Battery self-discharge detection method, device, electronic device and storage medium

Abstract

The present application provides a battery self-discharge detection method, device, electronic device, and storage medium, relating to the field of battery technology, including: obtaining battery voltage change rate sample data and self-discharge history data based on battery performance data; determining a standard value of the battery's voltage change rate within a target cycle based on the voltage change rate sample data and self-discharge history data, wherein the target cycle includes at least two cycles of different lengths; the self-discharge history data includes a historical voltage change rate; and performing self-discharge anomaly detection on the battery based on the actual voltage change rate of the battery and the standard value of the voltage change rate of the target cycle. The present application can specifically address the limitations of existing battery self-discharge rate detection.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a battery self-discharge detection method, device, electronic device, and storage medium. Background Art

[0002] A battery's self-discharge rate can be characterized by its K value, which refers to the rate of change of the battery's open-circuit voltage (OCV) over a specific time interval. By testing whether a battery's K value meets self-discharge standards, you can detect micro-short circuits, evaluate the battery's self-discharge characteristics, and screen out unqualified batteries.

[0003] Currently, the same self-discharge standard is used when testing the K value of batteries. This fails to take into account that the self-discharge performance of batteries will change with the use and storage time of batteries. If the same self-discharge standard is used to test the K value, there are limitations, which will affect the accuracy of the battery self-discharge test results.

[0004] It should be noted that the above statements are only used to provide background technical information related to this application and do not necessarily constitute prior art. Summary of the Invention

[0005] In view of this, the purpose of this application is to propose a battery self-discharge detection method, device, electronic device and storage medium. This application can specifically solve the limitations of existing battery self-discharge rate detection.

[0006] Based on the above-mentioned purpose, in a first aspect, the present application proposes a battery self-discharge detection method, comprising: obtaining voltage change rate sample data and self-discharge history data of the battery based on battery performance data; the self-discharge history data includes a historical voltage change rate; based on the voltage change rate sample data and the self-discharge history data, determining a standard value of the voltage change rate of the battery within a target cycle, the target cycle including at least two cycles of different lengths; and performing self-discharge abnormality detection on the battery according to the actual voltage change rate of the battery and the standard value of the voltage change rate of the target cycle.

[0007] The above embodiment can obtain standard values ​​for the voltage rate of change within different cycles. Based on the battery's actual voltage rate of change and the standard value for the voltage rate of change during the target cycle, the battery's self-discharge anomaly detection can be performed. This allows different standard values ​​for the voltage rate of change to be selected for different target cycles to detect the battery's self-discharge performance within each cycle, making battery self-discharge detection more flexible and applicable to multiple scenarios. For example, the actual voltage rate of change and the standard value for the voltage rate of change within a short cycle can be used to reflect the battery's initial state; the actual voltage rate of change and the standard value for the voltage rate of change within a long cycle can be used to reflect the battery's stability and lifespan.

[0008] In some embodiments, the self-discharge abnormality detection of the battery is performed based on the actual voltage change rate of the battery and the standard value of the voltage change rate of the target cycle, including: obtaining the cycle to be detected, and determining the standard value of the voltage change rate corresponding to the cycle to be detected; the cycle to be detected includes at least one of the target cycles; based on the actual voltage change rate of the battery in the cycle to be detected being greater than the standard value of the voltage change rate corresponding to the cycle to be detected, determining that the battery has self-discharge abnormality.

[0009] The above embodiment can accurately determine whether the battery has self-discharge anomaly based on the comparison of the actual voltage change rate within the detection period with the standard value, which helps to improve the accuracy and efficiency of battery self-discharge anomaly screening at different time scales.

[0010] In some embodiments, based on the voltage change rate sample data and the self-discharge history data, determining the standard value of the voltage change rate of the battery within the target cycle includes: performing statistical analysis based on the voltage change rate sample data to obtain the voltage change rate sample value of the battery; obtaining the voltage change rate theoretical value according to the self-discharge history data; and determining the standard value of the voltage change rate of the battery within the target cycle according to the minimum value between the voltage change rate sample value and the voltage change rate theoretical value.

[0011] The voltage change rate sample value of the battery is obtained through statistical analysis methods, so that the voltage change rate sample value is more in line with the actual self-discharge performance of the battery. The voltage change rate theoretical value is obtained based on the self-discharge historical data. Taking into account that different batches of batteries may have different self-discharge characteristics, the voltage change rate standard value of the battery within the target cycle is determined based on the minimum value between the voltage change rate sample value and the voltage change rate theoretical value. Dynamic adjustment of the voltage change rate standard value can be achieved, which can better adapt to the characteristic changes of different batches of batteries and ensure the consistency and accuracy of the screening results.

[0012] In some embodiments, the target cycle includes a first cycle, and statistical analysis is performed based on the voltage change rate sample data to obtain a voltage change rate sample value of the battery, including: performing statistical analysis on the voltage change rate sample data of the battery in the first cycle to obtain a first mean value and a first standard deviation that characterize the voltage change rate distribution information; obtaining a first voltage change rate sample value based on the first mean value, the first standard deviation and a first coefficient, the first voltage change rate sample value being used to determine a standard value of the voltage change rate of the battery in the first cycle, the first coefficient including any integer between 1 and 6, and the size of the first coefficient being positively correlated with the qualified rate of the battery.

[0013] The above embodiment can improve the accuracy of the first voltage change rate sample value by performing statistical analysis on the voltage change rate sample data. The preset pass rate control parameters can be used to adjust the screening strictness according to needs, flexibly adjust the screening criteria, and adapt to different application scenarios.

[0014] In some embodiments, obtaining a voltage change rate theoretical value based on self-discharge history data includes: using the historical voltage change rate as a first theoretical value of the voltage change rate, wherein the historical voltage change rate includes an average voltage change rate of the battery within a historical detection time period.

[0015] By using the battery's self-discharge history data as a factor in determining the standard value of the voltage change rate, the inconsistent battery performance characteristics of different batches of batteries can be taken into account, making the obtained standard value of the voltage change rate more accurate, reducing the impact of fluctuations in the current sample data on the battery self-discharge test results, and enabling a more comprehensive evaluation of the battery's performance.

[0016] In some embodiments, the target cycle includes a first cycle and a second cycle, the duration of the second cycle is greater than the duration of the first cycle, and the self-discharge history data also includes a capacity conversion pressure difference within a historical detection time period, and the capacity conversion pressure difference is obtained after voltage conversion of the capacity attenuation of the battery within the historical detection time period; obtaining a theoretical value of the voltage change rate based on the self-discharge history data includes: obtaining a first value based on the historical voltage change rate and a preset first self-discharge adjustment coefficient; obtaining a second value based on the capacity conversion pressure difference and a preset second self-discharge adjustment coefficient; determining a second theoretical value of the voltage change rate based on the minimum value of the first value and the second value, and the second theoretical value of the voltage change rate is used to determine a standard value of the voltage change rate of the battery in the second cycle.

[0017] The above embodiment is directed to the second cycle, and simultaneously obtains the second theoretical value of the voltage change rate based on the historical voltage change rate and the conversion voltage difference within the historical detection time period. At the same time, the influence of the voltage change rate and the conversion voltage difference on the battery self-discharge detection accuracy is taken into account. The combination of the two can more comprehensively cover the influence of different factors on the long-term performance of the battery, making the standard value of the voltage change rate in the second cycle more accurate.

[0018] In some embodiments, the sample data of the battery in the second cycle includes sample data of qualified self-discharge batteries in the first cycle and sample data of unqualified self-discharge batteries in the first cycle; performing statistical analysis based on the voltage change rate sample data of the battery to obtain a voltage change rate sample value of the battery, including: performing statistical analysis on the sample data of the qualified battery to obtain a second mean value and a second standard deviation characterizing the voltage change rate distribution information of the qualified battery, and obtaining the voltage change rate of the qualified battery based on the second mean value, the second standard deviation and the second coefficient; performing statistical analysis on the sample data of the unqualified battery to obtain a third mean value and a third standard deviation characterizing the voltage change rate distribution information of the unqualified battery, and obtaining the voltage change rate of the unqualified battery based on the third mean value, the third standard deviation and the third coefficient; the second coefficient and the third coefficient include any integer between 1 and 6, and the magnitude of the second coefficient and the third coefficient is positively correlated with the qualified rate of the battery; and determining the second voltage change rate sample value based on the minimum value of the voltage change rate of the qualified battery and the voltage change rate of the unqualified battery.

[0019] By analyzing sample data from qualified and unqualified batteries and taking into account abnormal self-discharge characteristics of the batteries, the above embodiment can reduce misjudgments caused by data fluctuations or outliers, and improve the calculation accuracy of the voltage rate of change sample values ​​within the second cycle. Furthermore, by using the minimum of the voltage rate of change of the qualified battery and the voltage rate of change of the unqualified battery as the second voltage rate of change sample value, it is possible to tighten testing standards and thereby improve the quality of batteries shipped.

[0020] In some embodiments, the method further includes: determining a temperature compensation coefficient corresponding to the current test condition based on the current test condition of the battery, the temperature compensation coefficient being obtained by data fitting the open circuit voltage of the battery under different test conditions, the test conditions including different temperatures and at least one of different states of charge of the battery; obtaining the compensated open circuit voltage based on the current open circuit voltage, current temperature and temperature compensation coefficient corresponding to the current test condition of the battery; determining the current voltage change rate of the battery based on the standing time at the target temperature and the compensated open circuit voltage corresponding to the start and end times of the standing time.

[0021] In the above embodiment, by introducing a temperature compensation coefficient obtained by data fitting of the open circuit voltage of the battery under different test conditions during the process of calculating the voltage change rate, the influence of different test temperatures on the open circuit voltage measurement results can be eliminated. The compensated open circuit voltage can more realistically reflect the voltage change rate of the battery under different operating temperatures, thereby improving the accuracy of battery self-discharge detection.

[0022] In some embodiments, the method further includes: obtaining an error threshold based on a standard value of the voltage change rate of the battery within a target cycle and a preset error coefficient, wherein the open circuit voltage influencing factor includes at least one of the test environment temperature, battery polarization error, and equipment test error; for each test condition, when the quantized value of the open circuit voltage influencing factor is less than the error threshold, performing data fitting on the open circuit voltage of the battery under the test condition to obtain a temperature compensation coefficient corresponding to the test condition.

[0023] In the above embodiment, by quantifying the specific effects of open-circuit voltage influencing factors such as ambient temperature, test error, and polarization on the measured battery voltage change rate, when the quantized value of the open-circuit voltage influencing factor is less than the error control amount, data fitting is performed on the open-circuit voltage of the battery under the test conditions, and then the temperature compensation coefficient corresponding to the test conditions is obtained, thereby further improving the calculation accuracy of the voltage change rate.

[0024] In some embodiments, after determining the current voltage change rate of the battery, the method further includes: obtaining the standard temperature difference corresponding to the current test conditions based on the standard value of the voltage change rate of the battery, the current voltage change rate of the battery, the standing time, and the temperature compensation coefficient; obtaining the actual temperature difference corresponding to the current test conditions based on the battery temperature at the first moment and the battery temperature at the second moment; generating ambient temperature control information based on the actual temperature difference being greater than or equal to the standard temperature difference, and the ambient temperature control information being used to control the test temperature of the battery so that the actual temperature difference is less than the standard temperature difference.

[0025] The above embodiment regulates the actual temperature difference through the standard temperature difference, forming a temperature closed-loop control. It can realize that when the voltage change rate is temperature compensated, the static temperature difference for calculating the voltage change rate is controlled at the same time, and the temperature of the test environment is automatically adjusted to ensure the consistency of the test conditions, which can effectively reduce the impact of temperature changes on battery testing.

[0026] In a second aspect, a battery self-discharge detection device is also provided, which includes: a data acquisition module for acquiring voltage change rate sample data and self-discharge history data of the battery based on battery performance data; the self-discharge history data includes historical voltage change rate; a standard value calculation module for determining the standard value of the voltage change rate of the battery within a target cycle based on the voltage change rate sample data and the self-discharge history data, wherein the target cycle includes at least two cycles of different lengths; and a detection module for performing self-discharge abnormality detection on the battery based on the actual voltage change rate of the battery and the standard value of the voltage change rate of the target cycle.

[0027] In a third aspect, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in the first aspect.

[0028] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and the program is executed by a processor to implement any method described in the first aspect.

[0029] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In the accompanying drawings, unless otherwise specified, identical reference numerals throughout the multiple drawings represent identical or similar components or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings depict only some embodiments disclosed herein and should not be construed as limiting the scope of this application. Furthermore, identical reference numerals are used throughout the drawings to represent identical components.

[0031] Figure 1 A flowchart showing the steps of a battery self-discharge detection method according to an embodiment of the present application;

[0032] Figure 2 shows a curve showing a change in open circuit voltage and temperature according to an embodiment of the present application;

[0033] Figure 3 A graph showing the relationship between the voltage change rate and temperature provided in this embodiment is shown;

[0034] Figure 4 A flow chart showing the steps of a temperature compensation method according to an embodiment of the present application is shown;

[0035] Figure 5 A flowchart showing the steps of a method for detecting battery self-discharge in a first cycle provided by an embodiment of the present application is shown;

[0036] Figure 6 A flowchart showing the steps of a method for detecting battery self-discharge in a second cycle provided by an embodiment of the present application is shown;

[0037] Figure 7 Another step flow chart of the temperature compensation method provided by one embodiment of the present application is shown;

[0038] Figure 8 A schematic structural diagram of a battery self-discharge detection device provided in one embodiment of the present application is shown;

[0039] Figure 9 A schematic structural diagram of an electronic device provided in one embodiment of the present application is shown;

[0040] Figure 10 A schematic diagram of a storage medium provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0041] The following embodiments of the technical solution of the present application will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application and are therefore only examples and are not intended to limit the scope of protection of the present application.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0043] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0044] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0045] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0046] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0047] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0048] Currently, market developments indicate that power batteries are becoming increasingly widely used. They are not only used in energy storage systems such as hydropower, thermal, wind, and solar power plants, but are also widely used in electric vehicles like electric bicycles, electric motorcycles, and electric vehicles, as well as in military equipment and aerospace. As power battery applications continue to expand, market demand is also growing.

[0049] A battery's self-discharge rate can be characterized by its K value. For example, it can be expressed as a voltage drop per unit time. The K value refers to the rate of change of the battery's open-circuit voltage (OCV) over a certain time interval. The units of K value can be expressed in mV / d (millivolts per day) or mV / h (millivolts per hour). The self-discharge K value is calculated as: K = (OCV1 - OCV2) / (t2 - t1), where OCV1 is the battery's open-circuit voltage measured at time t1; OCV2 is the battery's open-circuit voltage measured at time t2, and (t2 - t1) is the time interval between the two measurements.

[0050] By testing the battery's K value to see if it meets the self-discharge standard, you can detect whether the battery has a micro-short circuit or evaluate the battery's self-discharge characteristics, thereby screening out unqualified batteries. Currently, when testing the battery's K value, the same self-discharge standard is used. This fails to take into account that the battery's self-discharge performance will change with the increase in battery use and storage time. If the same self-discharge standard is used to test the K value, there are limitations, which will affect the accuracy of the battery self-discharge test results.

[0051] Among them, the battery can be a battery product such as a battery module, a battery pack or a battery cell. For the convenience of explanation in the following embodiments, the embodiments of this application are described using a battery cell as an example.

[0052] Based on the above problems, this embodiment determines the standard value of the battery's voltage change rate within a target cycle based on the battery's voltage change rate sample data and self-discharge history data. The target cycle includes at least two cycles of different lengths. In this way, the standard values ​​of the voltage change rate within different cycles can be obtained. Then, based on the battery's actual voltage change rate and the standard value of the voltage change rate within the target cycle, the battery is subjected to self-discharge abnormality detection. In this way, for different target cycles, different standard values ​​of the voltage change rate can be selected to respectively detect the battery's self-discharge performance within each cycle.

[0053] For example, based on the actual voltage change rate of the battery in a short cycle and the standard value of the voltage change rate, it is possible to detect whether the battery is abnormal in a short cycle, thereby reflecting the initial state of the battery; based on the actual voltage change rate of the battery in a long cycle and the standard value of the voltage change rate, it is possible to detect whether the battery is abnormal in a long cycle, thereby reflecting the stability and life of the battery, making battery self-discharge detection more flexible, suitable for multiple scenarios, and more targeted and accurate.

[0054] Figure 1 The flowchart of the steps of the battery self-discharge detection method of the present application is shown. The execution subject of the embodiment of the present application can be an electronic device that can execute the battery self-discharge detection method, and the electronic device can include but is not limited to a terminal or a server. Figure 1 As shown, in the embodiment of the present application, the battery self-discharge detection method includes the following steps S101 to S103:

[0055] S101 . Obtaining battery voltage change rate sample data and self-discharge history data based on battery performance data.

[0056] Battery performance data may include various parameters of the battery under different operating conditions and life cycle stages. For example, battery performance data includes basic performance parameters such as open-circuit voltage, current, capacity under test conditions, operating status data such as operating voltage, temperature, internal resistance, and safety performance data such as short-circuit current and thermal runaway characteristics.

[0057] The battery voltage change rate sample data refers to the voltage change rate data obtained by performing self-discharge testing on the battery under certain test conditions (which can be a preset test temperature, battery state of charge, and test equipment within an error threshold) during the normal battery production process.

[0058] In this embodiment, the battery performance data includes voltage data under test conditions and operating status data within a historical time period. The voltage data under test conditions can be used to obtain sample data of the battery's voltage change rate, such as obtaining the voltage drop per unit time based on the voltage value at the starting moment of the unit time, and then obtaining the voltage change rate K value.

[0059] The operating status data within a historical time period can be used to obtain historical self-discharge data. Historical self-discharge data refers to data that characterizes the battery's self-discharge performance during the historical detection period. Historical self-discharge data includes the historical voltage change rate. The historical detection period can be a fixed period, such as a week, month, quarter, or other preset period.

[0060] S102 : Determine a standard value of the voltage change rate of the battery within a target cycle based on the voltage change rate sample data and the self-discharge history data.

[0061] In this embodiment, the target period includes at least two periods of different lengths, such as a first period, a second period, and a third period, with the lengths of the first, second, and third periods increasing in sequence. This allows for analysis of the battery's self-discharge performance over short, medium, and long periods, with the specific number of periods customizable based on actual needs. For example, a short period can be 1 to 5 days. Analyzing the battery's voltage change rate over these short periods can assess the battery's self-discharge performance over these short periods and quickly identify any initial self-discharge issues. A medium period can be 5 to 30 days. Analyzing the battery's voltage change rate over these periods can assess the battery's self-discharge performance over these periods, balancing test time and comprehensive performance evaluation, helping to identify potential issues that might be overlooked in short-term testing. A long period can be 30 to 90 days. Analyzing the battery's voltage change rate during long-term storage can assess the battery's self-discharge performance during long-term storage and use, thereby enabling battery life assessment and long-term quality monitoring, improving battery reliability. For ease of illustration, this embodiment uses the target period as an example, with the first period comprising the short period and the second period comprising the long period.

[0062] In one example, due to factors such as the production batches of batteries, the consistency of materials within each batch, and the stability of the manufacturing process, which lead to inconsistent battery performance, different batches of batteries may have different self-discharge rates. For example, batteries of the same type in one batch may exhibit a higher self-discharge rate than batteries in other batches. Therefore, this embodiment uses the battery's self-discharge history data as a factor in determining the standard value of the voltage change rate. This factor can take into account the inconsistent battery performance characteristics of different batches of batteries, making the resulting standard value of the voltage change rate more accurate, enabling a more comprehensive assessment of battery performance and ensuring the consistency and reliability of product quality.

[0063] S103 : Perform a self-discharge abnormality detection on the battery according to the actual voltage change rate of the battery and the standard value of the voltage change rate of the target cycle.

[0064] After obtaining the standard voltage change rate value for each target cycle, the battery can be tested for self-discharge anomalies based on the relationship between the battery's actual voltage change rate during the corresponding cycle and the standard voltage change rate value for the target cycle. For example, if the battery's actual voltage change rate during a target cycle is greater than the standard voltage change rate value, the battery is determined to be experiencing abnormal self-discharge, and the battery is considered unqualified.

[0065] The above embodiment can obtain standard values ​​for the voltage rate of change within different cycles. Based on the battery's actual voltage rate of change and the standard value for the voltage rate of change during the target cycle, the battery's self-discharge anomaly detection can be performed. This allows different standard values ​​for the voltage rate of change to be selected for different target cycles to detect the battery's self-discharge performance within each cycle, making battery self-discharge detection more flexible and applicable to multiple scenarios. For example, the actual voltage rate of change and the standard value for the voltage rate of change within a short cycle can be used to reflect the battery's initial state; the actual voltage rate of change and the standard value for the voltage rate of change within a long cycle can be used to reflect the battery's stability and lifespan.

[0066] In an embodiment of the present application, a battery is subjected to self-discharge abnormality detection based on the actual voltage change rate of the battery and the standard value of the voltage change rate of a target cycle, including: obtaining a cycle to be detected and determining the standard value of the voltage change rate corresponding to the cycle to be detected; the cycle to be detected includes at least one of the target cycles; and determining that the battery has self-discharge abnormality based on the actual voltage change rate of the battery during the cycle to be detected being greater than the standard value of the voltage change rate corresponding to the cycle to be detected.

[0067] In this embodiment, the detection period can be determined by the user. For example, the user can determine the detection period based on the application scenario. In a scenario where the battery needs to be shipped quickly, the detection period can be the first period. For a scenario where the battery needs to be stored for a long time, the detection period can be the second period.

[0068] Taking the second cycle as an example, after obtaining that the second cycle is to be detected, a voltage change rate standard value matching the second cycle is obtained, and then the actual voltage change rate standard value of the battery in the second cycle is obtained. If the actual voltage change rate standard value is greater than the voltage change rate standard value of the second cycle, it is determined that the battery has a self-discharge abnormality. If the actual voltage change rate standard value is less than or equal to the voltage change rate standard value of the second cycle, it is also determined that the battery has a self-discharge abnormality.

[0069] The above embodiment can accurately determine whether the battery has self-discharge anomaly based on the comparison of the actual voltage change rate within the detection period with the standard value, which helps to improve the accuracy and efficiency of battery self-discharge anomaly screening at different time scales.

[0070] In an embodiment of the present application, a standard value of the voltage change rate of the battery within a target cycle is determined based on the voltage change rate sample data and the self-discharge history data, including: performing statistical analysis based on the voltage change rate sample data to obtain a voltage change rate sample value of the battery; obtaining a voltage change rate theoretical value based on the self-discharge history data; and determining the standard value of the voltage change rate of the battery within the target cycle based on the minimum value between the voltage change rate sample value and the voltage change rate theoretical value.

[0071] Before statistical analysis is performed on the voltage change rate sample data of the battery, this embodiment also performs data processing such as outlier screening on the voltage change rate sample data. For example, the voltage change rate sample data is obtained by collecting multiple voltage change rate sample values ​​under normal mass production. The number of samples can be determined according to the actual calculation accuracy. For example, the sample size N is 500-1000 voltage change rate sample values. These sample values ​​are subjected to outlier or scatter point removal to eliminate test anomalies and timeout scatter points. For example, scatter point specifications are set to eliminate sample values ​​that do not meet the scatter point specifications. The scatter point specifications can be that the voltage change rate is within the range of "median + (median - minimum value)". The quartile method can also be used to remove outliers from the screened data until no discrete data appears.

[0072] Statistical analysis of the processed voltage rate of change sample data yields battery voltage rate of change sample values, improving calculation accuracy. For example, the mean-standard deviation method (mean & sigma technique) can be used to analyze the data. In statistics, the mean (mean) reflects the central tendency of the data, while the standard deviation (sigma, σ) measures the degree of dispersion. A larger standard deviation indicates more dispersed data, while a smaller standard deviation indicates more concentrated data. The voltage rate of change sample values ​​obtained through statistical analysis of the voltage rate of change sample data can reflect the actual performance of the battery.

[0073] In this embodiment, the self-discharge history data includes a historical voltage change rate. Taking the historical monthly voltage change rate as an example, the historical monthly voltage change rate can be used as the theoretical voltage change rate value to reflect the self-discharge performance of the battery over the historical time period. In one example, the self-discharge history data may include one historical monthly voltage change rate or multiple historical monthly voltage change rates. If the self-discharge history data includes one historical monthly voltage change rate, the historical monthly voltage change rate can be used as the theoretical voltage change rate value. If the self-discharge history data includes multiple historical monthly voltage change rates, the theoretical voltage change rate value can be the average of the multiple historical monthly voltage change rates.

[0074] This embodiment determines the standard value of the voltage change rate of the battery within the target cycle based on the minimum value between the voltage change rate sample value and the voltage change rate theoretical value, so that the voltage change rate standard value is more stringent. For example, if the voltage change rate theoretical value is smaller than the voltage change rate sample value, it means that the historical performance of the battery is good, and the battery performance represented by the current sample data is inferior to the historical performance, and then the voltage change rate theoretical value is selected as the voltage change rate standard value. On the contrary, it means that the battery performance represented by the current sample data is better than the historical performance, and then the voltage change rate sample value is selected as the voltage change rate standard value. This can improve the accuracy of battery self-discharge abnormality detection, increase the strictness of detection, and prevent defective products from being missed.

[0075] The above embodiment obtains the voltage change rate sample value of the battery through a statistical analysis method, so that the voltage change rate sample value is more in line with the actual self-discharge performance of the battery. The theoretical value of the voltage change rate is obtained based on the self-discharge historical data. Taking into account that different batches of batteries may have different self-discharge characteristics, the standard value of the voltage change rate of the battery within the target cycle is determined based on the minimum value of the voltage change rate sample value and the theoretical value of the voltage change rate. Dynamic adjustment of the standard value of the voltage change rate can be achieved, which can better adapt to the characteristic changes of different batches of batteries and ensure the consistency and accuracy of the screening results.

[0076] In an embodiment of the present application, the target period includes at least two periods of different lengths. This embodiment takes the first period and the second period as examples. The length of the second period is greater than that of the first period. For example, the first period corresponds to a short period, and the second period corresponds to a long period. The first period is, for example, one day, and the second period is, for example, three months. The specific lengths of the first period and the second period can be determined based on the detection accuracy.

[0077] In an embodiment of the present application, the target cycle includes a first cycle, and statistical analysis is performed based on the voltage change rate sample data of the battery to obtain a voltage change rate sample value of the battery, including: performing statistical analysis on the voltage change rate sample data of the battery in the first cycle to obtain a first average value and a first standard deviation that characterize the voltage change rate distribution information; obtaining a first voltage change rate sample value based on the first average value, the first standard deviation and the first coefficient, and the first voltage change rate sample value is used to determine the voltage change rate standard value of the battery in the first cycle.

[0078] Taking the first cycle as one day as an example, outliers are removed from the battery voltage change rate sample data for the day to ensure data representativeness and accuracy. Statistical analysis is then performed using the mean-standard deviation method to obtain a first mean and first standard deviation. For clarity, the voltage change rate corresponding to the first cycle is denoted as K1. The first voltage change rate sample value is then derived based on the mean value (Mean1) and standard deviation (σ1) of K1, along with a first coefficient. In this embodiment, the first coefficient is an integer between 1 and 6, and its magnitude is positively correlated with the battery's pass rate. The first coefficient represents a pass rate control parameter, for example, denoted by n1, which can range from 1 to 6. The first voltage change rate sample value can be expressed as (Mean1 + n1σ1), where n1 is used to adjust the control stringency. A larger n1 value indicates a higher inspection standard, indicating stricter process control and a lower defective product rate. For example, if the qualified rate is required to reach 99.73%, then n is usually 3, and the corresponding defective rate is about 2700ppm (about 2700 defective products per million products).

[0079] The above embodiment can improve the accuracy of the first voltage change rate sample value by performing statistical analysis on the voltage change rate sample data. The preset pass rate control parameters can be used to adjust the screening strictness according to needs, flexibly adjust the screening criteria, and adapt to different application scenarios.

[0080] In an embodiment of the present application, a theoretical value of the voltage change rate is obtained based on historical self-discharge data, including: taking the historical voltage change rate as the first theoretical value of the voltage change rate, where the historical voltage change rate includes the average voltage change rate of the battery within a historical detection time period.

[0081] As described above, the historical detection time period can be any preset period. Taking the historical monthly voltage change rate as an example, the historical monthly voltage change rate can be used as the theoretical voltage change rate value to reflect the self-discharge performance of the battery within the historical time period. In one example, the self-discharge historical data may include one historical monthly voltage change rate or multiple historical monthly voltage change rates. If the self-discharge historical data includes one historical monthly voltage change rate, the historical monthly voltage change rate can be used as the theoretical voltage change rate value. If the self-discharge historical data includes multiple historical monthly voltage change rates, the theoretical voltage change rate value can be the average of the multiple historical monthly voltage change rates.

[0082] In this way, the first voltage change rate sample value and the first voltage change rate theoretical value are obtained, and then the voltage change rate standard value in the first cycle is determined according to the minimum value between the first voltage change rate sample value and the first voltage change rate theoretical value.

[0083] The above embodiment uses the battery's self-discharge history data as a factor in determining the standard value of the voltage change rate. In this way, the inconsistent battery performance characteristics of different batches of batteries can be taken into account, making the obtained standard value of the voltage change rate more accurate, reducing the impact of fluctuations in the current sample data on the battery self-discharge detection results, and enabling a more comprehensive evaluation of the battery performance.

[0084] It is understandable that capacity decay is usually accompanied by voltage changes. The voltage change can be derived and calculated through the mapping relationship between capacity decay and voltage, or directly calculated through the voltage drop of the battery caused by capacity decay. Therefore, in order to improve the battery self-discharge detection effect, the self-discharge history data of this embodiment also includes the capacity conversion voltage difference within the historical detection time period, that is, the influence of the voltage change rate and the capacity conversion voltage difference on the battery self-discharge detection accuracy is considered at the same time.

[0085] In the embodiment of the present application, the historical voltage change rate can be directly obtained by the voltage difference per unit time, and the capacity conversion pressure difference is obtained by converting the capacity decay of the battery in the historical detection time period into voltage. For example, if the capacity of the battery decays by a certain percentage, the corresponding voltage drop value can be obtained through the voltage-capacity characteristic curve of the battery, which can reflect the voltage drop directly caused by the capacity decay. The battery can be discharged at a known constant current until the battery voltage drops to the specified discharge termination voltage, and the discharge duration is recorded. The initial capacity and current capacity of the battery are calculated based on the product of the discharge current and the discharge time, and then the capacity decay value is obtained, and then the corresponding capacity conversion pressure difference is obtained based on the voltage-capacity characteristic curve. The initial capacity and current capacity of the battery can also be obtained through a preset model, and the preset model is, for example, a functional relationship between the battery capacity and the number of cycles or time.

[0086] In an embodiment of the present application, a theoretical value of the voltage change rate is obtained based on historical data of the voltage change rate, including: obtaining a first value based on the historical voltage change rate and a preset first self-discharge adjustment coefficient; obtaining a second value based on the capacity conversion pressure difference and a preset second self-discharge adjustment coefficient; determining a second theoretical value of the voltage change rate based on the minimum value of the first value and the second value, and the second theoretical value of the voltage change rate is used to determine a standard value of the voltage change rate of the battery in the second cycle.

[0087] The first and second self-discharge adjustment coefficients are coefficients less than 1 and can be set based on the required qualification rate and historical data. For example, when the factory qualification rate requirement for the battery is high, it indicates that the battery quality needs to be strictly controlled and more stringent screening standards are required. In this case, the self-discharge adjustment coefficient will be adjusted down; conversely, the self-discharge adjustment coefficient will be adjusted up. For example, if historical data indicates that the self-discharge rate distribution of the battery is relatively concentrated, indicating that the self-discharge performance is relatively stable, the self-discharge adjustment coefficient will be adjusted up; conversely, the self-discharge adjustment coefficient will be adjusted down. The first and second self-discharge adjustment coefficients can be the same or different, and the specific sizes of the first and second self-discharge adjustment coefficients can be customized according to actual needs.

[0088] In an example, assuming that the historical voltage change rate is A and the first self-discharge adjustment coefficient is 50%, the first value is 50%A; the capacity conversion pressure difference is B, and the time difference of capacity decay is t, then the voltage change rate corresponding to the capacity conversion pressure difference is B / t, the second self-discharge adjustment coefficient is 75%, and the second value is 75%B / t. Comparing the first value and the second value, and taking the minimum value of the first value and the second value as the second theoretical value of the voltage change rate, can make the second theoretical value of the voltage change rate more accurate, and thus the standard value of the voltage change rate obtained based on the second theoretical value of the voltage change rate is also more accurate.

[0089] In this embodiment, the first cycle is shorter than the second cycle. In a short cycle, the factors affecting battery self-discharge are relatively simple, and whether the battery self-discharge is abnormal can be quickly determined by the voltage change rate. The second cycle is longer than the first cycle. In a long cycle, battery self-discharge is affected by multiple factors, and a single indicator may not be able to fully reflect the long-term performance of the battery.

[0090] Therefore, the above embodiment is for the second cycle. For the second cycle, the second theoretical value of the voltage change rate is obtained based on the historical voltage change rate and the capacity conversion pressure difference within the historical detection time period. At the same time, the influence of the voltage change rate and the capacity conversion pressure difference on the battery self-discharge detection accuracy is taken into account. The combination of the two can more comprehensively cover the influence of different factors on the long-term performance of the battery, so that the standard value of the voltage change rate in the second cycle is more accurate.

[0091] In an embodiment of the present application, the sample data of the battery in the second cycle includes the sample data of the self-discharged qualified battery in the first cycle and the sample data of the self-discharged unqualified battery in the first cycle; statistical analysis is performed based on the voltage change rate sample data of the battery to obtain the voltage change rate sample value of the battery, including: performing statistical analysis on the sample data of the qualified battery to obtain the second mean value and the second standard deviation characterizing the voltage change rate distribution information of the qualified battery, and obtaining the voltage change rate of the qualified battery according to the second mean value, the second standard deviation and the second coefficient; performing statistical analysis on the sample data of the unqualified battery to obtain the third mean value and the third standard deviation characterizing the voltage change rate distribution information of the unqualified battery, and obtaining the voltage change rate of the unqualified battery according to the third mean value, the third standard deviation and the third coefficient; the second coefficient and the third coefficient include any integer between 1 and 6, and the size of the second coefficient and the third coefficient is positively correlated with the qualified rate of the battery; and determining the second voltage change rate sample value according to the minimum value of the voltage change rate of the qualified battery and the voltage change rate of the unqualified battery.

[0092] As shown above, the second cycle lasts longer than the first cycle. The sample data for the second cycle is selected from batteries that passed self-discharge during the first cycle, allowing for continuous evaluation of the self-discharge performance of batteries that passed the first cycle during the second cycle. The sample data for the second cycle is selected from batteries that failed self-discharge during the first cycle, reflecting the characteristics of abnormal battery self-discharge. In other words, the data for qualified batteries reflects the performance range of normal batteries, while the data for unqualified batteries reveals the characteristics of abnormal batteries. Therefore, by statistically analyzing the sample data for batteries that passed self-discharge during the first cycle and the sample data for batteries that failed self-discharge during the first cycle, the accuracy of the second voltage change rate sample value can be improved.

[0093] In this embodiment, the statistical analysis of sample data of qualified batteries and the statistical analysis of sample data of unqualified batteries can both be performed using the mean-standard deviation method. In one example, sample data of the voltage change rate of N qualified battery cells in the first cycle during the second cycle can be collected and recorded as K3 sample data. The K3 sample data can be statistically analyzed using the mean-standard deviation method to obtain a second mean value Mean2 and a second standard deviation σ2. The voltage change rate of the qualified battery can be obtained based on the second mean value Mean2, the second standard deviation σ2, and the second coefficient n2, i.e., (Mean2+n2σ2). Similarly, sample data of the voltage change rate of N unqualified battery cells in the first cycle during the second cycle can be collected and recorded as K3' sample data. The K3' sample data can be statistically analyzed using the mean-standard deviation method to obtain a third mean value Mean3 and a third standard deviation σ3. The voltage change rate of the qualified battery can be obtained based on the third mean value Mean3, the third standard deviation σ3, and the third coefficient n3, i.e., (Mean3+n3σ3). The minimum of (Mean2 + n2σ2) and (Mean3 + n3σ3) is used as the second voltage rate of change sample value. n2 and n3 can range from 1 to 6 and are used to adjust the strictness of control. Larger n2 and n3 values ​​indicate higher inspection standards, stricter process control, and lower defective product rates. For example, if a 99.73% pass rate is required, n2 and n3 are typically set to 3, corresponding to a defective rate of approximately 2700 ppm (approximately 2700 defective products per million units).

[0094] By analyzing sample data from qualified and unqualified batteries and taking into account abnormal self-discharge characteristics of the batteries, the above embodiment can reduce misjudgments caused by data fluctuations or outliers, and improve the calculation accuracy of the voltage rate of change sample values ​​within the second cycle. Furthermore, by using the minimum of the voltage rate of change of the qualified battery and the voltage rate of change of the unqualified battery as the second voltage rate of change sample value, it is possible to tighten testing standards and thereby improve the quality of batteries shipped.

[0095] In one example, the step of determining the standard value of the voltage change rate of the battery within the target cycle in the above embodiment can be processed by a preset voltage change rate calculation model, the input of the preset voltage change rate calculation model includes voltage change rate sample data and self-discharge history data, and the output of the preset voltage change rate calculation model is the standard value of the voltage change rate within the target cycle.

[0096] As mentioned above, the open circuit voltage is required to calculate the voltage change rate, and the open circuit voltage of the battery will change with the temperature. Figure 2The open circuit voltage and temperature curves provided in this embodiment are shown. The horizontal axis is temperature and the vertical axis is open circuit voltage. Curves a, b, and c represent the relationship between OCV and temperature of batteries with different material systems, where M, N, and P represent different temperatures. Figure 2 As shown, at the same temperature, batteries with different material systems have different open-circuit voltages. Batteries with the same material system also have different open-circuit voltages at different temperatures. This means that the battery's open-circuit voltage is affected by both the battery material and temperature. This is due to factors such as differences in the thermodynamic properties of the material system, the influence of temperature on electrode reactions, and the temperature sensitivity of SOC. For example, batteries with different material systems (such as lithium iron phosphate and ternary lithium) have different chemical compositions and structures, and these characteristics determine their thermodynamic behavior at different temperatures. For example, at low temperatures, the OCV-SOC curve of lithium iron phosphate batteries shifts downward, meaning the OCV is lower at the same SOC. At high temperatures, the OCV-SOC curve shifts upward. Ternary lithium batteries exhibit similar trends in OCV variation with temperature, but at high temperatures, different materials exhibit different cycling stability and OCV variation.

[0097] Temperature changes can affect the kinetics and thermodynamic equilibrium of the electrode reactions within the battery. For example, a temperature increase typically accelerates the rate of the electrode reaction, reducing the battery's internal resistance and leading to an increase in OCV. However, if the reaction is endothermic or exothermic, the direction of the OCV change may differ. For example, temperature changes can affect the chemical equilibrium within the battery, thereby altering the OCV. In some material systems, high temperatures can promote certain side reactions, leading to a decrease in OCV.

[0098] Furthermore, the chemical composition and reaction state within the battery vary at different SOCs, leading to varying sensitivity to temperature changes. At low SOCs, the battery contains fewer active substances, resulting in relatively small changes in reaction kinetics and thermodynamics, and the OCV may be less responsive to temperature changes. At high SOCs, the battery contains more active substances, leading to more intense reactions and a more pronounced impact of temperature changes on OCV.

[0099] The above factors together determine the complexity of the battery OCV changing with temperature. The change of open circuit voltage OCV affects the calculation of the voltage change rate in this embodiment. Figure 3The relationship between the voltage change rate (K value) and temperature provided by this embodiment is shown. The horizontal axis in the figure is temperature, the vertical axis is K value, and curves d, e, and f respectively represent the K value and temperature change curves obtained under different charging times. Curve d represents the K value and temperature change curve obtained by charging the battery for 15 hours and then letting it rest for 30 hours, curve e represents the K value and temperature change curve obtained by charging the battery for 52 hours and then letting it rest for 30 hours, and curve f represents the K value and temperature change curve obtained by charging the battery for 100 hours and then letting it rest for 30 hours. X, Y, and Z represent different temperatures. Figure 3 As shown in FIG, as the temperature increases, the K value increases, that is, the battery self-discharge K value is affected by temperature.

[0100] Therefore, in order to reduce the impact of temperature on the accuracy of calculating the battery voltage change rate, temperature compensation is performed in the above arbitrary calculation process of the voltage change rate, so that the test results at different temperatures are comparable, thereby improving the accuracy of battery self-discharge detection.

[0101] In the embodiment of this application, Figure 4 The flow chart of the temperature compensation method provided in this embodiment is shown as follows: Figure 4 As shown, the above method further includes the following steps S201 to S203:

[0102] S201 : Determine a temperature compensation coefficient corresponding to a current test condition of the battery.

[0103] S202 : Obtain a compensated open circuit voltage according to the current open circuit voltage of the battery, the current temperature, and a temperature compensation coefficient corresponding to the current test condition.

[0104] S203 : Determine the current voltage change rate of the battery according to the rest time at the target temperature and the compensated open circuit voltages corresponding to the start time and the end time of the rest time.

[0105] Before executing step S201, this embodiment obtains the temperature compensation coefficient under different test conditions by fitting the model, that is, the temperature compensation coefficient is obtained by fitting the data of the open circuit voltage of the battery under different test conditions, and the test conditions include at least one of different temperatures and different charge states of the battery.

[0106] In this embodiment, the battery is tested by setting different temperature points and SOC conditions. For example, a series of temperature points are selected, such as -20°C, 0°C, 25°C, 45°C, and 60°C, and different SOCs are selected, such as any SOC between 10% and 100%. A standard discharge test is performed at each temperature point or at different SOCs, and the battery performance parameters, including the battery's OCV experimental data, are recorded. The obtained OCV experimental data is input into a fitting model (temperature-SOC-OCV fitting model). The fitting method of the fitting model can be based on any data fitting method such as polynomial or least squares method. At the same time, the fitting model parameters are adjusted according to the OCV test data to ensure the accuracy of the model. After the model adjustment is completed, temperature compensation coefficients at different temperatures and different SOCs are obtained. For example, a temperature compensation coefficient table can be formed. The temperature compensation coefficient is used to correct the actual OCV test data to eliminate the impact of temperature and SOC changes on OCV.

[0107] The above method can be used to obtain the OCV temperature compensation coefficient W corresponding to different temperatures and different SOC conditions. OCV voltage temperature compensation formula:

[0108] OCV 补偿 OCV 初始 (25-T) W

[0109] Where, T is the test temperature / °C, and the standard operating temperature of the battery is 25°C.

[0110] From the above, we can know that the calculation formula of K value is:

[0111] K = (OCV1 - OCV2) / (t2 - t1)

[0112] Therefore, after considering temperature compensation, the K value calculation formula is:

[0113]

[0114] OCV1 补偿 OCV2 is the open circuit voltage corresponding to time t1 after considering temperature compensation. 补偿 is the open circuit voltage at time t2 after taking temperature compensation into account.

[0115] It can be seen from this that when it is necessary to test the compensated open circuit voltage at any time, the temperature compensation coefficient corresponding to the current test conditions can be determined according to the current test conditions and the temperature compensation coefficient table, and then the current open circuit voltage (OCV) of the battery can be used to determine the temperature compensation coefficient corresponding to the current test conditions. 初始 ), current temperature And the temperature compensation coefficient W corresponding to the current test conditions, using OCV 补偿 OCV 初始 (25-T) W, the open circuit voltage after compensation According to the static time (t2 - t1) at the target temperature, and the compensated open circuit voltage corresponding to the start and end time of the static time, the compensated open circuit voltage corresponding to the start time is , the open circuit voltage after compensation corresponding to the end time , you can determine the current voltage change rate of the battery , the target temperature represents the standard operating temperature of the battery, such as 25°C.

[0116] In the above embodiment, by introducing a temperature compensation coefficient obtained by data fitting of the open circuit voltage of the battery under different test conditions during the process of calculating the voltage change rate, the influence of different test temperatures on the open circuit voltage measurement results can be eliminated. The compensated open circuit voltage can more realistically reflect the voltage change rate of the battery under different operating temperatures, thereby improving the accuracy of battery self-discharge detection.

[0117] In an embodiment of the present application, the battery self-discharge detection method further includes: obtaining an error threshold based on a standard value of the voltage change rate of the battery within a target cycle and a preset error coefficient, wherein the open circuit voltage influencing factor includes at least one of the test environment temperature, the battery polarization error, and the equipment test error; for each test condition, when the quantized value of the open circuit voltage influencing factor is less than the error threshold, performing data fitting on the open circuit voltage of the battery under the test condition to obtain a temperature compensation coefficient corresponding to the test condition.

[0118] The error coefficient refers to an indicator or limit set to quantify and control errors during battery performance testing to ensure the accuracy and reliability of measurement results. For example, the error coefficient includes %GR&R (% Gage Repeatability and Reproducibility), which represents the ratio of the repeatability and reproducibility of the measuring equipment or measurement method to the total process variation. The lower the %GR&R value, the smaller the error of the measurement system and the more reliable the measurement results. Another example of the error coefficient is the number of distinct categories or groups that the measurement system can distinguish (NDC). The higher the NDC value, the more categories the measurement system can distinguish and the more refined the measurement results.

[0119] This embodiment takes %GR&R<10% and NDC≥5 as an example, which shows the error quantization value caused by the open circuit voltage influence factor ( ) The following conditions must be met:

[0120]

[0121] That is, the error threshold is 10%. , and then in each test process, it is necessary to ( ) controlled at 10% Only within 10 seconds can the open circuit voltage be detected and the data acquired.

[0122] In the above embodiment, by quantifying the specific effects of open circuit voltage influencing factors such as ambient temperature, test error, and polarization on the battery K measurement, when the quantized value of the open circuit voltage influencing factor is less than the error threshold, data fitting is performed on the open circuit voltage of the battery under the test conditions, and then the temperature compensation coefficient corresponding to the test conditions is obtained, thereby further improving the calculation accuracy of the voltage change rate.

[0123] In an embodiment of the present application, after determining the current voltage change rate of the battery, it also includes: obtaining the standard temperature difference corresponding to the current test conditions based on the standard value of the battery's voltage change rate, the current voltage change rate of the battery, the standing time, and the temperature compensation coefficient; obtaining the actual temperature difference corresponding to the current test conditions based on the battery temperature at the first moment and the battery temperature at the second moment; generating ambient temperature control information based on the actual temperature difference being greater than or equal to the standard temperature difference, and the ambient temperature control information is used to control the test temperature of the battery so that the actual temperature difference is less than the standard temperature difference.

[0124] In this embodiment, the standard temperature difference represents the temperature variation range allowed for the battery during the static period under ideal test conditions. Specifically, the standard temperature difference can be expressed as:

[0125]

[0126] That is, the standard value of voltage change rate, That is, the current voltage change rate. If the battery temperature T1 at the first moment and the battery temperature T2 at the second moment are equal to the actual temperature difference (T2-T1) corresponding to the current test conditions, then (T2-T1)≧ If the actual temperature difference exceeds the upper limit of the static temperature difference, the ambient temperature control information is generated to adjust the test environment to ensure the accuracy and reliability of the battery test.

[0127] The above embodiment uses the standard temperature difference to regulate the actual temperature difference, forming a temperature closed-loop control. It can achieve temperature compensation of the K value while controlling the static temperature difference of the calculated K value, automatically adjusting the temperature of the test environment, ensuring the consistency of the test conditions, and effectively reducing the impact of temperature changes on battery testing.

[0128] The following is a specific example to illustrate the battery self-discharge detection method of the embodiment of the present application.

[0129] Figure 5 The flowchart of the steps of the battery self-discharge detection method in the first cycle provided by an embodiment of the present application is shown; for the first cycle, that is, a short cycle, such as one day, Figure 5 As shown, the battery self-discharge detection method includes:

[0130] S50, collecting sample data;

[0131] Collect sample data of the battery voltage change rate K1 under normal mass production. The sample size N can be between 500 and 1000 to ensure the representativeness of the data.

[0132] S51, abnormal sample processing;

[0133] Scatter point values ​​are eliminated by setting scatter point specifications, and outliers are eliminated from the screened data using the quartile method until no discrete data appears.

[0134] S52, determining the standard value of the voltage change rate in the first cycle;

[0135] Use Mean & Sigma technology to calculate the K1 value. The upper specification limit of K1 = Mean1 + n1σ1, where Mean1 is the mean, σ1 is the standard deviation, and n1 is any value from 1 to 6. The sample value of the first voltage rate of change is obtained. The historical monthly voltage change rate is used as the theoretical value of the first voltage rate of change. The standard value of the first voltage rate of change (K1 specification) is obtained based on the minimum value between the sample value of the first voltage rate of change and the theoretical value of the first voltage rate of change.

[0136] S53. Determine whether the actual voltage change rate of the battery in the first cycle is less than the first voltage change rate standard value. If so, the battery self-discharge is normal in the first cycle; otherwise, the battery self-discharge is abnormal in the first cycle.

[0137] Figure 6 The flowchart of the steps of the battery self-discharge detection method in the second cycle provided by an embodiment of the present application is shown; for the second cycle, that is, a long cycle, such as three months, Figure 6 As shown, the battery self-discharge detection method includes:

[0138] S60, calculating a second theoretical value of the voltage change rate;

[0139] Based on the historical monthly self-discharge rate A and the first self-discharge adjustment coefficient, such as 50%, the voltage change rate 50%A obtained by capacity decay conversion is obtained, and the time difference of capacity decay is t. Based on the capacity conversion pressure difference B obtained by capacity decay conversion and the second self-discharge adjustment coefficient, such as 75%, the voltage change rate 75%B / t obtained by voltage change due to battery capacity decay is obtained. The minimum value between 50%A and 75%B / t is used as the second theoretical value of the voltage change rate, which can make the second theoretical value of the voltage change rate more accurate.

[0140] S61, determining the standard value of the voltage change rate in the second cycle;

[0141] Collect sample data from batteries that pass K1 and batteries that fail K1. The sample size N can be between 500 and 1000 to ensure data representativeness. Set the scatter point specification to eliminate scattered values, and use the quartile method to eliminate outliers from the filtered data until no discrete data appears.

[0142] Similar to the above-mentioned K1 specification calculation method, the Mean & Sigma technology is used to calculate the voltage change rate M of the battery with qualified K1, and the voltage change rate N of the battery with unqualified K1, and the minimum value of M and N is used as the second sample value of the voltage change rate.

[0143] The minimum value between the second sample value of the voltage change rate and the second theoretical value of the voltage change rate obtained in S60 is used as the second voltage change rate standard value K3.

[0144] S62: Determine whether the actual voltage change rate of the battery in the second cycle is less than the second voltage change rate standard value. If so, the battery self-discharge is normal in the second cycle; otherwise, the battery self-discharge is abnormal in the second cycle.

[0145] At the same time, in the process of calculating the actual voltage change rate of the battery, temperature compensation control is performed. The temperature compensation control method is as follows: Figure 7 As shown:

[0146] S70, setting test conditions;

[0147] Set different temperature points and SOC conditions for testing: select a series of temperature points, such as -20°C, 0°C, 25°C, 45°C, 60°, and select different SOCs, such as any one from 10% to 100%.

[0148] S71. Acquire experimental data;

[0149] Perform a standard discharge test at each temperature point or at different SOCs, and record the battery's performance parameter data, including temperature, open circuit voltage (OCV), and voltage change rate.

[0150] S72, model fitting;

[0151] A temperature-SOC-performance model is established, and experimental data is input into the temperature-SOC-performance model to fit the compensation coefficient settings at different temperatures and SOCs. Specifically, the OCV (dependent variable) collected at different temperatures and SOCs (independent variables) is fitted to derive the corresponding mathematical relationship between temperature, SOC, and OCV. The model can be adjusted as data accumulates. Instead of requiring individual fitting, the model automatically captures these three parameters for different products on the test equipment, fits them, and adjusts the model parameters. Model parameters are adjusted based on validation data to ensure model accuracy. Using the fitted model, the test temperature and SOC are input to calculate the corresponding temperature compensation coefficient.

[0152] S73, calculating the true K value;

[0153] By OCV 补偿 OCV 初始 (25-T) W, the open circuit voltage at the initial and final resting moments after compensation , the real K value is obtained according to the K value calculation formula after temperature compensation.

[0154] S74, static temperature difference control.

[0155] According to the error quantification value caused by the open circuit voltage influence factor ( ) satisfies the error control condition, executes the step of calculating the actual voltage change rate, and calculates the error quantization value ( ) does not meet the error control condition, and generates ambient temperature control information to make the actual temperature difference of the battery detection environment within the standard temperature difference range.

[0156] The embodiment of the present application sets at least two cycles of different lengths to obtain standard values ​​of the voltage change rate within different cycles. Then, based on the actual voltage change rate of the battery and the standard value of the voltage change rate of the target cycle, the battery self-discharge anomaly detection is performed. In this way, for different target cycles, different standard values ​​of the voltage change rate can be selected to respectively detect the self-discharge performance of the battery within each cycle. For example, based on the actual voltage change rate of the battery within a short cycle and the standard value of the voltage change rate, it is possible to detect whether the battery is abnormal within the short cycle, thereby reflecting the initial state of the battery; based on the actual voltage change rate of the battery within a long cycle and the standard value of the voltage change rate, it is possible to detect whether the battery is abnormal within the long cycle, thereby reflecting the stability and life of the battery, making battery self-discharge detection more flexible, applicable to multiple scenarios, and more targeted and accurate.

[0157] By introducing a temperature compensation coefficient obtained by data fitting of the open circuit voltage of the battery under different test conditions, the influence of different test temperatures on the open circuit voltage measurement results can be eliminated. The compensated open circuit voltage can more realistically reflect the voltage change rate of the battery at different operating temperatures, thereby improving the accuracy of battery self-discharge detection.

[0158] Figure 8 FIG. 1 shows a schematic diagram of the structure of a battery self-discharge detection device provided in an embodiment of the present application. Figure 8 As shown, the battery self-discharge detection device includes:

[0159] The data acquisition module 801 is used to acquire the battery voltage change rate sample data and self-discharge history data based on the battery performance data;

[0160] a standard value calculation module 802 for determining a standard value of the voltage change rate of the battery within a target cycle based on the voltage change rate sample data and self-discharge history data of the battery, wherein the target cycle includes at least two cycles of different lengths; and the self-discharge history data includes historical voltage change rates;

[0161] The detection module 803 is configured to perform self-discharge abnormality detection on the battery according to the actual voltage change rate of the battery and the standard value of the voltage change rate of the target cycle.

[0162] In one example, the detection module 803 is used to obtain a cycle to be detected and determine a standard value of the voltage change rate corresponding to the cycle to be detected; the cycle to be detected includes at least one of the target cycles; based on the actual voltage change rate of the battery during the cycle to be detected being greater than the standard value of the voltage change rate corresponding to the cycle to be detected, it is determined that the battery has self-discharge abnormality.

[0163] In one example, the standard value calculation module 802 is further used to perform statistical analysis based on the voltage change rate sample data to obtain a voltage change rate sample value of the battery; obtain a voltage change rate theoretical value based on the self-discharge history data; and determine a voltage change rate standard value of the battery within a target cycle based on the minimum value between the voltage change rate sample value and the voltage change rate theoretical value.

[0164] In one example, the target cycle includes a first cycle, and the standard value calculation module 801 is further used to perform statistical analysis on the voltage change rate sample data of the battery within the first cycle to obtain a first average value and a first standard deviation that characterize the voltage change rate distribution information; based on the first average value, the first standard deviation and the first coefficient, a first voltage change rate sample value is obtained, and the first voltage change rate sample value is used to determine the voltage change rate standard value of the battery within the first cycle, and the first coefficient includes any integer between 1 and 6, and the size of the first coefficient is positively correlated with the qualified rate of the battery.

[0165] In one example, the standard value calculation module 802 is further configured to use the historical voltage change rate as a first theoretical value of the voltage change rate, where the historical voltage change rate includes an average voltage change rate of the battery within a historical detection time period.

[0166] In one example, the target cycle includes a first cycle and a second cycle, the duration of the second cycle is greater than the duration of the first cycle, and the self-discharge history data also includes a capacity conversion pressure difference within a historical detection time period, and the capacity conversion pressure difference is obtained after voltage conversion of the capacity attenuation of the battery within the historical detection time period; the standard value calculation module 802 is also used to obtain a first value based on the historical voltage change rate and a preset first self-discharge adjustment coefficient; obtain a second value based on the capacity conversion pressure difference and a preset second self-discharge adjustment coefficient; determine a second theoretical value of the voltage change rate based on the minimum value of the first value and the second value, and the second theoretical value of the voltage change rate is used to determine the standard value of the voltage change rate of the battery in the second cycle.

[0167] In one example, the sample data of the battery in the second cycle includes sample data of qualified self-discharge batteries in the first cycle and sample data of unqualified self-discharge batteries in the first cycle; the standard value calculation module 802 is further used to perform statistical analysis on the sample data of the qualified batteries to obtain a second mean value and a second standard deviation representing the voltage change rate distribution information of the qualified batteries, and obtain the voltage change rate of the qualified batteries based on the second mean value, the second standard deviation and the second coefficient; perform statistical analysis on the sample data of the unqualified batteries to obtain a third mean value and a third standard deviation representing the voltage change rate distribution information of the unqualified batteries, and obtain the voltage change rate of the unqualified batteries based on the third mean value, the third standard deviation and the third coefficient; the second coefficient and the third coefficient include any integer between 1 and 6, and the size of the first coefficient is positively correlated with the qualified rate of the battery; and determine the second voltage change rate sample value based on the minimum value of the voltage change rate of the qualified battery and the voltage change rate of the unqualified battery.

[0168] In one example, the detection module 802 is further used to determine a temperature compensation coefficient corresponding to the current test condition based on the current test condition of the battery, the temperature compensation coefficient being obtained by data fitting the open circuit voltage of the battery under different test conditions, the test conditions including at least one of different temperatures and different states of charge of the battery; obtaining the compensated open circuit voltage based on the current open circuit voltage of the battery, the current temperature, and the temperature compensation coefficient corresponding to the current test condition; determining the current voltage change rate of the battery based on the standing time at the target temperature and the compensated open circuit voltage corresponding to the start and end times of the standing time, wherein the target temperature represents the standard operating temperature of the battery.

[0169] In one example, the detection module 802 is further used to obtain an error threshold based on the standard value of the voltage change rate of the battery within the target cycle and a preset error coefficient, where the open circuit voltage influencing factor includes at least one of the test environment temperature, battery polarization error, and equipment test error; for each test condition, when the quantized value of the open circuit voltage influencing factor is less than the error threshold, data fitting is performed on the open circuit voltage of the battery under the test condition to obtain a temperature compensation coefficient corresponding to the test condition.

[0170] In one example, after determining the current voltage change rate of the battery, the detection module 802 is further used to obtain the standard temperature difference corresponding to the current test condition based on the standard value of the voltage change rate of the battery, the current voltage change rate of the battery, the standing time and the temperature compensation coefficient; obtain the actual temperature difference corresponding to the current test condition based on the battery temperature at the first moment and the battery temperature at the second moment; and generate ambient temperature control information based on the actual temperature difference being greater than or equal to the standard temperature difference. The ambient temperature control information is used to control the test temperature of the battery so that the actual temperature difference is less than the standard temperature difference.

[0171] The above description of the various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced with each other and will not be repeated herein for the sake of brevity.

[0172] The self-discharge detection device provided in the above-mentioned embodiment of the present application and the self-discharge detection method provided in the embodiment of the present application are based on the same application concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0173] Please refer to Figure 9 , which shows a schematic diagram of an electronic device provided by some embodiments of the present application. Figure 9As shown, the electronic device 20 includes: a processor 200, a memory 201, a bus 202 and a communication interface 203, and the processor 200, the communication interface 203 and the memory 201 are connected via the bus 202; the memory 201 stores a computer program that can be run on the processor 200, and when the processor 200 runs the computer program, it executes the method provided in any of the aforementioned embodiments of the present application.

[0174] Memory 201 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between the system network element and at least one other network element is achieved through at least one communication interface 203 (which may be wired or wireless), and may utilize the Internet, a wide area network, a local area network, a metropolitan area network, or the like.

[0175] The bus 202 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, and the like. The memory 201 is used to store programs, and the processor 200 executes the programs upon receiving execution instructions. The battery self-discharge detection method disclosed in any of the aforementioned embodiments of the present application may be applied to or implemented by the processor 200.

[0176] The processor 200 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor 200 or by software instructions. The above processor 200 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in conjunction with the embodiments of this application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory 201 , and the processor 200 reads the information in the memory 201 and completes the steps of the above method in combination with its hardware.

[0177] The electronic device provided in the embodiment of the present application and the battery self-discharge detection method provided in the embodiment of the present application are based on the same application concept and have the same beneficial effects as the methods adopted, operated or implemented therein.

[0178] The battery mentioned in the embodiments of this application is a battery apparatus, which may include one or more battery cell assemblies to provide voltage and capacity. A battery cell assembly may include one or more battery cells, which are connected in series, parallel, or hybrid via a busbar.

[0179] In some embodiments, a battery cell assembly is typically formed by arranging multiple battery cells. For example, the battery cell assembly may be a battery module, which is a battery module formed by arranging and securing multiple battery cells to form a single module. For example, a battery module may be formed by bundling multiple battery cells using cable ties.

[0180] In some embodiments, the battery device may be a battery pack, which includes a case and one or more battery cell assemblies, wherein the battery cell assemblies are housed in the case.

[0181] As an example, the battery cell assembly may be a battery module, and the battery cell assembly may be accommodated in the box by fixing the battery module in the box.

[0182] As an example, the battery cell assembly may also be housed in the box by directly fixing the plurality of battery cells to the box.

[0183] As an example, the housing may include a first housing and a second housing. The first housing and the second housing engage to form an enclosed space within the housing to house the battery cell assembly. Enclosed here means covered or closed, and can be either sealed or unsealed. The first housing may be a top cover or a bottom plate.

[0184] As an example, the box may include a top cover, a frame, and a bottom plate, wherein the top cover and the bottom plate are respectively connected to the frame to form a closed space inside the box to accommodate the battery cell assembly.

[0185] As an example, the box body can be used as a part of the chassis structure of the vehicle. For example, the top cover of the box body can become at least a part of the floor of the vehicle, or the frame of the box body can become at least a part of the crossbeam and longitudinal beam of the vehicle.

[0186] In some embodiments, the battery device refers to an energy storage device, which includes a box with a door on at least one side. The energy storage device includes an energy storage container, an energy storage cabinet, etc.

[0187] The technical solutions described in the embodiments of the present application are applicable to various electrical devices that use battery cells and battery devices, such as mobile phones, portable devices, laptops, electric vehicles, electric toys, electric tools, vehicles, ships and spacecraft, etc. For example, spacecraft include airplanes, rockets, space shuttles and spacecraft, etc.

[0188] The present application also provides a computer-readable storage medium corresponding to the battery self-discharge detection method provided in the above embodiment. Figure 10 , which shows a computer-readable storage medium 30, which can be an optical disc, on which a program product is stored. The program product can be an operating system, application software, game, tool software, etc. The program product includes a computer program, which usually exists in source code or compiled binary form. When the computer program is run by the processor, it will execute the battery self-discharge detection method provided by any of the aforementioned embodiments.

[0189] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0190] The computer-readable storage medium provided in the above-mentioned embodiments of the present application and the battery self-discharge detection method provided in the embodiments of the present application are based on the same application concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0191] It should be noted that:

[0192] In the above text, the terms "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0193] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a more preferred embodiment. Based on this understanding, the technical solution of this application, or the part that contributes to the existing technology, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of this application.

[0194] The embodiments of the present application are described above in conjunction with the accompanying drawings, which are only specific implementation methods of the present application. However, the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A battery self-discharge detection method, characterized in that: include: Based on the battery performance data, obtaining voltage change rate sample data and self-discharge history data of the battery; the self-discharge history data includes historical voltage change rate; Determining a standard value of the voltage change rate of the battery within a target cycle based on the voltage change rate sample data and the self-discharge history data, where the target cycle includes at least two cycles of different lengths; performing self-discharge abnormality detection on the battery according to the actual voltage change rate of the battery and the standard value of the voltage change rate of the target cycle; Wherein, based on the voltage change rate sample data and the self-discharge history data, determining the standard value of the voltage change rate of the battery within the target cycle includes: performing statistical analysis based on the voltage change rate sample data to obtain the voltage change rate sample value of the battery; obtaining the voltage change rate theoretical value according to the self-discharge history data; and determining the standard value of the voltage change rate of the battery within the target cycle according to the minimum value between the voltage change rate sample value and the voltage change rate theoretical value.

2. The method according to claim 1, characterized in that The performing self-discharge abnormality detection on the battery according to the actual voltage change rate of the battery and the standard value of the voltage change rate of the target cycle includes: Acquire a period to be detected, and determine a standard value of a voltage change rate corresponding to the period to be detected; the period to be detected includes at least one of the target periods; According to the fact that the actual voltage change rate of the battery during the period to be detected is greater than the standard value of the voltage change rate corresponding to the period to be detected, it is determined that the battery has a self-discharge abnormality.

3. The method according to claim 1, characterized in that The target cycle includes a first cycle, and the performing statistical analysis based on the voltage change rate sample data to obtain the voltage change rate sample value of the battery includes: Performing statistical analysis on the voltage change rate sample data of the battery during the first cycle to obtain a first average value and a first standard deviation representing voltage change rate distribution information; A first voltage change rate sample value is obtained based on the first average value, the first standard deviation, and the first coefficient. The first voltage change rate sample value is used to determine a standard value of the voltage change rate of the battery in the first cycle. The first coefficient includes any integer between 1 and 6. The magnitude of the first coefficient is positively correlated with the qualified rate of the battery.

4. The method according to claim 3, characterized in that Obtaining a theoretical value of the voltage change rate based on the self-discharge historical data includes: The historical voltage change rate is used as a first theoretical value of the voltage change rate, where the historical voltage change rate includes an average value of the voltage change rate of the battery within a historical detection time period.

5. The method according to claim 1, wherein The target cycle includes a first cycle and a second cycle, the duration of the second cycle is longer than the duration of the first cycle, and the self-discharge history data also includes a capacity conversion voltage difference within a historical detection time period, where the capacity conversion voltage difference is obtained by performing voltage conversion on the capacity decay of the battery within the historical detection time period; Obtaining a theoretical value of the voltage change rate based on the self-discharge historical data includes: Obtaining a first value according to the historical voltage change rate and a preset first self-discharge adjustment coefficient; Obtaining a second value according to the capacity conversion pressure difference and a preset second self-discharge adjustment coefficient; A second theoretical value of the voltage change rate is determined according to the minimum value between the first value and the second value, and the second theoretical value of the voltage change rate is used to determine a standard value of the voltage change rate of the battery in a second cycle.

6. The method according to claim 5, characterized in that The sample data of the battery in the second cycle includes sample data of batteries that pass self-discharge in the first cycle and sample data of batteries that fail self-discharge in the first cycle; and the performing of statistical analysis based on the battery voltage change rate sample data to obtain the battery voltage change rate sample value includes: Performing statistical analysis on the sample data of the qualified batteries to obtain a second mean value and a second standard deviation representing voltage change rate distribution information of the qualified batteries, and obtaining the voltage change rate of the qualified batteries based on the second mean value, the second standard deviation, and the second coefficient; performing statistical analysis on the sample data of the unqualified batteries to obtain a third mean value and a third standard deviation characterizing voltage change rate distribution information of the unqualified batteries, and obtaining the voltage change rate of the unqualified batteries based on the third mean value, the third standard deviation, and a third coefficient; wherein the second coefficient and the third coefficient include any integer between 1 and 6, and the magnitudes of the second coefficient and the third coefficient are positively correlated with the qualified rate of the batteries; A second voltage change rate sample value is determined according to a minimum value of the voltage change rate of the qualified battery and the voltage change rate of the unqualified battery.

7. The method according to any one of claims 1 to 6, characterized in that The method further comprises: determining, according to a current test condition of the battery, a temperature compensation coefficient corresponding to the current test condition, the temperature compensation coefficient being obtained by performing data fitting on the open circuit voltage of the battery under different test conditions, the test conditions including at least one of different temperatures and different states of charge of the battery; Obtaining a compensated open circuit voltage according to a current open circuit voltage of the battery, a current temperature, and a temperature compensation coefficient corresponding to the current test condition; The current voltage change rate of the battery is determined according to the rest time at the target temperature and the compensated open circuit voltages corresponding to the start time and the end time of the rest time.

8. The method according to claim 7, characterized in that The method further comprises: An error threshold is obtained based on a standard value of the voltage change rate of the battery within a target cycle and a preset error coefficient, wherein the open circuit voltage influencing factor includes at least one of a test environment temperature, a battery polarization error, and an equipment test error; For each test condition, when the quantized value of the open circuit voltage influencing factor is less than the error threshold, data fitting is performed on the open circuit voltage of the battery under the test condition to obtain a temperature compensation coefficient corresponding to the test condition.

9. The method according to claim 7, characterized in that After determining the current voltage change rate of the battery, the method further includes: Obtaining a standard temperature difference corresponding to a current test condition according to the standard value of the battery voltage change rate, the current battery voltage change rate, the rest time, and the temperature compensation coefficient; Obtaining an actual temperature difference corresponding to the current test condition based on the battery temperature at the first moment and the battery temperature at the second moment; According to the actual temperature difference being greater than or equal to the standard temperature difference, environmental temperature control information is generated, where the environmental temperature control information is used to control the test temperature of the battery so that the actual temperature difference is less than the standard temperature difference.

10. A battery self-discharge detection device, characterized in that: The device comprises: A data acquisition module is used to acquire battery voltage change rate sample data and self-discharge history data based on battery performance data; the self-discharge history data includes historical voltage change rate; a standard value calculation module, configured to determine a standard value of the voltage change rate of the battery within a target cycle based on the voltage change rate sample data and the self-discharge history data, the target cycle including at least two cycles of different lengths; perform statistical analysis based on the voltage change rate sample data to obtain a voltage change rate sample value of the battery; obtain a voltage change rate theoretical value based on the self-discharge history data; and determine a standard value of the voltage change rate of the battery within the target cycle based on a minimum value between the voltage change rate sample value and the voltage change rate theoretical value; The detection module is used to perform self-discharge abnormality detection on the battery according to the actual voltage change rate of the battery and the standard value of the voltage change rate of the target cycle.

11. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method according to any one of claims 1 to 9.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method according to any one of claims 1 to 9.

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