Method and device for correcting capacity detection of battery capacity grading cabinet and electronic equipment

Abstract

The invention provides a correction method and device for capacity detection of a battery capacity grading cabinet and electronic equipment. The correction method comprises the following steps: acquiring a battery capacity reference value of a batch of batteries to be detected; obtaining a battery capacity detection value of the batch of batteries to be detected, wherein the battery capacity detection value is obtained by carrying out battery capacity grading test on the batch of batteries to be detected through the battery capacity grading cabinet; determining a correction relation between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be detected; and correcting a capacity detection value obtained by carrying out capacity grading test on the battery by the battery capacity grading cabinet according to the correction relation. According to the correction method for the capacity detection of the battery capacity grading cabinet provided by the invention, the battery capacity detection value actually measured by the battery capacity grading cabinet is corrected by using the accurate reference value of the battery capacity of the batch of batteries to be detected, so that the capacity grading precision correction of the battery capacity grading cabinet is realized, and the accuracy of the battery capacity grading cabinet is improved on the basis of not increasing the hardware cost. The capacity grading precision of the battery capacity grading cabinet is improved, and the quality control of the battery core capacity grading process is facilitated.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of battery performance detection, and in particular to a correction method, device and electronic equipment for battery capacity detection of a battery sub-capacity cabinet. Background Art

[0002] The battery capacity sorting cabinet is a device specially used for capacity sorting and performance screening of batteries. The battery capacity sorting cabinet charges and discharges each battery and uses a computer to record the data of each test point to obtain data such as battery capacity and internal resistance, and then determine the quality grade of the battery. This process is called capacity sorting, which helps to quickly and accurately evaluate the capacity and performance of the battery and improve the efficiency and life of the battery.

[0003] However, in the prior art, as the battery capacity cabinet operates for a period of time, the aging of the internal components of the battery capacity cabinet will cause the accuracy of the battery capacity cabinet to decrease. For example, the aging of the sensor causes the accuracy of the collected data to decrease, and the measured battery capacity data differs too much from the actual battery capacity data. Summary of the invention

[0004] The embodiments of the present invention provide a correction method, device and electronic device for capacity detection of a battery capacity cabinet, so as to realize the correction of the capacity detection accuracy of the battery capacity cabinet. On the basis of not increasing the hardware cost, the capacity detection accuracy of the battery capacity cabinet is improved, which is helpful for the quality control of the battery cell capacity detection process.

[0005] According to a first aspect of the present invention, a method for correcting capacity detection of a battery capacity distribution cabinet is provided, comprising:

[0006] Obtain the battery capacity reference value of the battery batch to be tested;

[0007] Obtaining a battery capacity detection value of the batch of batteries to be tested by performing a battery capacity test on the batch of batteries to be tested through the battery capacity test cabinet;

[0008] Determining a correction relationship between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested;

[0009] The capacity detection value obtained by the battery capacity division cabinet through the battery capacity division test is corrected according to the correction relationship.

[0010] Optionally, before determining the correction relationship between the battery capacity reference value and the battery capacity detection value corresponding to the battery batch to be tested, the method further includes:

[0011] Determining the capacity division error of the battery capacity division cabinet according to the battery capacity reference value of the batch of batteries to be tested and the battery capacity detection value;

[0012] When the capacity division error is greater than or equal to a set threshold, the correction relationship between the battery capacity reference value and the battery capacity detection value is determined according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested.

[0013] Optionally, determining the capacity division error of the battery capacity division cabinet according to the battery capacity reference value of the batch of batteries to be tested and the battery capacity detection value includes:

[0014] Determine a mean absolute percentage error or a root mean square error according to the battery capacity reference values ​​and the battery capacity detection values ​​respectively corresponding to the plurality of batteries in the batch of batteries to be tested;

[0015] The mean absolute percentage error or the root mean square error is determined as the capacity division error.

[0016] Optionally, obtaining a battery capacity reference value of a batch of batteries to be tested includes:

[0017] Obtaining a battery capacity reference value of a battery batch to be tested at set time thresholds;

[0018] Determining the capacity division error of the battery capacity division cabinet according to the battery capacity reference value of the batch of batteries to be tested and the battery capacity detection value includes:

[0019] A time threshold is set at each interval, and a capacity division error of the battery capacity division cabinet is determined according to a battery capacity reference value of the batch of batteries to be tested and the battery capacity detection value.

[0020] Optionally, obtaining a battery capacity reference value of a batch of batteries to be tested includes:

[0021] Perform multiple charge and discharge tests on the batch of batteries to be tested using a battery charge and discharge test device to obtain the discharge capacity of multiple batteries in each charge and discharge test;

[0022] For each of the batteries, calculating the range of the discharge capacity of the battery obtained in n consecutive charge and discharge tests;

[0023] When the discharge capacity ranges corresponding to the batteries are all less than the set threshold, for each battery, the average discharge capacity of multiple batteries corresponding to n consecutive charge and discharge tests is used as the battery capacity reference value, where n≥3.

[0024] Optionally, determining the correction relationship between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested includes:

[0025] The battery capacity detection values ​​corresponding to the multiple batteries in the batch of batteries to be tested are taken as input, and the battery capacity reference values ​​corresponding to the multiple batteries in the batch of batteries to be tested are taken as output, and the correction relationship is obtained according to a linear machine learning model or a nonlinear machine model.

[0026] Optionally, taking the battery capacity reference values ​​corresponding to the multiple batteries in the batch of batteries to be tested as outputs, taking the battery capacity detection values ​​corresponding to the multiple batteries in the batch of batteries to be tested as inputs, and obtaining the correction relationship according to a linear machine learning model or a nonlinear machine model, includes:

[0027] Taking the battery capacity detection values ​​corresponding to the multiple batteries in the batch of batteries to be tested as input and the battery capacity reference values ​​corresponding to the multiple batteries in the batch of batteries to be tested as output, a linear machine learning model or a nonlinear machine model is trained to obtain model parameters, and then the correction relationship is obtained.

[0028] Optionally, the correcting the capacity detection value obtained by the battery capacity division cabinet performing a capacity division test on the battery according to the correction relationship includes:

[0029] Substitute the battery capacity detection value into the correction relationship as the input of the correction relationship to obtain the battery capacity cabinet capacity correction value.

[0030] According to a second aspect of the present invention, a correction device for battery capacity cabinet capacity detection is provided, the correction device comprising:

[0031] A battery capacity reference value acquisition module is used to obtain a battery capacity reference value of a batch of batteries to be tested;

[0032] A battery capacity detection value acquisition module is used to obtain the battery capacity detection value of the battery batch to be tested;

[0033] A correction relationship acquisition module, used for acquiring a correction relationship according to the battery capacity reference value and the battery capacity detection value of the batch of batteries to be tested;

[0034] A correction module is used to correct the battery capacity detection value according to the correction relationship.

[0035] According to a third aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0036] one or more processors;

[0037] a storage device for storing one or more programs,

[0038] When the one or more programs are executed by the one or more processors, the one or more processors implement the correction method for battery capacity cabinet capacity detection as described in any of the above invention contents.

[0039] In the correction method for capacity detection of a battery capacity cabinet provided in an embodiment of the present invention, a battery capacity reference value is obtained for a batch of batteries to be tested as the actual battery capacity value of the batch of batteries to be tested. Then, the battery capacity cabinet to be corrected is used to perform a capacity test on the batch of batteries to be tested to obtain a battery capacity detection value. A correction relationship between the battery capacity reference value and the battery capacity detection value is established. This correction relationship is the correction relationship between the actual capacity value of the battery and the battery capacity value detected by the battery capacity cabinet to be corrected. The capacity detection value obtained by performing a capacity test on the battery is corrected according to the obtained correction relationship. The correction method for capacity detection of a battery capacity cabinet provided in an embodiment of the present invention realizes the correction of the battery capacity detection value detected by the battery capacity cabinet to be corrected, so that the battery capacity value detected by the battery capacity cabinet is closer to the actual capacity value of the battery, improves the accuracy of the test result, and makes the test result of the battery capacity cabinet more reliable and better able to reflect the true performance of the battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the contents of the embodiments of the present invention and these drawings without paying any creative work.

[0041] Figure 1 It is a flow chart of a method for correcting capacity detection of a battery capacity distribution cabinet provided by an embodiment of the present invention;

[0042] Figure 2 It is a flow chart of another method for correcting capacity detection of a battery capacity distribution cabinet provided by an embodiment of the present invention;

[0043] Figure 3 It is a line chart of the battery capacity reference value and the battery capacity detection value of the batch of batteries to be tested provided by the embodiment of the present invention;

[0044] Figure 4 It is a flow chart of another method for correcting capacity detection of a battery capacity distribution cabinet provided by an embodiment of the present invention;

[0045] Figure 5 It is a flow chart of another method for correcting capacity detection of a battery capacity distribution cabinet provided by an embodiment of the present invention;

[0046] Figure 6 is a voltage curve diagram of a single battery charge and discharge test over time provided by an embodiment of the present invention;

[0047] Figure 7 It is a line graph of battery capacity results of each battery in the batch of batteries to be tested in three charge and discharge tests provided by an embodiment of the present invention;

[0048] Figure 8 is a battery capacity range line graph obtained from three consecutive discharge capacity tests provided by an embodiment of the present invention;

[0049] Fig. 9 It is a flow chart of another method for correcting capacity detection of a battery capacity distribution cabinet provided by an embodiment of the present invention;

[0050] Fig.10 It is a correction relationship fitting diagram using linear regression (LR) model;

[0051] Fig.11 It is a correction relationship fitting diagram using Gaussian process regression (GPR) model;

[0052] Fig.12 It is a flow chart of another method for correcting capacity detection of a battery capacity distribution cabinet provided by an embodiment of the present invention;

[0053] Fig.13 It is the battery capacity detection value corresponding to each battery of another batch of batteries provided by the embodiment of the present invention, the battery capacity reference value, the battery capacity value corrected by the capacity distribution cabinet correction relationship 1 (LR) and the battery capacity value corrected by the capacity distribution cabinet correction relationship 2 (GPR);

[0054] Fig.14 A schematic diagram of the structure of a correction device for capacity detection of a battery capacity distribution cabinet provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0056] Figure 1 : is a flow chart of a method for correcting capacity detection of a battery capacity distribution cabinet provided by an embodiment of the present invention, such as Figure 1 As shown, the correction methods include:

[0057] S101, obtaining a battery capacity reference value of a batch of batteries to be tested.

[0058] Specifically, a battery capacity reference value of the batch of batteries to be tested is obtained after continuous charge and discharge tests are performed on the batch of batteries to be tested using high-precision battery charge and discharge experimental testing equipment and in accordance with laboratory testing procedures and standards.

[0059] Since the test equipment used in step S101 is a high-precision equipment and the test process is a standard laboratory process, the obtained battery capacity reference value can be used as the actual battery capacity value of the batch of batteries to be tested. The obtained battery capacity reference value of the batch of batteries to be tested is used to correct the subsequent capacity detection of the sub-capacity cabinet.

[0060] Optionally, the battery capacity reference value of the batch of batteries to be tested may be data provided by the manufacturer. Battery types include, but are not limited to: lithium batteries, sodium ion batteries, solid-state batteries or lead-acid batteries.

[0061] S102, obtaining battery capacity detection values ​​of the batch of batteries to be tested by performing a battery capacity test on the batch of batteries to be tested through a battery capacity test cabinet.

[0062] The battery capacity classification cabinet is used to perform a battery capacity classification test on the batch of batteries to be tested, and the battery capacity detection value of each battery in the batch of batteries to be tested of the battery capacity classification cabinet to be corrected is obtained.

[0063] S103, determining a correction relationship between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested.

[0064] After obtaining the battery capacity reference value corresponding to the batch of batteries to be tested in step S101 and obtaining the battery capacity detection value after the battery capacity cabinet to be corrected performs the capacity detection test on the same batch of batteries in step S102, a relationship between the battery capacity reference value and the battery capacity detection value can be established. This relationship is manifested as a deviation, error or trend, which reflects the possible problems or errors in the battery capacity cabinet when testing this batch of batteries. By analyzing the difference between the two values, a correction relationship can be established to adjust or correct the test results of the battery capacity cabinet to make it closer to the actual capacity of the battery.

[0065] Optionally, the relationship between the battery capacity reference value and the battery capacity detection value can be established by training a linear machine learning model or a nonlinear machine learning model.

[0066] S104, correcting the capacity detection value obtained by the battery capacity division cabinet through the capacity division test on the battery according to the correction relationship.

[0067] After obtaining the correction relationship, the error correction of the battery capacity test of the battery capacity cabinet is carried out to eliminate or reduce the error in the test process and improve the accuracy of the test results. The test results of the battery capacity cabinet are more reliable and can better reflect the real performance of the battery.

[0068] In the correction method for capacity detection of a battery capacity cabinet provided in an embodiment of the present invention, a battery capacity reference value is obtained for a batch of batteries to be tested as the actual battery capacity value of the batch of batteries to be tested. Then, the battery capacity cabinet to be corrected is used to perform a capacity test on the batch of batteries to be tested to obtain a battery capacity detection value. A correction relationship between the battery capacity reference value and the battery capacity detection value is established. This correction relationship is the correction relationship between the actual capacity value of the battery and the battery capacity value detected by the battery capacity cabinet to be corrected. The capacity detection value obtained by performing a capacity test on the battery is corrected according to the obtained correction relationship. The correction method for capacity detection of a battery capacity cabinet provided in an embodiment of the present invention realizes the correction of the battery capacity detection value detected by the battery capacity cabinet to be corrected, so that the battery capacity value detected by the battery capacity cabinet is closer to the actual capacity value of the battery, improves the accuracy of the test result, and makes the test result of the battery capacity cabinet more reliable and better able to reflect the true performance of the battery.

[0069] Figure 2 FIG. 1 is a flow chart of another method for correcting the capacity detection of a battery sub-capacity cabinet provided by an embodiment of the present invention. Figure 2 As shown, based on the above embodiments, the correction method includes:

[0070] S201, obtaining a battery capacity reference value of a batch of batteries to be tested.

[0071] S202, obtaining battery capacity detection values ​​of the batch of batteries to be tested by performing a battery capacity test on the batch of batteries to be tested through a battery capacity test cabinet.

[0072] S203, determining the capacity division error of the battery capacity division cabinet according to the battery capacity reference value and the battery capacity detection value of the batch of batteries to be tested.

[0073] When the internal sensors and other components of the battery capacity cabinet are in good condition or the test environment is more appropriate, the battery capacity detection value detected by the battery capacity cabinet for the batch of batteries to be tested is closer to the actual capacity value of the batch of batteries to be tested. Optionally, the battery capacity cabinet capacity detection may not be corrected at this time.

[0074] When the battery capacity detection value measured by the battery capacity cabinet differs greatly from the actual capacity value of the battery batch to be tested, it means that the capacity detection of the battery capacity cabinet needs to be corrected.

[0075] Specifically, in step S203, the capacity reference value of the battery batch to be tested and the capacity error of the battery capacity cabinet are determined to determine whether to correct the capacity detection of the battery capacity cabinet.

[0076] Among them, optionally, when obtaining the battery capacity reference value and the battery capacity detection value of the battery batch to be tested and determining the capacity detection error of the battery capacity detection cabinet, the average absolute percentage error or the root mean square error is determined according to the battery capacity reference value and the battery capacity detection value respectively corresponding to multiple batteries in the battery batch to be tested; the average absolute percentage error or the root mean square error is determined as the capacity detection error.

[0077] Figure 3 is a line chart of the battery capacity reference value and the battery capacity detection value of the batch of batteries to be tested provided by the embodiment of the present invention, such as Figure 3 As shown, the horizontal axis represents the serial numbers of the 50 batteries in the batch of batteries to be tested, and the two broken lines respectively represent the battery capacity reference value corresponding to each battery in the batch of batteries to be tested and the battery capacity corresponding to the battery capacity detection value measured by the test capacity cabinet.

[0078] The reference value and test value corresponding to each battery are significantly different. Figure 3 The data was analyzed and the average absolute percentage error between the reference value and the test value was 1.33%, the root mean square error was 0.026Ah, and the maximum absolute percentage error was 1.78%.

[0079] The error relationship between the test value and the reference value can be determined by the mean absolute percentage error or the root mean square error.

[0080] S204, determining whether the capacity division error is greater than or equal to a set threshold.

[0081] After obtaining the capacity division error of the battery capacity division cabinet in step S203, the capacity division error is compared with a set threshold.

[0082] Specifically, when the capacity division error is greater than or equal to the set threshold, it means that the battery capacity division cabinet needs to be corrected for the capacity division cabinet capacity detection. It is necessary to determine the correction relationship between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested.

[0083] Optionally, when the capacity division error is less than a set threshold, it means that the battery capacity detection value detected by the battery capacity division cabinet for the batch of batteries to be tested is relatively close to the actual capacity value of the batch of batteries to be tested. It is not necessary to correct the capacity detection of the battery capacity division cabinet. When the capacity division error is less than the set threshold, step S202 is executed to re-acquire the battery capacity detection value of the batch of batteries to be tested. The specific method steps after the capacity division error is less than the set threshold are determined according to actual needs and are not limited here.

[0084] Continue to refer Figure 3 , in the above Figure 3 According to the analysis of the data, the average absolute percentage error between the reference value and the test value is 1.33%, the root mean square error is 0.026Ah, and the maximum absolute percentage error is 1.78%.

[0085] The error relationship between the test value and the reference value is determined by the mean absolute percentage error or the root mean square error. The threshold is set according to the requirements for battery quality. For example, the mean absolute error between the test value and the reference value is determined as the capacity error, and the threshold is set to 1% according to the requirements for battery quality. Figure 3 If the average absolute error between the reference value and the test value of the tested batch of batteries is greater than the set threshold, it means that the capacity detection of the capacity distribution cabinet needs to be corrected. Therefore, the correction relationship between the battery capacity reference value and the battery capacity detection value corresponding to the tested batch of batteries is determined.

[0086] S205, determining a correction relationship between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested.

[0087] S206, correcting the capacity detection value obtained by the battery capacity division cabinet through the capacity division test on the battery according to the correction relationship.

[0088] Figure 4 FIG. 1 is a flow chart of another method for correcting the capacity detection of a battery sub-capacity cabinet provided by an embodiment of the present invention. Figure 4 As shown, based on the above embodiments, the correction method includes:

[0089] S301, obtaining a battery capacity reference value of a battery batch to be tested at every set time threshold.

[0090] At every set time threshold, a battery capacity reference value of the battery batch to be tested is obtained for subsequent determination of the capacity division error of the battery capacity division cabinet.

[0091] Optionally, the time threshold is set to one week or one month, which is not limited here.

[0092] S302, obtaining battery capacity detection values ​​of the batch of batteries to be tested by performing a battery capacity test on the batch of batteries to be tested through a battery capacity test cabinet.

[0093] Optionally, when the set time threshold is less than the set time threshold, step S302 is executed to obtain the battery capacity detection value after the battery capacity division cabinet performs the battery capacity division test on the batch of batteries to be tested. Since the set time threshold is not reached, it is not necessary to determine whether the correction relationship needs to be updated. Therefore, after the battery capacity detection value of the batch of batteries to be tested is obtained in step S302, step S306 is executed to correct the capacity detection value obtained by the battery capacity division cabinet performing the battery capacity division test according to the correction relationship.

[0094] S303, determining the capacity division error of the battery capacity division cabinet according to the battery capacity reference value and the battery capacity detection value of the batch of batteries to be tested at set time thresholds.

[0095] After the battery capacity distribution cabinet has been running for a long time, the accuracy of its battery capacity test (i.e., capacity distribution accuracy) will gradually change. In order to effectively monitor this change, a time threshold is set. Whenever the running time of the battery capacity distribution cabinet reaches or exceeds this time threshold, a periodic test of the capacity distribution error is performed. Through this test, potential error problems can be discovered and solved in a timely manner, thereby ensuring the accuracy and reliability of the battery capacity distribution cabinet test.

[0096] Optionally, the time threshold is set to one week or one month, which is not limited here.

[0097] S304: Determine whether the capacity division error is greater than or equal to a set threshold

[0098] S305, when the capacity division error is greater than or equal to the set threshold, determining a correction relationship between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested.

[0099] S306, correcting the capacity detection value obtained by the battery capacity division cabinet through the capacity division test on the battery according to the correction relationship.

[0100] Figure 5 FIG. 1 is a flow chart of another method for correcting the capacity detection of a battery sub-capacity cabinet provided by an embodiment of the present invention. Figure 5 As shown, based on the above embodiments, the correction method includes:

[0101] S401, using a battery charge and discharge test equipment to perform multiple charge and discharge tests on a batch of batteries to be tested, and obtaining the discharge capacity of multiple batteries in each charge and discharge test.

[0102] Figure 6 It is a voltage curve diagram of a single battery charge and discharge test changing with time provided by an embodiment of the present invention.

[0103] like Figure 6The battery is tested for capacity based on full charge and discharge three times in a row using a high-precision battery charge and discharge device to obtain the discharge capacity of multiple batteries in each charge and discharge test. Optionally, the battery is tested for capacity based on full charge and discharge three times in a row using a high-precision battery charge and discharge device. During these three charge and discharge processes, the voltage of the battery changes periodically with time and charge and discharge operations. Based on the relationship between voltage and time, the discharge capacity value of each battery in three consecutive tests is calculated using the ampere-hour integration method.

[0104] Exemplarily, for each battery, the range of the discharge capacity of the battery obtained in three consecutive charge and discharge tests is calculated. Figure 7 It is a line chart of the battery capacity results of each battery in the batch of batteries to be tested in three charge and discharge tests provided by the embodiment of the present invention.

[0105] like Figure 7 As shown, three charge and discharge tests were performed: Q1, Q2 and Q3. The horizontal axis represents the number of each battery in the batch of batteries to be tested. Figure 7 The battery discharge capacity value obtained for each battery during each charge and discharge test is shown.

[0106] S402, for each battery, calculate the range of the discharge capacity of the battery obtained in n consecutive charge and discharge tests; when the range of the discharge capacity corresponding to each battery is less than the set threshold, for each battery, the average value of the discharge capacity of multiple batteries corresponding to n consecutive charge and discharge tests is used as the battery capacity reference value, where n≥3.

[0107] Exemplarily, for each battery, the range of the discharge capacity of the battery obtained in three consecutive charge and discharge tests is calculated; when the range of the discharge capacity corresponding to each battery is less than a set threshold, for each battery, the average value of the discharge capacity of multiple batteries corresponding to the three consecutive charge and discharge tests is used as the battery capacity reference value.

[0108] Optionally, the threshold value may be set to 3% of the rated capacity of the battery.

[0109] Figure 8 It is a line graph of battery capacity extreme difference obtained from three consecutive discharge capacity tests provided in an embodiment of the present invention.

[0110] like Figure 8 As shown, after obtaining the battery discharge capacity value of each battery in each discharge test in the above steps, the battery capacity range obtained by three consecutive discharge capacity tests is calculated. The threshold is set to 0.054Ah, and the battery capacity range obtained by three consecutive charge and discharge capacity tests of each battery is less than 0.054Ah, then the average value of the discharge capacity of these three tests is the battery capacity reference value of this batch of batteries.

[0111] Optionally, if the battery capacity range obtained from the three consecutive charge and discharge capacity tests of each battery exceeds a set threshold, the discharge capacity test is continued.

[0112] S403, obtaining battery capacity detection values ​​of the batch of batteries to be tested by performing a battery capacity test on the batch of batteries to be tested through a battery capacity test cabinet.

[0113] S404, determining a correction relationship between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested.

[0114] S405, correcting the capacity detection value obtained by the battery capacity division cabinet through the capacity division test on the battery according to the correction relationship.

[0115] Fig. 9 FIG. 1 is a flow chart of another method for correcting the capacity detection of a battery sub-capacity cabinet provided by an embodiment of the present invention. Fig. 9 As shown, based on the above embodiments, the correction method includes:

[0116] S501, obtaining a battery capacity reference value of a batch of batteries to be tested.

[0117] S502, obtaining battery capacity detection values ​​of the batch of batteries to be tested by performing a battery capacity test on the batch of batteries to be tested through a battery capacity test cabinet.

[0118] S503, using the battery capacity detection values ​​corresponding to the multiple batteries in the batch of batteries to be tested as input, and using the battery capacity reference values ​​corresponding to the multiple batteries in the batch of batteries to be tested as output, and obtaining a correction relationship according to a linear machine learning model or a nonlinear machine model.

[0119] Taking the battery capacity detection values ​​corresponding to multiple batteries in the batch of batteries to be tested as input and the battery capacity reference values ​​corresponding to multiple batteries in the batch of batteries to be tested as output, a linear machine learning model or a nonlinear machine model is trained to obtain model parameters, and then a correction relationship is obtained.

[0120] Optionally, with the battery capacity detection value as input and the battery capacity reference value as output, a linear regression (LR) model and a Gaussian process regression (GPR) model are selected to learn the correction relationship.

[0121] For example, Fig.10This is a correction relationship fitting diagram using a linear regression (LR) model. After obtaining the battery capacity test value and the battery capacity reference value, the battery capacity test values ​​corresponding to multiple batteries in the batch of batteries to be tested are used as input, and the battery capacity reference values ​​corresponding to multiple batteries in the batch of batteries to be tested are used as output. The linear regression (LR) model is trained and the model parameters are obtained, and the correction relationship is obtained: y = 0.9933x-0.0127.

[0122] Fig.11 This is a correction relationship fitting diagram using the Gaussian process regression (GPR) model. Fig.11 As shown, the battery capacity detection values ​​corresponding to the multiple batteries in the batch of batteries to be tested are used as input, and the battery capacity reference values ​​corresponding to the multiple batteries in the batch of batteries to be tested are used as output. The Gaussian process regression (GPR) model is used to fit the correction relationship to obtain the correction relationship: y = f GP (x). The implicit relationship learned using the Gaussian process regression (GPR) model is nonlinear.

[0123] S504, correcting the capacity detection value obtained by the battery capacity division cabinet through the capacity division test on the battery according to the correction relationship.

[0124] Fig.12 FIG. 1 is a flow chart of another method for correcting the capacity detection of a battery sub-capacity cabinet provided by an embodiment of the present invention. Fig.12 As shown, based on the above embodiments, the correction method includes:

[0125] S601, obtaining a battery capacity reference value of a batch of batteries to be tested.

[0126] S602, obtaining battery capacity detection values ​​of the batch of batteries to be tested by performing a battery capacity test on the batch of batteries to be tested through a battery capacity test cabinet.

[0127] S603, determining a correction relationship between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested.

[0128] S604, substituting the battery capacity detection value into the correction relationship as an input of the correction relationship to obtain a battery capacity cabinet capacity correction value.

[0129] Exemplarily, based on the above embodiments, the correction relationship between the battery capacity reference value and the battery capacity detection value is obtained by two fitting methods. Fig.13 It is the battery capacity detection value corresponding to each battery of another batch of batteries provided in an embodiment of the present invention, the battery capacity reference value, the battery capacity value corrected by the capacity distribution cabinet correction relationship 1 (LR) and the battery capacity value corrected by the capacity distribution cabinet correction relationship 2 (GPR).

[0130] Based on the above embodiments, Fig.13 As shown, after obtaining the correction relationship between the battery capacity reference value and the battery capacity detection value, the correction relationship is verified. Select another batch of batteries and obtain the battery capacity reference value and battery capacity detection value of each battery capacity of the batch of batteries. Fig.13 It can be seen that the average absolute percentage error between each battery capacity reference value and the battery capacity detection value of this batch of batteries is 1.30%, the root mean square error is 0.0258Ah, and the maximum absolute percentage error is 1.8202%. Therefore, it shows that the capacity division error of the capacity division cabinet is relatively large.

[0131] The line graph of "Correction 1 (LR) of the capacity cabinet" is obtained by using the linear regression (LR) model to obtain the correction relationship 1 (LR), and then the battery capacity detection value is substituted into the correction relationship as the input of the correction relationship to obtain the battery capacity cabinet capacity correction value 1. The line graph of "Correction 2 (GPR) of the capacity cabinet" is obtained by using the Gaussian process regression (GPR) model to obtain the correction relationship 2 (GPR), and then the battery capacity detection value is substituted into the correction relationship as the input of the correction relationship to obtain the battery capacity cabinet capacity correction value 2. It can be seen that the battery capacity cabinet capacity correction value 1 and the battery capacity cabinet capacity correction value 2 are closer to the battery capacity reference value than the battery capacity detection value.

[0132] The performance analysis of correction relationship 1 (LR) and correction relationship 2 (GPR) is performed: the battery capacity cabinet capacity correction value 1 and the battery capacity cabinet capacity correction value 2 are compared with the battery capacity reference value respectively.

[0133] Compared with the battery capacity reference value, the average absolute percentage error of the battery capacity cabinet correction value 1 obtained by correction relationship 1 (LR) is 0.1698%, the root mean square error is 0.0047Ah, and the maximum absolute percentage error is 0.6093%. Compared with the battery capacity cabinet correction value 2 obtained by correction relationship 2 (GPR), the average absolute percentage error is 0.1588%, the root mean square error is 0.0044Ah, and the maximum absolute percentage error is 0.5292%. It can be seen that both correction relationships can improve the detection accuracy of the capacity cabinet.

[0134] The embodiment of the present invention provides a correction method for battery capacity detection. The method includes: selecting a linear regression model or a nonlinear regression model to fit the correction relationship between the battery capacity reference value and the battery capacity detection value. When the nonlinear regression model is selected to fit the correction relationship between the battery capacity reference value and the battery capacity detection value, the correction relationship obtained can better improve the detection accuracy of the capacity cabinet, and the obtained battery capacity cabinet capacity correction value is closer to the battery capacity reference value. When the linear regression model is selected to fit the correction relationship between the battery capacity reference value and the battery capacity detection value, the calculation efficiency is high. And the stability of the correction relationship fitted by the linear regression model is also good: when the correction relationship is run for a period of time, even if the battery capacity detection value fluctuates slightly, the linear regression model can still maintain good prediction performance. By using the correction method for battery capacity detection provided by the embodiment of the present invention, the battery capacity detection accuracy of the capacity cabinet is greatly improved.

[0135] Fig.14 A structural schematic diagram of a battery capacity detection correction device provided by an embodiment of the present invention, such as Fig.14 As shown, the correction device comprises:

[0136] A battery capacity reference value acquisition module 701 is used to acquire a battery capacity reference value of a batch of batteries to be tested;

[0137] A battery capacity detection value acquisition module 702 is used to obtain the battery capacity detection value of the batch of batteries to be tested;

[0138] A correction relationship acquisition module 703, used to acquire a correction relationship according to a battery capacity reference value and a battery capacity detection value of a batch of batteries to be tested;

[0139] The correction module 704 is used to correct the battery capacity detection value according to the correction relationship.

[0140] A correction device for capacity detection of a battery capacity cabinet provided in an embodiment of the present invention can achieve the same technical effect as a correction method for capacity detection of a battery capacity cabinet provided in the above-mentioned embodiment of the invention, which will not be repeated here.

[0141] Based on the above embodiments, an embodiment of the present invention provides an electronic device, which includes: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by one or more processors, the one or more processors implement the correction method for battery capacity cabinet capacity detection in any of the above embodiments.

[0142] Specifically, the processor and the storage device in the electronic device may be connected via a bus or other means.

[0143] The storage device is a computer-readable storage medium that can be used to store software programs, computer executable programs and modules. The processor executes various functional applications and data processing of the electronic device by running the software programs, instructions and modules stored in the storage device, that is, the correction method for battery capacity cabinet capacity detection described in any of the above embodiments is implemented.

[0144] The storage device may mainly include a program storage area and a data storage area. Among them, the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal, etc. In addition, the storage device may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the storage device may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the electronic device 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 combinations thereof.

[0145] An electronic device provided in an embodiment of the present invention can achieve the same technical effect as the correction method for capacity detection of a battery capacity cabinet provided in the above-mentioned embodiment of the invention, which will not be described in detail here.

[0146] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A correction method for battery capacity detection cabinet, characterized in that: include: Obtain the battery capacity reference value of the battery batch to be tested; Obtaining a battery capacity detection value of the batch of batteries to be tested by performing a battery capacity test on the batch of batteries to be tested through the battery capacity test cabinet; Determining a correction relationship between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested; The capacity detection value obtained by the battery capacity division cabinet through the battery capacity division test is corrected according to the correction relationship.

2. The correction method for battery capacity detection of the battery capacity cabinet according to claim 1 is characterized in that: Before determining the correction relationship between the battery capacity reference value and the battery capacity detection value according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested, the method further includes: Determining the capacity division error of the battery capacity division cabinet according to the battery capacity reference value of the batch of batteries to be tested and the battery capacity detection value; When the capacity division error is greater than or equal to a set threshold, the correction relationship between the battery capacity reference value and the battery capacity detection value is determined according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested.

3. The correction method for battery capacity detection of the battery capacity cabinet according to claim 2 is characterized in that: The determining the capacity division error of the battery capacity division cabinet according to the battery capacity reference value of the batch of batteries to be tested and the battery capacity detection value comprises: Determine a mean absolute percentage error or a root mean square error according to the battery capacity reference values ​​and the battery capacity detection values ​​respectively corresponding to the plurality of batteries in the batch of batteries to be tested; The mean absolute percentage error or the root mean square error is determined as the capacity division error.

4. The correction method for battery capacity detection of the battery sub-capacity cabinet according to claim 2 is characterized in that: The step of obtaining a reference value of the battery capacity of the batch of batteries to be tested includes: Obtaining a battery capacity reference value of a battery batch to be tested at set time thresholds; Determining the capacity division error of the battery capacity division cabinet according to the battery capacity reference value of the batch of batteries to be tested and the battery capacity detection value includes: A time threshold is set at each interval, and a capacity division error of the battery capacity division cabinet is determined according to a battery capacity reference value of the batch of batteries to be tested and the battery capacity detection value.

5. The correction method for battery capacity detection of the battery sub-capacity cabinet according to claim 1 is characterized in that: The step of obtaining a reference value of the battery capacity of the batch of batteries to be tested includes: Perform multiple charge and discharge tests on the batch of batteries to be tested using a battery charge and discharge test device to obtain the discharge capacity of multiple batteries in each charge and discharge test; For each of the batteries, calculating the range of the discharge capacity of the battery obtained in n consecutive charge and discharge tests; When the discharge capacity ranges corresponding to the batteries are all less than the set threshold, for each battery, the average discharge capacity of multiple batteries corresponding to n consecutive charge and discharge tests is used as the battery capacity reference value, where n≥3.

6. The correction method for battery capacity detection of the battery capacity cabinet according to claim 1 is characterized in that: The determining, according to the battery capacity reference value and the battery capacity detection value corresponding to the batch of batteries to be tested, a correction relationship between the battery capacity reference value and the battery capacity detection value comprises: The battery capacity detection values ​​corresponding to the multiple batteries in the batch of batteries to be tested are taken as input, and the battery capacity reference values ​​corresponding to the multiple batteries in the batch of batteries to be tested are taken as output, and the correction relationship is obtained according to a linear machine learning model or a nonlinear machine model.

7. The correction method for battery capacity detection of the battery capacity cabinet according to claim 6 is characterized in that: Taking the battery capacity reference values ​​corresponding to the multiple batteries in the batch of batteries to be tested as outputs, taking the battery capacity detection values ​​corresponding to the multiple batteries in the batch of batteries to be tested as inputs, and obtaining the correction relationship according to a linear machine learning model or a nonlinear machine model, including: Taking the battery capacity detection values ​​corresponding to the multiple batteries in the batch of batteries to be tested as input and the battery capacity reference values ​​corresponding to the multiple batteries in the batch of batteries to be tested as output, a linear machine learning model or a nonlinear machine model is trained to obtain model parameters, thereby obtaining the correction relationship.

8. The correction method for battery capacity detection of a battery capacity cabinet according to claim 1 is characterized in that: The method of correcting the capacity detection value obtained by the battery capacity division cabinet through the battery capacity division test according to the correction relationship includes: Substitute the battery capacity detection value into the correction relationship as the input of the correction relationship to obtain the battery capacity cabinet capacity correction value.

9. A correction device for battery capacity detection cabinet, characterized in that: include: A battery capacity reference value acquisition module is used to obtain a battery capacity reference value of a batch of batteries to be tested; A battery capacity detection value acquisition module is used to obtain the battery capacity detection value of the battery batch to be tested; A correction relationship acquisition module, used for acquiring a correction relationship according to the battery capacity reference value and the battery capacity detection value of the batch of batteries to be tested; A correction module is used to correct the battery capacity detection value according to the correction relationship.

10. An electronic device, characterized in that: The electronic device comprises: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the correction method for battery capacity cabinet capacity detection as described in any one of claims 1-8.

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