to the labeled data set; If the sub-algorithm weighted combination with the highest accuracy contains the sub-algorithm to be added, outputting that the verification is passed.

7. The method according to any one of claims 3-6, characterized in that After determining the performance index results corresponding to the long-cycle test data according to the performance index algorithm, the method further includes: Based on the results of the performance indicators, determine the preset change indicators of the battery pack to be tested in a single cycle, where the preset change indicators include at least one of the capacity efficiency change rate, energy efficiency change rate, monomer voltage difference change rate, and single body temperature difference change rate; Obtain the change rate threshold corresponding to the preset change indicator, and determine whether the preset change indicator exceeds the change rate threshold. If it exceeds, send a change limit warning signal.

8. The method according to any one of claims 1-6, characterized in that, After obtaining the test performance report of the battery pack to be tested according to the preset algorithm program, the method further includes: Generate a performance indicator curve graph based on the test performance report; Use a non-linear electrochemical algorithm to predict the trend prediction curve of the performance indicator curve graph; Generate a test conclusion for the battery pack to be tested based on the trend prediction curve.

9. A computer-readable storage medium, characterized in that, The storage medium includes a stored program, where the program executes the battery pack test method according to any one of claims 1 to 8.

10. An electronic device, characterized in that, Includes one or more processors and a memory, where the memory is used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the battery pack test method according to any one of claims 1 to 8.

Images