A battery pack consistency evaluation method and system

Abstract

The present invention provides a battery pack consistency evaluation method and system, the method includes: collecting and obtaining test samples, and establishing the SOC module minimum voltage value curve during the charging and discharging process; comparing the SOC module minimum voltage value curve during the charging and discharging process, converting the maximum and minimum voltages of the module during the charging and discharging stage to obtain the corresponding SOC values, and calculating ΔSOC to establish a regression equation and a SOC ΔSOC curve during the charging and discharging process, selecting no less than 2 groups of test samples, and establishing the standard SOC ΔSOC confidence interval during the charging and discharging process; S3, collecting the test data of the factory battery pack, and comparing and processing the test data with the standard SOC ΔSOC confidence interval during the charging and discharging process to obtain the preset confidence interval exceeding ratio, and judging the test data, and judging the battery pack exceeding ratio data and discreteness data, so as to obtain the consistency estimation result of the factory battery pack. The technical problem that the prior art lacks the evaluation of the entire test process and the estimation accuracy is not high is solved.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a battery pack consistency evaluation method and system. Background Art

[0002] Lithium-ion batteries are the core components of electric vehicles, and the performance of the battery pack directly determines the performance of the electric vehicle. Since the battery pack is composed of multiple modules connected in series, the consistency of these modules directly determines the performance of the entire battery pack.

[0003] At present, the main way to check the consistency of battery packs is to judge the pressure difference. The consistency is judged by the dynamic pressure difference and static pressure difference at the end of charging and discharging in the electrical performance test. This method has two main drawbacks in evaluating the consistency of modules in the battery pack. First, this method only evaluates the two time points of charging end and discharging end during the entire electrical performance test, and does not evaluate the entire test process. Second, since the battery voltage and SOC are not linearly related, the SOC corresponding pressure difference at different stages is inconsistent. It is not accurate enough to evaluate the consistency only by the pressure difference. The existing invention patent application document "A method for describing battery consistency" with the publication number CN110031771A includes the following steps: S1, the real-time charging curves of all single cells in the target lithium-ion battery are processed, the characteristic values ​​of all single cells are extracted, and the charging capacity of the corresponding points of the characteristic values ​​is recorded; S2, the charging capacity of the corresponding points of the characteristic values ​​obtained in S1 is used as the input parameter of the algorithm model to calculate the SOC distribution value of all single cells in the battery pack; S3, the SOC distribution value of all single cells in the battery pack obtained in S2 is used as the input parameter of the battery consistency description to describe the battery consistency. The technical solution disclosed in the existing document is different from the technical solution of the present application. The existing document does not fully disclose the technical features of the present application, and the existing document is used to describe battery consistency, while the present application is used to evaluate the consistency of battery packs. The technical problems solved by the existing application document and the present application are also different, and the technical effect of the present application cannot be achieved. The existing invention patent application document "Battery Module Voltage Consistency Evaluation Method, Device, Equipment and Medium" with publication number CN114094218A obtains at least one attribute parameter of the battery module to be tested in at least two time periods; each of the time periods includes at least one moment; each attribute parameter in different time periods is input into a pre-trained regression forest model to obtain at least one moment voltage corresponding to each time period; a state sequence corresponding to each time period is generated according to each moment voltage, and the voltage consistency of the battery module to be tested is evaluated according to each state sequence. It can be seen from the contents of the patent specification that the existing application document uses a pre-trained regression forest model to process voltage data and obtains the battery parameter state sequence through confidence interval prediction. Its specific implementation technical solution is different from that of the present application, and the calculation logic used is also quite different from that of the present application, and it cannot achieve the technical effect of the present application.

[0004] In summary, the existing technology lacks technical problems of evaluating the entire testing process and has low estimation accuracy. Summary of the invention

[0005] The technical problem to be solved by the present invention is how to solve the technical problem that the prior art lacks the ability to evaluate the entire test process and has low estimation accuracy.

[0006] The present invention adopts the following technical solution to solve the above technical problem: A battery pack consistency evaluation method includes:

[0007] S1. Collecting and acquiring test data as test samples, and establishing SOC-module minimum voltage value curves during charging and discharging according to the test samples;

[0008] S2. By comparing the SOC-module minimum voltage curve during the charging and discharging process, the maximum module voltage and the minimum module voltage during the charging and discharging stage are converted to obtain corresponding SOC values, and ΔSOC is calculated to establish a regression equation, a charging process SOC-ΔSOC curve, and a discharging process SOC-ΔSOC curve, and at least 2 groups of the test samples are selected to respectively establish a charging process standard SOC-ΔSOC confidence interval and a discharging process standard SOC-ΔSOC confidence interval;

[0009] S3. Collect the test data of the factory battery pack, and compare and process the test data with the standard SOC-ΔSOC confidence interval of the charging process and the standard SOC-ΔSOC confidence interval of the discharging process to obtain the preset confidence interval excess ratio, and determine the excess ratio data and dispersion data of the factory battery pack according to the test data to obtain the consistency estimation result of the factory battery pack.

[0010] The present invention first calculates ΔSOC to establish a regression equation and a SOC-ΔSOC curve for the charging and discharging process, selects no less than 2 groups of test samples, and respectively establishes a standard SOC-ΔSOC confidence interval for the charging and discharging process, and compares the test data of the factory battery with the standard SOC-ΔSOC confidence interval. If it exceeds or exceeds a certain proportion, it can be considered that it does not meet the requirements and is judged as abnormal. The greater the excess proportion, the greater the discreteness, and the worse the consistency of the battery pack. The evaluation method provided by the present invention can effectively monitor and determine the consistency of the battery pack during the charging and discharging process of the factory test, and can perform targeted cause analysis based on the time and location of the abnormality.

[0011] In a more specific technical solution, step S2 includes:

[0012] S21, referring to the SOC-module minimum voltage curve, converting the module maximum voltage and module minimum voltage corresponding to the SOC in the charging process and the discharging process into corresponding SOC values ​​respectively;

[0013] S22, processing the SOC of the maximum voltage of the module and the SOC of the minimum voltage of the module with a preset logic to obtain a difference ΔSOC between the maximum voltage value SOC of the module and the minimum SOC of the module;

[0014] S23, calculating the ΔSOC corresponding to the different SOCs according to a preset logic to establish a regression equation, the charging process SOC-ΔSOC curve, and the discharging process SOC-ΔSOC curve;

[0015] S24, selecting at least 2 groups of the test samples, and using preset statistical logic to respectively establish standard SOC-ΔSOC confidence intervals for the charge and discharge process.

[0016] The present invention establishes a regression equation based on the ΔSOC corresponding to different SOCs obtained by calculation, obtains the SOC-ΔSOC curve of the charging process and the SOC-ΔSOC curve of the discharging process, selects multiple groups of sample test data according to the above method, and uses statistical methods to respectively establish standard SOC-ΔSOC confidence intervals for the charging process and the discharging process, thereby solving the technical problem of incomplete testing and low accuracy caused by the traditional method of inspecting the consistency of battery packs, which is that the consistency is judged by specific parameters such as battery voltage difference and charge and discharge cut-off, and thus improves the accuracy of battery pack consistency evaluation.

[0017] In a more specific technical solution, in step S22, the difference ΔSOC between the maximum voltage value SOC of the module and the minimum SOC of the module is calculated using the following logic:

[0018] ΔSOC=SOC vmax -SOC Vmin

[0019] , where SOC Vmax SOC is the maximum voltage value of the module, SOC Vmin This is the module minimum value.

[0020] In a more specific technical solution, step S2 includes:

[0021] S241, randomly selecting no less than 2 test samples, and calculating a test curve based on the samples;

[0022] S242, calculating the difference ΔSOC between the maximum voltage value SOC of the module and the minimum SOC of the module corresponding to the test curve at different SOCs, and generating a ΔSOC normal distribution diagram accordingly;

[0023] S243, processing the ΔSOC normal distribution graph to obtain a sample mean and a standard deviation;

[0024] S244. Calculate the confidence interval according to the present mean and the standard deviation to obtain a standard confidence interval under 0% to 100% SOC.

[0025] In a more specific technical solution, in step 2 and step 3, the capacity value of the charging stage and the capacity value of the discharging stage are acquired and processed to obtain the SOC value.

[0026] In a more specific technical solution, the SOC value corresponds one-to-one to the minimum value of the module voltage in the battery pack.

[0027] In a more specific technical solution, the following logic is used in step S21 to calculate the SOC value in the charging stage:

[0028]

[0029] , where SOC C is the SOC during the charging phase, C C is the capacity of the battery pack currently charged, It is the total capacity charged into the battery pack from the beginning to the end of charging.

[0030] In a more specific technical solution, the following logic is used in step S21 to calculate the SOC value in the discharge phase:

[0031]

[0032] , where SOC D is the SOC in the discharge phase, C D is the capacity of the current battery pack that has been discharged. It is the total capacity discharged from the battery pack from the start to the end of discharge.

[0033] The present invention adopts the difference between the module's maximum voltage value SOC and the module's minimum SOC, and uses a specific algorithm to calculate the SOC value in the charging stage and the SOC value in the discharging stage, thereby avoiding the technical problems in the prior art of only using parameters such as battery voltage to evaluate the consistency of the battery pack and the low accuracy caused by the inconsistent pressure difference corresponding to the SOC in different stages.

[0034] In a more specific technical solution, step S3 includes:

[0035] S31, establishing SOC-module minimum voltage value curves during charging and discharging according to the data to be tested;

[0036] S32, referring to the SOC-module minimum voltage curve, converting the maximum module voltage and the minimum module voltage of the battery pack during the charging and discharging phases into corresponding SOC values ​​respectively;

[0037] S33, obtaining ΔSOC by subtracting the SOC of the minimum voltage of the module from the SOC value of the maximum voltage of the module of the factory-produced battery pack;

[0038] S34, calculating the ΔSOC of the factory battery pack corresponding to the different SOC values ​​to establish a regression equation, and obtaining the SOC-ΔSOC curve of the factory battery pack during charging and the SOC-ΔSOC curve of the factory battery pack during discharging;

[0039] S35, fitting the charging process SOC-ΔSOC curve, the discharging process SOC-ΔSOC curve and the charging process and discharging process SOC-ΔSOC confidence intervals of the test data, and comparing them, such as estimating the consistency of the factory battery pack according to a preset excess ratio discrete threshold.

[0040] The present invention selects electrical performance test data to be detected, wherein the data to be recorded include: a module maximum voltage value Vmax, a module minimum voltage value Vmin, a charging capacity, and a discharging capacity. The collected battery pack data to be detected includes data during a charging process and a discharging process, replacing the technical solution of only taking data at two time points, namely, a charging cutoff and a discharging cutoff, for consistency evaluation in the traditional technology, thereby realizing the evaluation of the entire test process.

[0041] In a more specific technical solution, a battery pack consistency evaluation system includes:

[0042] A minimum voltage value curve establishment module is used to collect and obtain test data as test samples, and establish SOC-module minimum voltage value curves during charging and discharging according to the test samples;

[0043] A confidence interval module, for comparing the SOC-module minimum voltage value curve during the charging and discharging process, converting the module maximum voltage and the module minimum voltage during the charging and discharging stage to obtain corresponding SOC values, and calculating ΔSOC to establish a regression equation, a charging process SOC-ΔSOC curve, and a discharging process SOC-ΔSOC curve, and selecting at least 2 groups of the test samples to respectively establish a charging process standard SOC-ΔSOC confidence interval and a discharging process standard SOC-ΔSOC confidence interval, and the confidence interval module is connected to the minimum voltage value curve establishment module;

[0044] A consistency estimation module is used to collect the test data of the factory battery pack, and compare and process the test data with the standard SOC-ΔSOC confidence interval of the charging process and the standard SOC-ΔSOC confidence interval of the discharging process to obtain the preset confidence interval excess ratio, and determine the excess ratio data and dispersion data of the factory battery pack according to the test data to obtain the consistency estimation result of the factory battery pack. The consistency estimation module is connected to the confidence interval module.

[0045] Compared with the prior art, the present invention has the following advantages: the present invention first calculates ΔSOC to establish a regression equation and a SOC-ΔSOC curve for the charging and discharging process, selects no less than 2 groups of test samples, and respectively establishes the standard SOC-ΔSOC confidence interval for the charging and discharging process, and compares the test data of the factory battery with the standard SOC-ΔSOC confidence interval. If it exceeds or exceeds a certain proportion, it can be considered that it does not meet the requirements and is judged as abnormal. The greater the excess proportion, the greater the discreteness, and the worse the consistency of the battery pack. The evaluation method provided by the present invention can effectively monitor and determine the consistency of the battery pack during the charging and discharging process of the factory test, and can conduct targeted cause analysis based on the time and location of the abnormality.

[0046] The present invention establishes a regression equation based on the ΔSOC corresponding to different SOCs obtained by calculation, obtains the SOC-ΔSOC curve of the charging process and the SOC-ΔSOC curve of the discharging process, selects multiple groups of sample test data according to the above method, and uses statistical methods to respectively establish standard SOC-ΔSOC confidence intervals for the charging process and the discharging process, thereby solving the technical problem of incomplete testing and low accuracy caused by the traditional method of inspecting the consistency of battery packs, which is that the consistency is judged by specific parameters such as battery voltage difference and charge and discharge cut-off, and thus improves the accuracy of battery pack consistency evaluation.

[0047] The present invention adopts the difference between the module's maximum voltage value SOC and the module's minimum SOC, and uses a specific algorithm to calculate the SOC value in the charging stage and the SOC value in the discharging stage, thereby avoiding the technical problems in the prior art of only using parameters such as battery voltage to evaluate the consistency of the battery pack and the low accuracy caused by the inconsistent pressure difference corresponding to the SOC in different stages.

[0048] The present invention selects the electrical performance test data to be detected, wherein the data to be recorded include: the maximum voltage value Vmax of the module, the minimum voltage value Vmin of the module, the charging capacity and the discharging capacity. The collected battery pack data to be detected includes the data during the charging process and the discharging process, replacing the technical solution of only taking the data at the two time points of charging cutoff and discharging cutoff for consistency evaluation in the traditional technology, and realizing the evaluation of the entire test process. The present invention solves the technical problem that the prior art lacks the evaluation of the entire test process and the estimation accuracy is not high. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A basic flow chart of a method for battery pack consistency according to Embodiment 1 of the present invention;

[0050] Figure 2 A schematic diagram of a flow chart for establishing a confidence interval of a power state according to Embodiment 2 of the present invention;

[0051] Figure 3Schematic diagram of the detection data and confidence interval comparison process of Example 2 of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in combination with the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Example 1

[0054] like Figure 1 As shown, a method for battery pack consistency includes the following steps:

[0055] In this embodiment, the specific steps of establishing the SOC-SOC confidence interval include:

[0056] S1. Establishing a SOC-module minimum voltage value curve according to sample data;

[0057] S2, the maximum module voltage and the minimum module voltage are converted into corresponding SOC values ​​respectively;

[0058] S3, calculating the difference ΔSOC between the maximum voltage value SOC of the module and the minimum SOC of the module;

[0059] S4, establishing a charge and discharge process state of charge SOC-ΔSOC curve;

[0060] In this embodiment, the specific steps of comparing the monitoring data with the confidence interval include:

[0061] S1', establishing a SOC-module minimum voltage value curve according to the data to be tested;

[0062] S2', the maximum module voltage and the minimum module voltage are converted into corresponding SOC values;

[0063] S3', calculating the difference ΔSOC between the maximum module voltage value SOC and the minimum module SOC of the factory-tested battery;

[0064] S4', establishing a charge and discharge process state of charge SOC-ΔSOC curve of the data to be measured;

[0065] S5. Establish a standard SOC-ΔSOC confidence interval based on multiple sets of data.

[0066] Example 2

[0067] The present invention provides a method for battery pack consistency, the process of which includes establishing a SOC-ΔSOC confidence interval and comparing detection data with the confidence interval.

[0068] like Figure 2 As shown, establishing the SOC-ΔSOC confidence interval includes the following steps:

[0069] Step S101: Select the historical data of the electrical performance test as sample data, where the data to be recorded include: the maximum voltage value Vmax of the module, the minimum voltage value Vmin of the module, the charging capacity and the discharging capacity. The SOC value at each time point in the charging stage and the discharging stage is calculated in the following way:

[0070]

[0071] Among them, SOCC is the SOC in the charging stage, CC is the capacity of the battery pack currently charged, It is the total capacity charged into the battery pack from the beginning to the end of charging.

[0072]

[0073] Among them, SOCD is the SOC in the discharge stage, CD is the capacity of the current battery pack that has been discharged, It is the total capacity discharged from the battery pack from the start to the end of discharge.

[0074] With the charge and discharge SOC as the X-axis and the module minimum voltage value Vmin as the Y-axis, a SOC-Vmin curve is drawn.

[0075] Step S102: referring to the SOC-Vmin curve, converting the maximum voltage and the minimum voltage of the module at each time point in the charging process and the discharging process into corresponding SOC values ​​respectively;

[0076] Step S103: ΔSOC is obtained by subtracting the SOC of the minimum voltage of the module from the SOC of the maximum voltage of the module. The calculation method is as follows:

[0077] ΔSOC=SOC Vmax -SOC Vmin

[0078] Among them, ΔSOC is the difference between the maximum voltage value SOC of the module and the minimum SOC of the module, SOCVmax is the maximum voltage value SOC of the module, and SOCVmin is the minimum voltage value SOC of the module.

[0079] Step S104: establishing a regression equation based on the ΔSOC corresponding to different SOCs obtained by calculation, and fitting to obtain a charging process SOC-ΔSOC curve and a discharging process SOC-ΔSOC curve;

[0080] Step S105: select multiple groups of sample test data (the larger the sample size, the better, N ≥ 30 is recommended), use the above method to fit multiple groups of charging process SOC-ΔSOC curves and discharging process SOC-ΔSOC curves, calculate the ΔSOC corresponding to different SOCs in the charging process and the discharging process, make a ΔSOC normal distribution diagram, get the sample mean and standard deviation, select 95% or 90% confidence level, set the confidence interval, and get the ΔSOC standard confidence interval under 0% to 100% SOC;

[0081] like Figure 3 As shown, the comparison between the detection data and the confidence interval includes the following steps:

[0082] Step S201: Select the electrical performance test data to be tested, where the data to be recorded include: module maximum voltage value Vmax, module minimum voltage value Vmin, charging capacity and discharging capacity. The SOC value at each time point in the charging stage and the discharging stage is calculated in the following way:

[0083]

[0084] Among them, SOCC is the SOC in the charging stage, CC is the capacity of the battery pack currently charged, It is the total capacity charged into the battery pack from the beginning to the end of charging.

[0085]

[0086] Among them, SOCD is the SOC in the discharge stage, CD is the capacity of the current battery pack that has been discharged, It is the total capacity discharged from the battery pack from the start to the end of discharge.

[0087] With the charge and discharge SOC as the X-axis and the module minimum voltage value Vmin as the Y-axis, a SOC-Vmin curve is drawn.

[0088] Step S202: referring to the SOC-Vmin curve, converting the maximum voltage and the minimum voltage of the module at each time point in the charging process and the discharging process into corresponding SOC values ​​respectively;

[0089] Step S203: ΔSOC is obtained by subtracting the SOC of the minimum voltage of the module from the SOC of the maximum voltage of the module. The calculation method is as follows:

[0090] ΔSOC=SOC Vmax -SOC Vmin

[0091] Among them, ΔSOC is the difference between the maximum voltage value SOC of the module and the minimum SOC of the module, SOCVmax is the maximum voltage value SOC of the module, and SOCVmin is the minimum voltage value SOC of the module.

[0092] Step S204: establishing a regression equation based on the ΔSOC corresponding to different SOCs obtained by calculation, and fitting the charging process SOC-ΔSOC curve and the discharging process SOC-ΔSOC curve of the data to be detected;

[0093] Step S205: The SOC-ΔSOC curve of the charging process and the SOC-ΔSOC curve of the discharging process fitted by the data to be tested are compared with the standard confidence intervals of the SOC-ΔSOC of the charging process and the discharging process. If they exceed or exceed a certain proportion, it can be considered that the requirements are not met and the battery pack consistency is determined to be abnormal. The larger the excess proportion, the greater the dispersion, and the worse the battery pack consistency.

[0094] In summary, the present invention first calculates ΔSOC to establish a regression equation and a SOC-ΔSOC curve for the charging and discharging process, selects no less than 2 groups of test samples, and respectively establishes the standard SOC-ΔSOC confidence interval for the charging and discharging process, and compares the test data of the factory battery with the standard SOC-ΔSOC confidence interval. If it exceeds or exceeds a certain proportion, it can be considered that it does not meet the requirements and is judged as abnormal. The greater the excess proportion, the greater the discreteness, and the worse the consistency of the battery pack. The evaluation method provided by the present invention can effectively monitor and determine the consistency of the battery pack during the charging and discharging process of the factory test, and can perform targeted cause analysis based on the time and location of the abnormality.

[0095] The present invention establishes a regression equation based on the ΔSOC corresponding to different SOCs obtained by calculation, obtains the SOC-ΔSOC curve of the charging process and the SOC-ΔSOC curve of the discharging process, selects multiple groups of sample test data according to the above method, and uses statistical methods to respectively establish standard SOC-ΔSOC confidence intervals for the charging process and the discharging process, thereby solving the technical problem of incomplete testing and low accuracy caused by the traditional method of inspecting the consistency of battery packs, which is that the consistency is judged by specific parameters such as battery voltage difference and charge and discharge cut-off, and thus improves the accuracy of battery pack consistency evaluation.

[0096] The present invention adopts the difference between the module's maximum voltage value SOC and the module's minimum SOC, and uses a specific algorithm to calculate the SOC value in the charging stage and the SOC value in the discharging stage, thereby avoiding the technical problems in the prior art of only using parameters such as battery voltage to evaluate the consistency of the battery pack and the low accuracy caused by the inconsistent pressure difference corresponding to the SOC in different stages.

[0097] The present invention selects the electrical performance test data to be detected, wherein the data to be recorded include: the maximum voltage value Vmax of the module, the minimum voltage value Vmin of the module, the charging capacity and the discharging capacity. The collected battery pack data to be detected includes the data during the charging process and the discharging process, replacing the technical solution of only taking the data at the two time points of charging cutoff and discharging cutoff for consistency evaluation in the traditional technology, and realizing the evaluation of the entire test process. The present invention solves the technical problem that the prior art lacks the evaluation of the entire test process and the estimation accuracy is not high.

[0098] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A battery pack consistency evaluation method, characterized in that: The method comprises: S1. Collecting and acquiring test data as test samples, and establishing SOC-module minimum voltage value curves during charging and discharging according to the test samples; S2. By comparing the SOC-module minimum voltage curve during the charging and discharging process, the maximum module voltage and the minimum module voltage during the charging and discharging stage are converted to obtain corresponding SOC values, and ΔSOC is calculated to establish a regression equation, a charging process SOC-ΔSOC curve, and a discharging process SOC-ΔSOC curve, and at least 2 groups of the test samples are selected to respectively establish a charging process standard SOC-ΔSOC confidence interval and a discharging process standard SOC-ΔSOC confidence interval; S3. Collect the test data of the factory battery pack, and compare and process the test data with the standard SOC-ΔSOC confidence interval of the charging process and the standard SOC-ΔSOC confidence interval of the discharging process to obtain the preset confidence interval excess ratio, and determine the excess ratio data and dispersion data of the factory battery pack according to the test data to obtain the consistency estimation result of the factory battery pack.

2. A battery pack consistency evaluation method according to claim 1, characterized in that: The step S2 comprises: S21, referring to the SOC-module minimum voltage curve, converting the module maximum voltage and module minimum voltage corresponding to the SOC during the charging process and the discharging process into corresponding SOC values ​​respectively; S22, processing the SOC of the maximum voltage of the module and the SOC of the minimum voltage of the module with a preset logic to obtain a difference ΔSOC between the maximum voltage value SOC of the module and the minimum SOC of the module; S23, calculating different corresponding SOC values ​​according to preset logic, obtaining the ΔSOC to establish a regression equation, the charging process SOC-ΔSOC curve, and the discharging process SOC-ΔSOC curve; S24, selecting at least 2 groups of the test samples, and using preset statistical logic to respectively establish standard SOC-ΔSOC confidence intervals for the charge and discharge process.

3. A battery pack consistency evaluation method according to claim 2, characterized in that: In step S22, the difference ΔSOC between the maximum voltage value SOC of the module and the minimum SOC of the module is calculated using the following logic: ΔSOC=SOC Vmax -SOC Vmin , Among them, SOC Vmax SOC is the maximum voltage value of the module, SOC Vmin This is the module minimum value.

4. A battery pack consistency evaluation method according to claim 2, characterized in that: The step S2 comprises: S241, randomly selecting no less than 2 test samples, and calculating a test curve based on the samples; S242, calculating the difference ΔSOC between the maximum voltage value SOC of the module and the minimum SOC of the module corresponding to the test curve at different SOCs, and generating a ΔSOC normal distribution diagram accordingly; S243, processing the ΔSOC normal distribution graph to obtain a sample mean and a standard deviation; S244. Calculate the confidence interval according to the present mean and the standard deviation to obtain a standard confidence interval under 0% to 100% SOC.

5. A battery pack consistency evaluation method according to claim 1, characterized in that: In step 2 and step 3, the capacity value of the charging stage and the capacity value of the discharging stage are acquired and processed to obtain the SOC value.

6. A battery pack consistency evaluation method according to claim 5, characterized in that: The SOC value corresponds one-to-one to the minimum value of the module voltage in the battery pack.

7. A battery pack consistency evaluation method according to claim 2, characterized in that: In step S21, the following logic is used to calculate the SOC value in the charging stage: , Among them, SOC C is the SOC during the charging phase, C C is the capacity of the battery pack currently charged, It is the total capacity charged into the battery pack from the beginning to the end of charging.

8. A battery pack consistency evaluation method according to claim 2, characterized in that: In step S21, the following logic is used to calculate the SOC value in the discharge phase: , Among them, SOC D is the SOC in the discharge phase, C D is the capacity of the current battery pack that has been discharged. It is the total capacity discharged from the battery pack from the start to the end of discharge.

9. A battery pack consistency evaluation method according to claim 5, characterized in that: The step S3 comprises: S31, establishing SOC-module minimum voltage value curves during charging and discharging according to the data to be tested; S32, referring to the SOC-module minimum voltage curve, converting the maximum module voltage and the minimum module voltage of the battery pack during the charging and discharging phases into corresponding SOC values ​​respectively; S33, obtaining ΔSOC by subtracting the SOC of the minimum voltage of the module from the SOC value of the maximum voltage of the module of the factory battery pack; S34, calculating the ΔSOC of the factory battery pack corresponding to the different SOC values ​​to establish a regression equation, and obtaining the SOC-ΔSOC curve of the factory battery pack during charging and the SOC-ΔSOC curve of the factory battery pack during discharging; S35, fitting the charging process SOC-ΔSOC curve, the discharging process SOC-ΔSOC curve and the charging process and discharging process SOC-ΔSOC confidence intervals of the data to be tested, and estimating the consistency of the factory battery pack according to a preset excess ratio discrete threshold.

10. A battery pack consistency evaluation system, characterized in that: The system comprises: A minimum voltage value curve establishment module is used to collect and obtain test data as test samples, and establish SOC-module minimum voltage value curves during charging and discharging according to the test samples; A confidence interval module, for comparing the SOC-module minimum voltage value curve during the charging and discharging process, converting the module maximum voltage and the module minimum voltage during the charging and discharging stage to obtain corresponding SOC values, and calculating ΔSOC to establish a regression equation, a charging process SOC-ΔSOC curve, and a discharging process SOC-ΔSOC curve, and selecting at least 2 groups of the test samples to respectively establish a charging process standard SOC-ΔSOC confidence interval and a discharging process standard SOC-ΔSOC confidence interval, and the confidence interval module is connected to the minimum voltage value curve establishment module; A consistency estimation module is used to collect the test data of the factory battery pack, and compare and process the test data with the standard SOC-ΔSOC confidence interval of the charging process and the standard SOC-ΔSOC confidence interval of the discharging process to obtain the preset confidence interval excess ratio, and determine the excess ratio data and dispersion data of the factory battery pack according to the test data to obtain the consistency estimation result of the factory battery pack. The consistency estimation module is connected to the confidence interval module.

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