Charging data consistency determination method and device

Abstract

The invention discloses a charging data consistency determination method and device. The method comprises the following steps: acquiring charging data of a battery pack in the electric vehicle in a sampling period; obtaining a plurality of charging data variations of each single battery; obtaining a first charging data mean value of each single battery; determining a charging data total capacity, and determining a second charging data mean value of the battery pack; determining a statistical index of a first error of the charging data in each single battery; determining a statistical index of a second error of the charging data between the single batteries; determining a charging data statistical value of each single battery, and determining a charging data critical value; and comparing the charging data statistical value with the charging data critical value to determine a charging data consistency evaluation index of the single battery. According to the method and the device, the technical problem that the potential safety hazard of the battery cannot be checked in time due to the fact that the consistency of the charging data cannot be accurately determined based on the charging data of the battery pack in the sampling period in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of new energy applications in Internet of Vehicles, and more specifically, to a method and device for determining charging data consistency. Background Art

[0002] The frequent fire and explosion accidents of electric vehicle power battery systems in recent years have proved that the safety and reliability of power battery systems are extremely important. The inconsistency of cells in new energy batteries after grouping and in actual operation is one of the root causes of battery system safety problems.

[0003] The inconsistency of the power battery system refers to the fact that after the single cells of the same specifications and models are assembled into a battery pack, there are certain differences in parameters such as voltage, battery state of charge (SOC), remaining useful life or remaining useful life (RUL), temperature, capacity decay rate, internal resistance and its change rate, and self-discharge rate. The inconsistency of the power battery system is mainly manifested in the following two aspects when it is manufactured.

[0004] 1. The original differences in monomers caused by the manufacturing process, errors in the manufacturing process and uneven battery materials will cause slight differences in the degree of activation, thickness, microporosity, etc. of the active substances in the battery plates. This inconsistency in the internal structure and material of the battery will cause the capacity, internal resistance and other parameters of the same model and batch of batteries to have certain inconsistencies when leaving the factory.

[0005] 2. Differences in monomer degradation caused by environmental differences when installed on the vehicle. Since the storage temperature, ventilation conditions, self-discharge degree and electrolyte density of each monomer battery will have certain differences, this will to a certain extent also aggravate the inconsistency of battery parameters such as voltage, internal resistance and capacity.

[0006] The various inconsistent parameters of the power battery system are not independent of each other, but influence each other and are mutually causal. The most direct manifestation is the inconsistency of battery voltage. The inconsistency of voltage can reflect the inconsistency of other parameters of the power battery system to a certain extent. With the increase of usage time and mileage, the inconsistency of the power battery system will gradually increase. The most intuitive reflection is the gradual increase in the inconsistency level of single cell voltage.

[0007] Since a single cell will have a large difference from other cells in the battery pack when it fails, and even cause safety problems, the analysis method of evaluating the consistency of the battery pack based on cloud charging data is worth studying. With the widespread application of cloud data, the data of new energy electric vehicles can be detected, and these data can be used to analyze the safety of electric vehicles and the consistency of battery packs. Although the data sampling frequency on electric vehicles is high, the recording frequency of cloud data is low. Therefore, only the charging data in the cloud is more meaningful and suitable for analyzing the consistency of the battery pack of electric vehicles. However, the relevant technology cannot accurately determine the consistency of the charging data based on the charging data of the battery pack during the sampling period, which leads to the inability to timely detect the safety hazards of the battery.

[0008] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0009] The embodiments of the present application provide a method and device for determining charging data consistency, so as to at least solve the technical problem that the safety hazards of the battery cannot be timely checked because the related technology cannot accurately determine the consistency of the charging data based on the charging data of the battery pack within a sampling period.

[0010] According to one aspect of an embodiment of the present application, a method for determining charging data consistency is provided, comprising: obtaining charging data of a battery pack in an electric vehicle within a sampling period, wherein the battery pack includes: a plurality of single cells, the sampling period includes: a plurality of sampling time points, and the charging data includes: voltage data and temperature data; determining a charging data change amount of each single cell between each two consecutive sampling time points, and obtaining a plurality of charging data change amounts of each single cell; determining a mean of the plurality of charging data change amounts of each single cell, and obtaining a first charging data mean value of each single cell; determining a total charging data capacity according to the number of charging data change amounts and the number of single cells, and obtaining a first charging data mean value of each single cell according to the first charging data mean value of each single cell. and the number of single cells, determine the second charging data mean of the battery pack; determine the statistical index of the first error of the charging data within each single cell according to the multiple charging data changes of each single cell and the total capacity of the charging data; determine the statistical index of the second error of the charging data between each single cell according to the second charging data mean and the total capacity of the charging data; determine the charging data statistical value of each single cell according to the statistical index of the first error and the statistical index of the second error, and determine the charging data critical value according to the number of single cells and the total capacity of the charging data; compare the charging data statistical value with the charging data critical value, and determine the charging data consistency evaluation index of the single cell according to the comparison result.

[0011] Optionally, obtaining charging data of a battery pack in an electric vehicle within a sampling period includes: obtaining a notification message for indicating that charging of the electric vehicle has ended, wherein the notification message includes at least: vehicle identification information of the electric vehicle, a charging start time, and a charging end time; reading initial charging data of the battery pack of the electric vehicle corresponding to the vehicle identification information within the sampling period in a database; sorting the initial charging data according to the sampling time, removing repeated parameters in the sorted initial charging data, and in the case where there is missing data in the sorted initial charging data, using a piecewise linear interpolation method to fill the missing data to obtain the charging data of the battery pack in the electric vehicle within the sampling period; and resampling the charging data when the rate of change of the voltage data is less than a first preset threshold and / or the rate of change of the temperature data is less than a second preset threshold.

[0012] Optionally, when the rate of change of the voltage data is less than a first preset threshold and / or the rate of change of the temperature data is less than a second preset threshold, the charging data is resampled, including: determining the average voltage increment of each single cell according to the number and quantity of each single cell, the charging voltage at the start of charging, and the charging voltage at the end of charging; determining the charging time according to the start time and the end time of charging; determining the expected sampling period according to the average voltage increment and preset parameters; determining the resampling period according to the charging time, the expected sampling period and the original sampling period, wherein the resampling period is an integer multiple of the original sampling period; and obtaining the charging data of the battery pack in the electric vehicle within the resampling period.

[0013] Optionally, determining the amount of change in charging data of each single cell between every two consecutive sampling time points to obtain multiple charging data changes of each single cell; determining the average of the multiple charging data changes of each single cell to obtain the first charging data average of each single cell, including: determining a first matrix and a second matrix according to the voltage data of each single cell, wherein the i-th column of the first matrix is ​​the voltage of the single cell corresponding to the i-th sampling time point, the rows of the first matrix and the second matrix are both used to characterize the number of single cells, the i-th column of the second matrix is ​​the voltage of the single cell corresponding to the i+1-th sampling time point, i is a positive integer not greater than n, n is the number of sampling time points, and n is an integer greater than 1; determining the first voltage change of each single cell between every two consecutive sampling time points according to the difference between the second matrix and the first matrix to obtain multiple first voltage changes of each single cell; determining the average of the multiple first voltage changes of each single cell to obtain the first voltage average of each single cell.

[0014] Optionally, based on multiple charging data changes of each single cell and the total capacity of charging data, a statistical indicator of a first error of charging data inside each single cell is determined, including: determining the mean square error of the first voltage error of the voltage data inside each single cell according to the total voltage capacity in the total capacity of charging data, the number of single cells, the number of first voltage changes of each single cell, and multiple first voltage changes; based on the second charging data mean and the total capacity of charging data, a statistical indicator of a second error of charging data between each single cell is determined, including: determining the mean square error of the second voltage error of the voltage data between each single cell according to the number of single cells, the second voltage mean in the second charging data mean, and the first voltage mean of each single cell.

[0015] Optionally, according to the statistical index of the first error and the statistical index of the second error, the charging data statistics of each single cell are determined, and according to the number of single cells and the total capacity of the charging data, the charging data critical value is determined, including: determining the ratio of the mean square error of the second voltage error to the mean square error of the first voltage error as the voltage statistical value; determining the voltage critical value according to the number of single cells and the total voltage capacity; comparing the charging data statistics with the charging data critical value, and determining the charging data consistency evaluation index of the single cell according to the comparison result, including: when the voltage statistical value is greater than or equal to the voltage critical value, determining that there is a difference in voltage consistency of the battery pack in the electric vehicle.

[0016] Optionally, determining the amount of change in charging data of each single cell between every two consecutive sampling time points to obtain multiple amounts of charging data change of each single cell; determining the average of the multiple amounts of charging data change of each single cell to obtain the first average value of charging data of each single cell, including: determining a third matrix and a fourth matrix according to the temperature data of each single cell, wherein the j-th column of the third matrix is ​​the temperature of the single cell corresponding to the j-th sampling time point, the rows of the third matrix and the fourth matrix are both used to characterize the number of single cells, the j-th column of the fourth matrix is ​​the temperature of the single cell corresponding to the j+1-th sampling time point, j is a positive integer not greater than m, m is the number of sampling time points, and m is an integer greater than 1; determining the first temperature change of each single cell between every two consecutive sampling time points according to the difference between the fourth matrix and the third matrix to obtain multiple first temperature changes of each single cell; determining the average of the multiple first temperature changes of each single cell to obtain the first temperature average of each single cell.

[0017] Optionally, based on multiple charging data changes of each single cell and the total capacity of charging data, a statistical indicator of a first error of charging data inside each single cell is determined, including: determining the mean square error of the first temperature error of the temperature data inside each single cell according to the total temperature capacity in the total capacity of charging data, the number of temperature sensors in the battery pack, the number of first temperature changes of each single cell, and multiple first temperature changes; based on the second charging data mean and the total capacity of charging data, a statistical indicator of a second error of charging data between each single cell is determined, including: determining the mean square error of the second temperature error of the temperature data between each single cell according to the number of temperature sensors in the battery pack, the second temperature mean in the second charging data mean, and the first temperature mean of each single cell.

[0018] Optionally, according to the statistical index of the first error and the statistical index of the second error, the charging data statistics of each single cell are determined, and according to the number of temperature sensors in the battery pack and the total capacity of the charging data, the charging data critical value is determined, including: determining the ratio of the mean square error of the second temperature error to the mean square error of the first temperature error as the temperature statistical value; determining the temperature critical value according to the number of temperature sensors in the battery pack and the total temperature capacity; comparing the charging data statistics with the charging data critical value, and determining the charging data consistency evaluation index of the single cell according to the comparison result, including: when the temperature statistical value is greater than or equal to the temperature critical value, determining that there is a difference in temperature consistency of the battery pack in the electric vehicle.

[0019] Optionally, determining a charging data consistency evaluation index for a single cell battery includes: when it is determined that there is a difference in charging data consistency of a battery pack in an electric vehicle, generating a curve graph of the charging data change for each single cell battery, determining and displaying identification information of a sensor with the largest average charging data and identification information of a battery pack with the largest average charging data.

[0020] According to another aspect of the embodiment of the present application, a charging data consistency determination device is also provided, including: an acquisition module, used to acquire charging data of a battery pack in an electric vehicle within a sampling period, wherein the battery pack includes: a plurality of single cells, the sampling period includes: a plurality of sampling time points, and the charging data includes: voltage data and temperature data; a first determination module, used to determine the amount of change in charging data of each single cell between each two consecutive sampling time points, and obtain multiple amounts of charging data change of each single cell; determine the average of the multiple amounts of charging data change of each single cell, and obtain the first charging data average of each single cell; a second determination module, used to determine the total capacity of the charging data according to the amount of charging data change and the number of single cells, and determine the total capacity of the charging data according to the first charging data average of each single cell and the single cell; a third determining module, for determining the statistical index of the first error of the charging data within each single cell according to the multiple charging data changes of each single cell and the total capacity of the charging data; a fourth determining module, for determining the statistical index of the second error of the charging data between each single cell according to the second charging data mean and the total capacity of the charging data; a fifth determining module, for determining the charging data statistical value of each single cell according to the statistical index of the first error and the statistical index of the second error, and determining the charging data critical value according to the number of single cells and the total capacity of the charging data; a comparison module, for comparing the charging data statistical value with the charging data critical value, and determining the charging data consistency evaluation index of the single cell according to the comparison result.

[0021] According to another aspect of the embodiments of the present application, a non-volatile storage medium is further provided, the storage medium including a stored program, wherein when the program is executed, the device where the storage medium is located is controlled to execute the above charging data consistency determination method.

[0022] According to another aspect of the embodiments of the present application, an electronic device is provided, including: a memory and a processor, the processor being configured to run a program stored in the memory, wherein the above charging data consistency determination method is executed when the program is run.

[0023] According to yet another aspect of the embodiments of the present application, a computer program is further provided, wherein when the computer program is executed by a processor, the above charging data consistency determination method is implemented.

[0024] According to another aspect of the embodiments of the present application, a computer program product is also provided, the computer program product comprising a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above charging data consistency determination method is implemented.

[0025] In an embodiment of the present application, the charging data of a battery pack in an electric vehicle within a sampling period is obtained, wherein the battery pack includes: a plurality of single cells, the sampling period includes: a plurality of sampling time points, and the charging data includes: voltage data and temperature data; the charging data change amount of each single cell between each two consecutive sampling time points is determined to obtain a plurality of charging data change amounts of each single cell; the mean of the plurality of charging data change amounts of each single cell is determined to obtain a first charging data mean value of each single cell; the total charging data capacity is determined based on the number of charging data change amounts and the number of single cells, and the second charging data mean value of the battery pack is determined based on the first charging data mean value of each single cell and the number of single cells; the first error of the charging data inside each single cell is determined based on the plurality of charging data change amounts of each single cell and the total charging data capacity. Statistical indicators; determining the statistical indicators of the second error of the charging data between each single battery according to the second charging data mean and the total capacity of the charging data; determining the charging data statistical value of each single battery according to the statistical indicators of the first error and the statistical indicators of the second error, and determining the charging data critical value according to the number of single batteries and the total capacity of the charging data; comparing the charging data statistical value with the charging data critical value, and determining the charging data consistency evaluation index of the single battery according to the comparison result, achieves the purpose of accurately determining the consistency of the charging data based on the charging data of the battery pack within the sampling period, thereby achieving the technical effect of timely checking the safety hazards of the battery, and further solves the technical problem of being unable to timely check the safety hazards of the battery due to the inability of related technologies to accurately determine the consistency of the charging data based on the charging data of the battery pack within the sampling period. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0027] Figure 1 is a flow chart of a method for determining charging data consistency according to an embodiment of the present application;

[0028] Figure 2 is a flow chart of another charging data consistency determination method according to an embodiment of the present application;

[0029] Figure 3 is a structural diagram of a charging data consistency determination device according to an embodiment of the present application;

[0030] Figure 4 It is a hardware structure block diagram of a computer terminal according to a charging data consistency determination method of an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0032] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] According to an embodiment of the present application, a method embodiment of a method for determining charging data consistency is provided. 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 a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] Figure 1 is a flow chart of a method for determining charging data consistency according to an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0035] Step S101, acquiring charging data of a battery pack in an electric vehicle within a sampling period, wherein the battery pack includes: a plurality of single cells, the sampling period includes: a plurality of sampling time points, and the charging data includes: voltage data and temperature data.

[0036] The battery pack is composed of multiple single cells, which are connected in series and parallel to meet the voltage and capacity requirements of electric vehicles.

[0037] The sampling period is, for example, 1 hour, and there are 360 ​​sampling time points, that is, starting from time zero, sampling is performed every 10 seconds.

[0038] Step S102, determining the charging data change amount of each single cell between each two consecutive sampling time points to obtain multiple charging data change amounts of each single cell; determining the average of the multiple charging data change amounts of each single cell to obtain the first charging data average of each single cell.

[0039] For example, when there are 360 ​​sampling time points, the number of charging data changes of each single battery between every two consecutive sampling time points is 359.

[0040] Step S103, determining the total capacity of the charging data according to the amount of charging data changes and the number of single cells, and determining the second charging data mean of the battery pack according to the first charging data mean of each single cell and the number of single cells.

[0041] Step S104 , determining a statistical indicator of a first error of charging data within each single battery according to a plurality of charging data variation amounts and a total capacity of charging data of each single battery.

[0042] Step S105 , determining a statistical indicator of a second error of charging data between each single battery according to the second charging data mean value and the total capacity of the charging data.

[0043] Statistical indicators such as mean square error, where the mean square error is the arithmetic square root of the average of the square values ​​of the differences between each data in a set of data and its arithmetic mean. The larger the mean square error, the greater the fluctuation of the data and the higher the degree of dispersion; the smaller the mean square error, the more concentrated the data and the lower the degree of dispersion.

[0044] Step S106, determining the charging data statistics of each single battery according to the statistical index of the first error and the statistical index of the second error, and determining the charging data critical value according to the number of single batteries and the total capacity of the charging data.

[0045] Step S107 , comparing the charging data statistics with the charging data critical value, and determining the charging data consistency evaluation index of the single cell according to the comparison result.

[0046] The following Figure 1 The steps shown are exemplary and explanatory.

[0047] In some optional embodiments, obtaining charging data of a battery pack in an electric vehicle within a sampling period may be achieved by the following method:

[0048] Obtain a notification message for indicating that charging of the electric vehicle has ended, wherein the notification message includes at least: vehicle identification information of the electric vehicle, charging start time, and charging end time; read initial charging data of a battery pack of the electric vehicle corresponding to the vehicle identification information within a sampling period in a database; sort the initial charging data according to the sampling time, remove repeated parameters in the sorted initial charging data, and in the case where there is missing data in the sorted initial charging data, fill the missing data with a piecewise linear interpolation method to obtain the charging data of the battery pack in the electric vehicle within the sampling period; and resample the charging data in the case where the rate of change of the voltage data is less than a first preset threshold value and / or the rate of change of the temperature data is less than a second preset threshold value.

[0049] A notification message indicating that charging of the above-mentioned vehicle has ended is obtained through the cloud platform, wherein the notification message at least includes: vehicle identification information of the electric vehicle, charging start time and charging end time. The vehicle identification information of the electric vehicle is, for example, the vehicle identification number (VIN) of the electric vehicle, which is a unique code consisting of seventeen letters or numbers, just like the identity card number of the electric vehicle.

[0050] It is understandable that when the change rate of voltage data and the change rate of temperature data are too small, the data sampling period should be adjusted appropriately to perform data resampling. Specifically, the charging data can be resampled by the following method:

[0051] Determine the average voltage increment of each battery cell according to the number and quantity of each battery cell, the charging voltage at the start time of charging, and the charging voltage at the end time of charging; determine the charging time according to the start time and the end time of charging; determine the expected sampling period according to the average voltage increment and preset parameters; determine the resampling period according to the charging time, the expected sampling period and the original sampling period, wherein the resampling period is an integer multiple of the original sampling period; obtain the charging data of the battery pack in the electric vehicle within the resampling period.

[0052] The average voltage increment of each battery cell can be determined by the following formula:

[0053]

[0054] Where i is the i-th battery cell in the battery pack, R V is the number of battery cells, N is the time when battery charging ends, 0 is the time when charging starts, and V is the voltage.

[0055] Charging time = charging end time - charging start time.

[0056] For example, if the preset parameter is 0.01, the expected sampling period can be determined by the following formula:

[0057]

[0058] Furthermore, the resampling period can be determined by the following formula:

[0059] Resampling period = (charging time / cycle estimation + terminal collection period - 1) / terminal collection period.

[0060] According to some optional embodiments of the present application, the charging data change amount of each single cell between every two consecutive sampling time points is determined to obtain multiple charging data change amounts of each single cell; the average of the multiple charging data change amounts of each single cell is determined to obtain the first charging data average of each single cell, which can be achieved by the following method: according to the voltage data of each single cell, a first matrix and a second matrix are determined, wherein the i-th column of the first matrix is ​​the voltage of the single cell corresponding to the i-th sampling time point, the rows of the first matrix and the second matrix are used to characterize the number of single cells, the i-th column of the second matrix is ​​the voltage of the single cell corresponding to the i+1-th sampling time point, i is a positive integer not greater than n, n is the number of sampling time points, and n is an integer greater than 1; according to the difference between the second matrix and the first matrix, the first voltage change amount of each single cell between every two consecutive sampling time points is determined to obtain multiple first voltage change amounts of each single cell; the average of the multiple first voltage change amounts of each single cell is determined to obtain the first voltage average of each single cell.

[0061] It can be understood that the rows of the above matrix are the numbers of the single cells, such as the 0th row is the single cell numbered 1, the 1st row is the single cell numbered 2, the 2nd row is the single cell numbered 3, and so on.

[0062] For example, the first voltage change is recorded as ΔV, and for the i-th single cell, its j-th first voltage change is ΔV ij If the sampling period includes 100 sampling time points, the single cell corresponds to 99 ΔV, and the first voltage change can be recorded as ΔV i1 , the 10th first voltage change can be recorded as ΔV i10 By adding 99 ΔV and dividing by 99, we can get the average of multiple first voltage changes, that is, the first voltage average of the i-th single cell, recorded as

[0063] Determining the statistical index of the first error of the charging data inside each single cell based on multiple charging data changes and the total capacity of the charging data of each single cell can be achieved by the following method: determining the mean square error of the first voltage error of the voltage data inside each single cell based on the total voltage capacity, the number of single cells, the number of first voltage changes of each single cell, and multiple first voltage changes.

[0064] The first voltage average of each single cell is multiplied by the number of single cells to obtain the second voltage average of the battery pack, which is recorded as The number of single cells is recorded as R V , according to the amount of the first voltage change of each single battery and the number of single batteries R V , the total voltage capacity of the battery pack can be determined, and the total voltage capacity of the battery pack is recorded as N V .

[0065] The mean square error MSE of the first voltage error of the voltage data inside the i-th single cell is determined by the following formula: V :

[0066]

[0067] Where KV is the number of ΔV inside the i-th single cell.

[0068] Furthermore, determining the statistical indicator of the second error of the charging data between each single cell based on the second charging data mean and the total capacity of the charging data can be achieved by the following method: determining the mean square error of the second voltage error of the voltage data between each single cell based on the number of single cells, the second voltage mean in the second charging data mean and the first voltage mean of each single cell.

[0069] Specifically, the mean square error MSA of the second voltage error of the voltage data between each single battery is calculated by the following formula: V :

[0070]

[0071] According to the statistical indicators of the first error and the second error, the statistical value of the charging data of each single cell is determined, and according to the number of single cells and the total capacity of the charging data, the critical value of the charging data is determined. This can be achieved by the following method: the ratio of the mean square error of the second voltage error to the mean square error of the first voltage error is determined as the voltage statistical value; according to the number of single cells and the total voltage capacity, the voltage critical value is determined.

[0072] Specifically, the voltage statistic F V =MSA V / MSE V , the voltage threshold is F V0.05 (R V -1,N V -R V )

[0073] Comparing the charging data statistics with the charging data critical value, and determining the charging data consistency evaluation index of the single cell based on the comparison result, can be achieved by the following method: when the voltage statistics is greater than or equal to the voltage critical value, determining that there is a difference in the voltage consistency of the battery pack in the electric vehicle.

[0074] That is to say, if F V Less than F V0.05 (R V -1,N V -R V ), it means that the voltage consistency of the single cell is not significant, otherwise it means that the voltage consistency of the single cell is significant.

[0075] F V0.05 is the critical value of F distribution, where R V -1, N V -R V , are the numerator and denominator degrees of freedom, respectively. In variance analysis, the calculated voltage statistics are compared with the voltage critical value to determine whether there is a significant difference in the means of different single cells.

[0076] F V0.05 The 0.05 in the equation is used to represent the significance level. For example, the numerator degrees of freedom is R V -1 is 3, and the denominator degree of freedom is N V -R V is 30, the critical value obtained by looking up the table may be 2.92. If the calculated voltage statistical value is greater than 2.92, it is determined that there is a difference in the voltage consistency of the battery pack in the electric vehicle.

[0077] According to some preferred embodiments of the present application, determining the amount of change in charging data of each single cell between every two consecutive sampling time points to obtain multiple amounts of charging data change of each single cell; determining the average of the multiple amounts of charging data change of each single cell to obtain the first average value of charging data of each single cell can be achieved by the following method: determining a third matrix and a fourth matrix according to the temperature data of each single cell, wherein the j-th column of the third matrix is ​​the temperature of the single cell corresponding to the j-th sampling time point, the rows of the third matrix and the fourth matrix are both used to characterize the number of single cells, the j-th column of the fourth matrix is ​​the temperature of the single cell corresponding to the j+1-th sampling time point, j is a positive integer not greater than m, m is the number of sampling time points, and m is an integer greater than 1; determining the first temperature change of each single cell between every two consecutive sampling time points according to the difference between the fourth matrix and the third matrix to obtain multiple first temperature changes of each single cell; determining the average of the multiple first temperature changes of each single cell to obtain the first temperature average of each single cell.

[0078] It can be understood that the rows of the above matrix are the numbers of the single cells, such as the 0th row is the single cell numbered 1, the 1st row is the single cell numbered 2, the 2nd row is the single cell numbered 3, and so on.

[0079] For example, the first temperature change is recorded as ΔT, and for the i-th single cell, its j-th first temperature change is ΔT ij If the sampling period includes 100 sampling time points, the single cell corresponds to 99 ΔT, and the first temperature change can be recorded as ΔT i1 , the 10th first temperature change can be recorded as ΔT i10 By adding 99 ΔT and dividing by 99, we can get the average of multiple first temperature changes, that is, the first temperature average of the i-th single cell, recorded as

[0080] Determining the statistical index of the first error of the charging data inside each single cell based on multiple charging data changes and the total capacity of the charging data of each single cell can be achieved by the following method: determining the mean square error of the first temperature error of the temperature data inside each single cell based on the total temperature capacity, the number of temperature sensors in the battery pack, the number of first temperature changes of each single cell, and multiple first temperature changes.

[0081] The first temperature average of each single cell is multiplied by the number of temperature sensors in the battery pack to obtain the second temperature average of the battery pack, which is recorded as The number of temperature sensors in the battery pack is denoted as R T, according to the number of first temperature changes of each single battery and the number of temperature sensors in the battery pack R T , the total temperature capacity of the battery pack can be determined, and the total temperature capacity of the battery pack is recorded as N T .

[0082] The mean square error MSE of the first temperature error of the temperature data inside the i-th single cell is determined by the following formula: T :

[0083]

[0084] Wherein, KT is the number of ΔT inside the i-th single cell.

[0085] Furthermore, determining the statistical indicator of the second error of the charging data between each single cell based on the second charging data mean and the total capacity of the charging data can be achieved by the following method: determining the mean square error of the second temperature error of the temperature data between each single cell based on the number of temperature sensors in the battery pack, the second temperature mean in the second charging data mean and the first temperature mean of each single cell.

[0086] Specifically, the mean square error MSA of the second temperature error of the temperature data between each single battery is calculated by the following formula: T :

[0087]

[0088] According to the statistical indicators of the first error and the second error, the statistical value of the charging data of each single battery is determined, and according to the number of temperature sensors in the battery pack and the total capacity of the charging data, the critical value of the charging data is determined. This can be achieved by the following method: the ratio of the mean square error of the second temperature error to the mean square error of the first temperature error is determined as the temperature statistical value; according to the number of temperature sensors in the battery pack and the total temperature capacity, the temperature critical value is determined.

[0089] Specifically, the temperature statistic F T =MSA T / MSE T , the critical temperature value is F T0.05 (R T -1,N T -R T ).

[0090] Comparing the charging data statistics with the charging data critical value, and determining the charging data consistency evaluation index of the single cell based on the comparison result, can be achieved by the following method: when the temperature statistics is greater than or equal to the temperature critical value, determining that there is a difference in the temperature consistency of the battery pack in the electric vehicle.

[0091] That is to say, if F T Less than F V0.05 (R T -1,N T -R T ), it means that the temperature consistency of the single cell is not significant, otherwise it means that the temperature consistency of the single cell is significant.

[0092] F T0.05 is the critical value of F distribution, where R T -1, N T -R T , which are the numerator and denominator degrees of freedom, respectively. In variance analysis, the calculated temperature statistics are compared with the temperature critical value to determine whether there is a significant difference in the means of different single cells.

[0093] F T0.05 The 0.05 in the equation is used to represent the significance level. For example, the numerator degrees of freedom is R T -1 is 3, and the denominator degree of freedom is N T -R T is 30, the critical value obtained by looking up the table may be 2.92. If the calculated temperature statistics value is greater than 2.92, it is determined that there is a difference in the temperature consistency of the battery pack in the electric vehicle.

[0094] Preferably, when it is determined that there is a difference in charging data consistency of the battery pack in the electric vehicle, a curve graph of the charging data change of each battery cell is generated, and the identification information of the sensor with the largest average charging data and the identification information of the battery pack with the largest average charging data are determined and displayed.

[0095] In other words, an early warning of poor consistency of battery cells is generated to remind relevant personnel to pay attention and handle it in time, so that relevant personnel can view or quickly locate it. Specifically, a curve chart of the voltage change of each battery cell and the temperature change of the temperature sensor is generated; the number of the temperature sensor with the largest average temperature difference, the number of the battery cell with the largest average voltage difference, the number of the battery cell with the largest battery cell voltage difference, the number of the battery cell with the lowest battery cell voltage, and the amount of significant difference are generated.

[0096] According to the above steps, the charging data of the battery pack in the electric vehicle within the sampling period is obtained, wherein the battery pack includes: a plurality of single cells, the sampling period includes: a plurality of sampling time points, and the charging data includes: voltage data and temperature data; the charging data change amount of each single cell between each two consecutive sampling time points is determined to obtain a plurality of charging data change amounts of each single cell; the mean of the plurality of charging data change amounts of each single cell is determined to obtain a first charging data mean value of each single cell; the total charging data capacity is determined according to the number of charging data change amounts and the number of single cells, and the second charging data mean value of the battery pack is determined according to the first charging data mean value of each single cell and the number of single cells; the charging data change amount of each single cell is determined according to the plurality of charging data change amounts of each single cell. and the total capacity of the charging data, determine the statistical index of the first error of the charging data within each single cell; determine the statistical index of the second error of the charging data between each single cell according to the mean value of the second charging data and the total capacity of the charging data; determine the charging data statistical value of each single cell according to the statistical index of the first error and the statistical index of the second error, and determine the charging data critical value according to the number of single cells and the total capacity of the charging data; compare the charging data statistical value with the charging data critical value, and determine the charging data consistency evaluation index of the single cell according to the comparison result, thereby achieving the purpose of accurately determining the consistency of the charging data based on the charging data of the battery pack within the sampling period, thereby realizing the technical effect of timely troubleshooting the safety hazards of the battery.

[0097] Figure 2 is a flow chart of another charging data consistency determination method according to an embodiment of the present application. Figure 2 As shown, the method includes the following steps.

[0098] Step S201, after the vehicle is charged, the cloud platform obtains the voltage and temperature data of the single battery during the vehicle charging process.

[0099] Step S202, cleaning and filtering the data acquired in step S201 to ensure the accuracy and reliability of the data.

[0100] Step S203, based on the data after data preprocessing, calculate the cell voltage change ΔV of each cell during the charging process i , Temperature change ΔT i .

[0101] Step S204, calculate the mean square error (MSE) of the data errors in each single cell V , MSE T ) to quantify the degree of data fluctuation.

[0102] Step S205, further calculating the mean square error (MSA) of the data errors between the single cells V 、MSA T ) to evaluate the consistency of performance between single cells.

[0103] Step S206, according to the principle of statistics, calculate the statistical value F and the critical value F 0.05 (R-1, NR), used for subsequent difference tests.

[0104] Step S207, verifying that the voltage and temperature consistency is significantly poor.

[0105] Step S208: determining whether the voltage and temperature are in poor consistency.

[0106] Step S209: Generate a warning of poor consistency of battery cells to remind relevant personnel to pay attention and handle it in time.

[0107] Step S210: data destruction to ensure that the data is not accessed, used or disclosed without authorization.

[0108] Specifically, step S201 can be implemented by the following method:

[0109] Step S2011, receiving the vehicle charging end notification (VIN code, charging start time, charging end time), if the charging time is too short, the notification is not processed.

[0110] Step S2012, reading the voltage data of all single cells in the battery pack and the temperature data of all temperature probes at the designated VIN code and the corresponding time from the database.

[0111] Specifically, step S202 can be implemented by the following method:

[0112] Step S2021, sorting the voltage and temperature data by acquisition time.

[0113] Step S2022, remove duplicate and redundant information, eliminate any erroneous data, and fill in missing data based on piecewise linear interpolation.

[0114] Step S2023, when the voltage and temperature cycle data change is too small (the slow charging time is relatively long), the data sampling period is appropriately adjusted to perform data resampling.

[0115] Wherein, step S2023 can be implemented by the following method:

[0116] Step S20231, determining the average voltage increment of each battery cell according to the number, quantity, charging voltage at the start time of charging, and charging voltage at the end time of charging of each battery cell:

[0117]

[0118] Where i is the i-th battery cell in the battery pack, R V is the number of battery cells, N is the time when battery charging ends, 0 is the time when charging starts, and V is the voltage.

[0119] Step S20232, determining the charging duration according to the charging start time and the charging end time: charging duration = charging end time - charging start time.

[0120] Step S20233, determining the expected sampling period according to the average voltage increment and preset parameters:

[0121]

[0122] The resampling period is a multiple of the terminal acquisition period.

[0123] Step S20234, discarding the data collected within the non-resampling period, and generating the voltage matrix and temperature matrix of the single cell.

[0124] Specifically, step S203 can be implemented by the following method:

[0125] Step S2031, construct two matrices, matrix A = all cell voltage matrix, matrix starting from column 1 to the end column; matrix B = all cell voltage matrix, matrix starting from column 0 to the column before the end column, ΔV matrix = matrix A - matrix B. In order to improve operation efficiency and performance, calculation can be performed based on GPU.

[0126] In step S2032, the temperature matrix ΔT can be obtained in the same way.

[0127] Specifically, step S204 can be implemented by the following method:

[0128] Step S2041, calculate each voltage monomer ΔV ij The mean value of i∈[0, number of voltage cells), j∈[0, KV), KV=voltage cell ΔV i Number, KT = temperature monomer ΔT i Number.

[0129] Step S2042, calculate total voltage capacity = KV × R V , the total voltage capacity is recorded as N V , R V is the number of battery cells; R T is the number of temperature probes, and the total temperature capacity is N T .

[0130] Step S2043, calculate the total mean voltage, recorded as

[0131] Step S2044, calculating the mean square error of the data error in each voltage cell

[0132] Step S2045, calculate the mean square error of the data error in each temperature unit

[0133] It is worth noting that in order to improve operating efficiency and performance, the above calculations can all be calculated using GPU operators.

[0134] Specifically, step S205 can be implemented by the following method:

[0135] Step S2051, calculate the mean square error of the voltage data errors between each cell

[0136] Step S2052, calculate the mean square error of the temperature data between each monomer

[0137] Specifically, step S206 can be implemented by the following method:

[0138] Step S2061: voltage statistic F V =MSA V / MSE V The voltage threshold is F V0.05 (R V -1,N V -R V ).

[0139] Step S2062, specifically, the temperature statistics F T =MSA T / MSE T The critical temperature is F T005 (R T -1,N T -R T ).

[0140] Specifically, step S207 can be implemented by the following method:

[0141] Step S2071, voltage significance determination: If F V Less than F V0.05 (R V -1,N V -R V ), it means that the voltage consistency of the single cell is not significant, otherwise it means that the voltage consistency of the single cell is significant.

[0142] Step S2072, temperature significance determination: If F T Less than F V0.05 (R T -1,N T -R T ), it means that the temperature consistency of the single cell is not significant, otherwise it means that the temperature consistency of the single cell is significant.

[0143] Specifically, step S209 can be implemented by the following method: generate an early warning of poor consistency of battery cells to remind relevant personnel to pay attention and handle it in time, so that relevant personnel can view or quickly locate: generate curves of voltage change of each cell and temperature change of probe; the probe number with the largest average temperature difference, the cell number with the largest average voltage difference, the cell number with the largest cell voltage difference, the cell number with the lowest battery cell voltage, and the amount of significant difference, etc.

[0144] Figure 3 is a structural diagram of a charging data consistency determination device according to an embodiment of the present application, such as Figure 3 As shown, the device comprises:

[0145] The acquisition module 31 is used to acquire charging data of a battery pack in an electric vehicle within a sampling period, wherein the battery pack includes: a plurality of single cells, the sampling period includes: a plurality of sampling time points, and the charging data includes: voltage data and temperature data;

[0146] The first determination module 32 is used to determine the charging data change amount of each single battery between each two consecutive sampling time points to obtain multiple charging data change amounts of each single battery; determine the average of the multiple charging data change amounts of each single battery to obtain the first charging data average of each single battery;

[0147] A second determination module 33, configured to determine the total capacity of the charging data according to the amount of charging data variation and the number of single cells, and to determine the second charging data mean of the battery pack according to the first charging data mean of each single cell and the number of single cells;

[0148] A third determination module 34 is used to determine a statistical indicator of a first error of the charging data inside each single cell according to a plurality of charging data changes and a total capacity of the charging data of each single cell;

[0149] A fourth determination module 35, configured to determine a statistical indicator of a second error of charging data between each single battery according to the second charging data mean value and the total capacity of the charging data;

[0150] A fifth determination module 36, configured to determine a charging data statistical value of each single battery according to the statistical index of the first error and the statistical index of the second error, and to determine a charging data critical value according to the number of single batteries and the total capacity of the charging data;

[0151] The comparison module 37 is used to compare the charging data statistics with the charging data critical value, and determine the charging data consistency evaluation index of the single battery according to the comparison result.

[0152] Optionally, the acquisition module 31 is also used to perform the following steps: obtain a notification message for indicating that the electric vehicle has ended charging, wherein the notification message includes at least: vehicle identification information of the electric vehicle, charging start time and charging end time; read the initial charging data of the battery pack of the electric vehicle corresponding to the vehicle identification information within the sampling period in the database; sort the initial charging data according to the sampling time, remove repeated parameters in the sorted initial charging data, and in the case where there is missing data in the sorted initial charging data, fill the missing data with a piecewise linear interpolation method to obtain the charging data of the battery pack in the electric vehicle within the sampling period; resample the charging data when the rate of change of the voltage data is less than a first preset threshold and / or the rate of change of the temperature data is less than a second preset threshold.

[0153] Optionally, the acquisition module 31 is also used to perform the following steps: determine the average voltage increment of each single cell according to the number and quantity of each single cell, the charging voltage at the start of charging, and the charging voltage at the end of charging; determine the charging time according to the start time and the end time of charging; determine the expected sampling period according to the average voltage increment and preset parameters; determine the resampling period according to the charging time, the expected sampling period and the original sampling period, wherein the resampling period is an integer multiple of the original sampling period; obtain the charging data of the battery pack in the electric vehicle within the resampling period.

[0154] Optionally, the first determination module 32 is further used to perform the following steps: determine a first matrix and a second matrix according to the voltage data of each single cell, wherein the i-th column of the first matrix is ​​the voltage of the single cell corresponding to the i-th sampling time point, the rows of the first matrix and the second matrix are both used to represent the number of single cells, and the i-th column of the second matrix is ​​the voltage of the single cell corresponding to the i+1-th sampling time point, i is a positive integer not greater than n, n is the number of sampling time points, and n is an integer greater than 1; determine the first voltage change of each single cell between every two consecutive sampling time points according to the difference between the second matrix and the first matrix, and obtain multiple first voltage changes of each single cell; determine the average of the multiple first voltage changes of each single cell, and obtain the first voltage average of each single cell.

[0155] Optionally, the third determination module 34 is also used to perform the following steps: determining the mean square error of the first voltage error of the voltage data inside each single cell according to the total voltage capacity in the total capacity of the charging data, the number of single cells, the number of first voltage changes of each single cell, and multiple first voltage changes; determining the statistical indicator of the second error of the charging data between each single cell according to the second charging data mean and the total capacity of the charging data, including: determining the mean square error of the second voltage error of the voltage data between each single cell according to the number of single cells, the second voltage mean in the second charging data mean, and the first voltage mean of each single cell.

[0156] Optionally, the fifth determination module 36 is also used to perform the following steps: determine the ratio of the mean square error of the second voltage error to the mean square error of the first voltage error as a voltage statistic; determine a voltage critical value based on the number of single cells and the total voltage capacity; compare the charging data statistic with the charging data critical value, and determine the charging data consistency evaluation index of the single cell based on the comparison result, including: when the voltage statistic is greater than or equal to the voltage critical value, determine that there is a difference in voltage consistency of the battery pack in the electric vehicle.

[0157] Optionally, the first determination module 32 is further used to perform the following steps: determine a third matrix and a fourth matrix according to the temperature data of each single cell, wherein the j-th column of the third matrix is ​​the temperature of the single cell corresponding to the j-th sampling time point, the rows of the third matrix and the fourth matrix are used to characterize the number of single cells, and the j-th column of the fourth matrix is ​​the temperature of the single cell corresponding to the j+1-th sampling time point, j is a positive integer not greater than m, m is the number of sampling time points, and m is an integer greater than 1; determine the first temperature change of each single cell between every two consecutive sampling time points according to the difference between the fourth matrix and the third matrix, and obtain multiple first temperature changes of each single cell; determine the average of the multiple first temperature changes of each single cell, and obtain the first temperature average of each single cell.

[0158] Optionally, the third determination module 34 is also used to perform the following steps: determine the mean square error of the first temperature error of the temperature data inside each single cell according to the total temperature capacity in the total capacity of the charging data, the number of temperature sensors in the battery pack, the number of first temperature changes of each single cell, and multiple first temperature changes; determine the statistical indicator of the second error of the charging data between each single cell according to the second charging data mean and the total capacity of the charging data, including: determine the mean square error of the second temperature error of the temperature data between each single cell according to the number of temperature sensors in the battery pack, the second temperature mean in the second charging data mean, and the first temperature mean of each single cell.

[0159] Optionally, the fifth determination module 36 is also used to perform the following steps: determine the ratio of the mean square error of the second temperature error to the mean square error of the first temperature error as a temperature statistic; determine the temperature critical value according to the number of temperature sensors in the battery pack and the total temperature capacity; compare the charging data statistic with the charging data critical value, and determine the charging data consistency evaluation index of the single cell battery based on the comparison result, including: when the temperature statistic is greater than or equal to the temperature critical value, determine that there is a difference in the temperature consistency of the battery pack in the electric vehicle.

[0160] Optionally, the comparison module 37 is also used to perform the following steps: when it is determined that there is a difference in the consistency of the charging data of the battery pack in the electric vehicle, generate a curve graph of the charging data change of each single battery, determine and display the identification information of the sensor with the largest average charging data and the identification information of the battery pack with the largest average charging data.

[0161] It should be noted that the above Figure 3 The modules in the embodiment may be program modules (e.g., a set of program instructions for implementing a specific function) or hardware modules. For the latter, they may be expressed in the following forms, but are not limited thereto: the expression form of the above modules is a processor, or the functions of the above modules are implemented by a processor.

[0162] It should be noted that Figure 3 The preferred implementation of the illustrated embodiment can be found in Figure 1 The relevant description of the illustrated embodiment will not be repeated here.

[0163] Figure 4 FIG. 1 shows a hardware structure block diagram of a computer terminal for implementing a method for determining charging data consistency. Figure 4 As shown, the computer terminal 40 may include one or more (402a, 402b, ..., 402n are used to illustrate) processors 402 (the processor 402 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 404 for storing data, and a transmission module 406 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 4 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 4 More or fewer components as shown, or with Figure 4 Different configurations are shown.

[0164] It should be noted that the one or more processors 402 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 40. As involved in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0165] The memory 404 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the charging data consistency determination method in the embodiment of the present application. The processor 402 executes various functional applications and data processing by running the software programs and modules stored in the memory 404, that is, the above-mentioned charging data consistency determination method is realized. The memory 404 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 404 may further include a memory remotely arranged relative to the processor 402, and these remote memories can be connected to the computer terminal 40 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0166] The transmission module 406 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 40. In one example, the transmission module 406 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission module 406 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0167] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 40 .

[0168] It should be noted that, in some optional embodiments, the above Figure 4 The computer terminal shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of hardware elements and software elements. It should be noted that Figure 4 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the computer terminal described above.

[0169] It should be noted that Figure 4 The computer terminal shown is used to execute Figure 1 The charging data consistency determination method shown in the figure, therefore the relevant explanations in the execution method of the above command are also applicable to the electronic device and will not be repeated here.

[0170] An embodiment of the present application further provides a non-volatile storage medium, the non-volatile storage medium includes a stored program, wherein when the program is executed, the device where the storage medium is located is controlled to execute the above charging data consistency determination method.

[0171] A program for a non-volatile storage medium to perform the following functions: obtaining charging data of a battery pack in an electric vehicle within a sampling period, wherein the battery pack includes: a plurality of single cells, the sampling period includes: a plurality of sampling time points, and the charging data includes: voltage data and temperature data; determining the amount of change in charging data of each single cell between each two consecutive sampling time points, and obtaining a plurality of amounts of change in charging data of each single cell; determining the average of the plurality of amounts of change in charging data of each single cell, and obtaining a first average of charging data of each single cell; determining the total capacity of the charging data according to the amount of the amount of change in charging data and the number of single cells, and obtaining a first average of charging data of each single cell according to the first average of charging data of each single cell and the number of single cells; determining the total capacity of the charging data according to the amount of the change in charging data and the number of single cells, and obtaining a first average of charging data of each single cell according to the first average of charging data of each single cell and the number of single cells; determining the total capacity of the charging data .... According to the amount of charging data variation of each single cell and the total capacity of charging data, determine the statistical index of the first error of charging data within each single cell; according to the second charging data mean and the total capacity of charging data, determine the statistical index of the second error of charging data between each single cell; according to the statistical index of the first error and the statistical index of the second error, determine the charging data statistical value of each single cell, and according to the number of single cells and the total capacity of charging data, determine the charging data critical value; compare the charging data statistical value with the charging data critical value, and determine the charging data consistency evaluation index of the single cell according to the comparison result.

[0172] An embodiment of the present application further provides an electronic device, including: a memory and a processor, wherein the processor is used to run a program stored in the memory, wherein the above charging data consistency determination method is executed when the program is running.

[0173] The processor is used to run a program that performs the following functions: obtaining charging data of a battery pack in an electric vehicle within a sampling period, wherein the battery pack includes: a plurality of single cells, the sampling period includes: a plurality of sampling time points, and the charging data includes: voltage data and temperature data; determining a charging data change amount of each single cell between each two consecutive sampling time points, and obtaining a plurality of charging data change amounts of each single cell; determining an average of a plurality of charging data change amounts of each single cell, and obtaining a first charging data average of each single cell; determining a total charging data capacity according to the number of charging data change amounts and the number of single cells, and obtaining a first charging data average of each single cell according to the first charging data average of each single cell and the number of single cells; determining a total charging data capacity ... According to the amount of charging data variation of each single cell and the total capacity of charging data, determine the statistical index of the first error of charging data within each single cell; according to the second charging data mean and the total capacity of charging data, determine the statistical index of the second error of charging data between each single cell; according to the statistical index of the first error and the statistical index of the second error, determine the charging data statistical value of each single cell, and according to the number of single cells and the total capacity of charging data, determine the charging data critical value; compare the charging data statistical value with the charging data critical value, and determine the charging data consistency evaluation index of the single cell according to the comparison result.

[0174] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0175] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0176] In the above-mentioned embodiments of the present application, the collected information is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary protection measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0177] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0178] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0179] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0180] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0181] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining charging data consistency, characterized in that: include: Obtain charging data of a battery pack in an electric vehicle within a sampling period, wherein the battery pack includes: a plurality of single cells, the sampling period includes: a plurality of sampling time points, and the charging data includes: Voltage data and temperature data; Determine the charging data change amount of each single cell between each two consecutive sampling time points to obtain multiple charging data change amounts of each single cell; determine the average of the multiple charging data change amounts of each single cell to obtain a first charging data average value of each single cell; Determine the total capacity of the charging data according to the amount of the charging data change and the number of the single cells, and determine the second charging data mean value of the battery pack according to the first charging data mean value of each of the single cells and the number of the single cells; Determine a statistical indicator of a first error of the charging data inside each of the single cells according to a plurality of charging data changes of each of the single cells and the total capacity of the charging data; Determining a statistical indicator of a second error of the charging data between the single cells according to the second charging data mean value and the total capacity of the charging data; Determine a charging data statistic value of each of the single cells according to the statistical index of the first error and the statistical index of the second error, and determine a charging data critical value according to the number of the single cells and the total capacity of the charging data; The charging data statistic value is compared with the charging data critical value, and the charging data consistency evaluation index of the single battery is determined according to the comparison result.

2. The method according to claim 1, characterized in that Obtain charging data of the battery pack in the electric vehicle during the sampling period, including: Acquire a notification message for indicating that the electric vehicle ends charging, wherein the notification message at least includes: vehicle identification information of the electric vehicle, charging start time, and charging end time; Reading in a database the initial charging data of the battery pack of the electric vehicle corresponding to the vehicle identification information within the sampling period; Sorting the initial charging data according to the sampling time, removing repeated parameters in the sorted initial charging data, and in the case where there are missing data in the sorted initial charging data, using piecewise linear interpolation to fill the missing data, so as to obtain the charging data of the battery pack in the electric vehicle within the sampling period; When the change rate of the voltage data is less than a first preset threshold and / or the change rate of the temperature data is less than a second preset threshold, the charging data is resampled.

3. The method according to claim 2, characterized in that When the change rate of the voltage data is less than a first preset threshold and / or the change rate of the temperature data is less than a second preset threshold, resampling the charging data includes: Determine the average voltage increment of each of the single cells according to the number, quantity, charging voltage at the start of charging, and charging voltage at the end of charging of each of the single cells; Determining a charging duration according to the charging start time and the charging end time; Determining an expected sampling period according to the voltage average increment and preset parameters; Determine a resampling period according to the charging duration, the predetermined sampling period and the original sampling period, wherein the resampling period is an integer multiple of the original sampling period; The charging data of the battery pack in the electric vehicle during the resampling period is obtained.

4. The method according to claim 1, characterized in that Determine the charging data change amount of each single battery between each two consecutive sampling time points to obtain multiple charging data change amounts of each single battery; Determining the average of the plurality of charging data changes of each of the single cells to obtain a first charging data average of each of the single cells comprises: Determine a first matrix and a second matrix according to the voltage data of each single cell, wherein the i-th column of the first matrix is ​​the voltage of the single cell corresponding to the i-th sampling time point, the rows of the first matrix and the second matrix are used to represent the number of the single cells, and the i-th column of the second matrix is ​​the voltage of the single cell corresponding to the i+1-th sampling time point, i is a positive integer not greater than n, n is the number of the sampling time points, and n is an integer greater than 1; Determine the first voltage variation of each of the single cells between each two consecutive sampling time points according to the difference between the second matrix and the first matrix, and obtain a plurality of first voltage variation of each of the single cells; An average value of a plurality of the first voltage changes of each of the single cells is determined to obtain an average value of the first voltage of each of the single cells.

5. The method according to claim 4, characterized in that Determining a statistical indicator of a first error of charging data within each of the single cells according to a plurality of charging data changes of each of the single cells and the total capacity of the charging data includes: Determine the mean square error of the first voltage error of the voltage data inside each of the single cells according to the total voltage capacity in the total capacity of the charging data, the number of the single cells, the number of the first voltage changes of each of the single cells, and the plurality of the first voltage changes; Determining a statistical indicator of a second error of charging data between each of the single cells according to the second charging data mean value and the total capacity of the charging data includes: A mean square error of a second voltage error of the voltage data between each of the single cells is determined according to the number of the single cells, the second voltage mean value in the second charging data mean value, and the first voltage mean value of each of the single cells.

6. The method according to claim 5, characterized in that Determining a charging data statistic value of each of the single cells according to the statistical index of the first error and the statistical index of the second error, and determining a charging data critical value according to the number of the single cells and the total capacity of the charging data, including: Determine a ratio of a mean square error of the second voltage error to a mean square error of the first voltage error as a voltage statistical value; Determining a voltage critical value according to the number of the single cells and the total voltage capacity; Comparing the charging data statistics with the charging data critical value, and determining the charging data consistency evaluation index of the single battery according to the comparison result, including: When the voltage statistical value is greater than or equal to the voltage critical value, it is determined that there is a difference in the voltage consistency of the battery pack in the electric vehicle.

7. The method according to claim 1, characterized in that Determine the charging data change amount of each single battery between each two consecutive sampling time points to obtain multiple charging data change amounts of each single battery; Determining the average of the plurality of charging data changes of each of the single cells to obtain a first charging data average of each of the single cells comprises: Determine a third matrix and a fourth matrix according to the temperature data of each single cell, wherein the j-th column of the third matrix is ​​the temperature of the single cell corresponding to the j-th sampling time point, the rows of the third matrix and the fourth matrix are used to represent the number of the single cells, and the j-th column of the fourth matrix is ​​the temperature of the single cell corresponding to the j+1-th sampling time point, j is a positive integer not greater than m, m is the number of the sampling time points, and m is an integer greater than 1; Determine, according to the difference between the fourth matrix and the third matrix, a first temperature variation of each of the single cells between each two consecutive sampling time points, to obtain a plurality of first temperature variations of each of the single cells; The average of the plurality of first temperature changes of each of the single cells is determined to obtain the first temperature average of each of the single cells.

8. The method according to claim 7, characterized in that Determining a statistical indicator of a first error of charging data within each of the single cells according to a plurality of charging data changes of each of the single cells and the total capacity of the charging data includes: Determine the mean square error of the first temperature error of the temperature data inside each of the single cells according to the total temperature capacity in the total charging data capacity, the number of temperature sensors in the battery pack, the number of the first temperature change amounts of each of the single cells, and the plurality of the first temperature change amounts; Determining a statistical indicator of a second error of charging data between each of the single cells according to the second charging data mean value and the total capacity of the charging data includes: A mean square error of a second temperature error of the temperature data between each of the single cells is determined according to the number of temperature sensors in the battery pack, a second temperature mean value in the second charging data mean value, and a first temperature mean value of each of the single cells.

9. The method according to claim 8, characterized in that Determining a charging data statistic value of each of the single cells according to the statistical index of the first error and the statistical index of the second error, and determining a charging data critical value according to the number of temperature sensors in the battery pack and the total capacity of the charging data, including: Determine a ratio of the mean square error of the second temperature error to the mean square error of the first temperature error as a temperature statistic value; Determining a temperature critical value according to the number of temperature sensors in the battery pack and the total temperature capacity; Comparing the charging data statistics with the charging data critical value, and determining the charging data consistency evaluation index of the single battery according to the comparison result, including: When the temperature statistic value is greater than or equal to the temperature critical value, it is determined that there is a difference in the temperature consistency of the battery pack in the electric vehicle.

10. The method according to claim 1, characterized in that Determining the charging data consistency evaluation index of the single cell, including: when it is determined that there is a difference in the charging data consistency of the battery pack in the electric vehicle, generating a curve graph of the charging data change of each single cell, determining and displaying the identification information of the sensor with the largest average charging data and the identification information of the battery pack with the largest average charging data.

11. A charging data consistency determination device, characterized in that: include: An acquisition module is used to acquire charging data of a battery pack in an electric vehicle within a sampling period, wherein the battery pack includes: a plurality of single cells, the sampling period includes: a plurality of sampling time points, and the charging data includes: voltage data and temperature data; A first determination module is used to determine the charging data change amount of each single cell between each two consecutive sampling time points to obtain multiple charging data change amounts of each single cell; determine the average of the multiple charging data change amounts of each single cell to obtain the first charging data average of each single cell; A second determination module is used to determine the total capacity of the charging data according to the amount of the charging data change and the number of the single cells, and to determine the second charging data mean value of the battery pack according to the first charging data mean value of each of the single cells and the number of the single cells; A third determination module, configured to determine a statistical indicator of a first error of the charging data inside each of the single cells according to the plurality of charging data changes and the total capacity of the charging data of each of the single cells; a fourth determining module, configured to determine a statistical indicator of a second error of the charging data between the single cells according to the second charging data mean value and the total capacity of the charging data; a fifth determination module, configured to determine a charging data statistical value of each of the single cells according to the statistical index of the first error and the statistical index of the second error, and to determine a charging data critical value according to the number of the single cells and the total capacity of the charging data; The comparison module is used to compare the charging data statistical value with the charging data critical value, and determine the charging data consistency evaluation index of the single battery according to the comparison result.

12. A non-volatile storage medium, characterized in that: The non-volatile storage medium includes a stored program, wherein when the program is executed, the device where the non-volatile storage medium is located is controlled to execute the charging data consistency determination method according to any one of claims 1 to 10.

13. An electronic device, characterized in that: include: A memory and a processor, wherein the processor is used to run a program stored in the memory, wherein the charging data consistency determination method according to any one of claims 1 to 10 is executed when the program is run.

14. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the charging data consistency determination method according to any one of claims 1 to 10 is implemented.

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