Abnormal battery cell identification method and device, server, and storage medium

Abstract

The application relates to the technical field of battery management, in particular to an abnormal battery cell identification method and device, a server and a storage medium, wherein the method comprises the following steps: acquiring charging data of multiple charging and discharging cycles of each battery cell in a battery pack; identifying a first charging time when each battery cell reaches a reference voltage in the charging data; calculating a charging deviation time of each battery cell relative to a reference cell according to the first charging time and a second charging time of the reference cell of the battery pack; fitting the charging deviation time of each battery cell in each charging and discharging cycle to obtain a curve of the charging deviation time changing with the number of charging and discharging cycles; and identifying an abnormal battery cell with self-discharge abnormality in each battery cell according to the fitting slope of the curve. Therefore, the problems that a complex model needs to be established and additional calculation is needed to determine the battery with self-discharge abnormality in the prior art, and the false positive rate is high when applied to real vehicle data are solved.

Description

Technical Field

[0001] This invention relates to the field of battery management technology, specifically to a method, apparatus, server, and storage medium for identifying abnormal battery cells. Background Technology

[0002] With the rapid development and widespread adoption of electric vehicles, the safety of power batteries, as the core component of electric vehicles, has become increasingly important. Accidents such as fires and even explosions caused by thermal runaway of power batteries can easily result in personal injury and property damage, and are currently a key focus and challenge in electric vehicle safety research.

[0003] One of the main causes of thermal runaway in power batteries is an internal short circuit. An internal short circuit creates a circuit within the battery and continuously consumes electricity, manifesting externally as an abnormal decrease in battery charge, i.e., abnormal self-discharge. As the severity of the internal short circuit increases, the abnormal self-discharge of the battery increases, the heat generation increases, and eventually leads to thermal runaway.

[0004] A method and apparatus for detecting battery micro-short circuits are disclosed in related technologies. Specifically, it calculates the internal short-circuit leakage current of a battery cell based on the difference in charging capacity between the battery cell and a reference cell at the end of two adjacent charging processes. Furthermore, it estimates the internal short-circuit resistance using the average voltage at the end of the two charging processes. Finally, it determines whether an internal short circuit exists by comparing the leakage current and internal short-circuit resistance with corresponding thresholds. However, this method has the following problems: 1. It only uses two charging processes for judgment, which is easily affected by voltage / current data jumps and missing data when applied to real vehicle data, potentially misclassifying normal batteries as internally short-circuited batteries; 2. The reference cell is fixed as the highest voltage cell after each charging process, requiring reference cell determination before each calculation, and the results are not comparable when the reference cell changes; 3. The calculation process is complex, requiring the calculation of multiple parameters such as reference charging time, reference charging capacity, average voltage, and internal short-circuit resistance. Another related technology discloses a method for detecting internal short circuits in lithium-ion battery cells. This method uses the relationship between OCV (Open Circuit Voltage), capacity Q, and SOC (State of Charge) obtained through pre-testing as input to construct an equivalent circuit model. The model compares the voltage, temperature, and rate of change during the charging and discharging process of the battery cell. When a threshold is exceeded, an internal short circuit fault is determined in the battery cell. However, this method has the following problems: 1. It requires extensive pre-testing of battery cells to obtain accurate battery parameters for comparison; 2. The model construction and calculation are complex, and the model parameters need repeated identification, making it difficult to adapt to complex and changing real-world vehicle operating conditions. Summary of the Invention

[0005] One objective of this invention is to provide a method for identifying abnormal battery cells, in order to solve the problem that existing technologies require the establishment of complex models and additional calculations to determine batteries with abnormal self-discharge, and that the false alarm rate is high when applied to real vehicle data; a second objective is to provide a device for identifying abnormal battery cells; a third objective is to provide a server; and a fourth objective is to provide a computer-readable storage medium.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for identifying abnormal battery cells, applied to a server, comprising the following steps: acquiring charging data of each battery cell in a battery pack over multiple charge-discharge cycles; identifying the first charging time when each battery cell reaches a reference voltage in the charging data; calculating the charging deviation time of each battery cell relative to the reference cell based on the first charging time and a second charging time of a reference cell in the battery pack; fitting the charging deviation time of each battery cell in each charge-discharge cycle to obtain a curve showing the change of charging deviation time with the number of charge-discharge cycles; and identifying abnormal battery cells with self-discharge abnormalities based on the slope of the fitted curve.

[0008] Based on the above technical means, the embodiments of this application can obtain the charging data of each battery cell in the battery pack through multiple charge and discharge cycles, and use the slope of the change in the charging deviation time within multiple cycles to determine whether the battery has abnormal self-discharge. This avoids the misjudgment caused by data jumps when only two charging processes are used. The self-discharge is determined directly by using the slope of the change in the charging deviation time. There is no need to perform test calibration, establish complex models or perform additional complex calculations in advance, which reduces the amount of calculation and complexity of determining the self-discharge abnormal battery.

[0009] Furthermore, the step of identifying abnormal battery cells with self-discharge abnormalities among the battery cells based on the fitting slope of the curve includes: determining whether the fitting slope is greater than a first slope threshold; if the fitting slope is greater than the first slope threshold, then determining that the battery cell is an abnormal battery cell with self-discharge abnormalities.

[0010] Based on the above technical means, the embodiments of this application can directly use the fitting slope and the magnitude of the first slope threshold to determine whether a battery cell is an abnormal battery cell with self-discharge abnormality, without the need for additional complex calculations, thus reducing the amount of calculation.

[0011] Furthermore, the step of identifying abnormal battery cells with self-discharge abnormalities among the battery cells based on the fitting slope of the curve includes: determining whether the fitting slope is less than a second slope threshold; if the fitting slope is less than the second slope threshold, then determining that the reference cell is an abnormal battery cell with self-discharge abnormalities.

[0012] Based on the above technical means, the embodiments of this application can directly use the magnitude of the fitting slope and the second slope threshold to determine whether a battery cell is an abnormal battery cell with self-discharge abnormality, without the need for additional complex calculations, thus reducing the amount of calculation.

[0013] Furthermore, the step of fitting the charging deviation time of each battery cell in each charge-discharge cycle to obtain the curve of the charging deviation time changing with the number of charge-discharge cycles includes: selecting a charging cycle number window for each charging cell; determining a target cycle number range for each charging cell based on the charging cycle number window; and fitting the charging deviation time of each charge-discharge cycle within the target cycle number range to obtain the curve of the charging deviation time changing with the number of charge-discharge cycles.

[0014] Based on the above technical means, the embodiments of this application can determine the target cycle number range for each charging cell according to the charging cycle number window, fit the charging deviation time of each charge-discharge cycle within the target cycle number range, and obtain a curve of the charging deviation time changing with the number of charge-discharge cycles, which can be used to determine the subsequent curve based on the fitting slope.

[0015] Furthermore, identifying the first charging moment when each battery cell in the charging data reaches the reference voltage includes: taking any battery cell in the battery pack as a reference cell; extracting the voltage change curve of the reference cell in the charging data, selecting the voltage that all battery cells can reach as the reference voltage based on the voltage change curve; and obtaining the first charging moment when each battery cell reaches the reference voltage within any voltage range.

[0016] Based on the above technical means, the embodiments of this application can select any single battery cell in the battery pack as a reference cell, avoiding additional determination before calculation, and determine the reference voltage based on the voltage change curve during the charging process. The selection of the reference voltage is not unique, and multiple reference voltages can be selected for calculation.

[0017] Furthermore, the step of selecting the reference voltage that all battery cells can reach based on the voltage change curve includes: obtaining the charging current of the reference cell in each charging voltage range; extracting all charging voltage ranges of the reference cell from the voltage change curve based on the charging current; and selecting the reference voltage that all battery cells can reach within the charging voltage range.

[0018] Based on the above technical means, the embodiments of this application can extract all charging voltage ranges of the reference cell from the voltage change curve of the reference cell in each charging voltage range according to the charging current of the reference cell, and select the voltage that can be reached by all battery cells in the charging voltage range as the reference voltage.

[0019] Further, the step of selecting the reference voltage that all battery cells can reach within the charging voltage range includes: obtaining the selection order of all charging voltage ranges; sequentially selecting the reference voltage within the charging voltage range according to the selection order, wherein, in any charging voltage range, during the first selection, the median voltage of the charging voltage range is selected; if all battery cells can reach the median voltage, the median voltage is used as the reference voltage; otherwise, the lower limit voltage of the charging voltage range and the average voltage of the median voltage are selected; if all battery cells can reach the average voltage, the average voltage is used as the reference voltage; otherwise, the reference voltage is selected in the next charging voltage range.

[0020] Based on the above technical means, the embodiments of this application can select the reference voltage according to the selection order of the charging voltage range, and fully consider the influence of polarization internal resistance on the reference voltage when the current switches between steps.

[0021] Furthermore, obtaining the first charging time when each battery cell reaches the reference voltage within any voltage range includes: identifying the charging current of the charging voltage range; and recording the charging time when the battery cell reaches the reference voltage and the charging current is the same as that of the charging voltage range.

[0022] Based on the above technical means, the embodiments of this application can record the first charging time when each battery cell reaches the reference voltage within any charging voltage range, so as to be used for subsequent calculation of charging deviation time.

[0023] Furthermore, before acquiring the charging data of each battery cell in the battery pack for multiple charge-discharge cycles, the method further includes: acquiring the charge-discharge data of the battery pack; extracting the actual number of charge-discharge cycles from the charge-discharge data; if the actual number of cycles is greater than a preset number, then acquiring the charging data of each battery cell in the battery pack for multiple charge-discharge cycles, otherwise not identifying abnormal battery cells.

[0024] Based on the above technical means, the embodiments of this application can obtain the charging data of each battery cell in the battery pack during multiple charge-discharge cycles when the number of charge-discharge cycles is greater than a preset number; otherwise, abnormal battery cells are not identified, thus avoiding misjudgment caused by data jumps when only a few charge-discharge processes are used to judge self-discharge abnormalities.

[0025] Furthermore, after identifying abnormal battery cells with self-discharge abnormalities among the battery cells based on the fitting slope of the curve, the method further includes: generating preset reminder information; and sending the preset reminder information to a preset terminal to provide a self-discharge abnormality reminder based on the preset reminder information.

[0026] Based on the above technical means, the embodiments of this application can remind the user after identifying a battery cell with abnormal self-discharge, so as to remind the user to take timely action and avoid thermal runaway of the power battery.

[0027] Furthermore, after identifying abnormal battery cells with self-discharge abnormalities among the battery cells based on the fitting slope of the curve, the method further includes: identifying the identifier of the abnormal battery cell; and sending the identifier to a preset terminal to locate the abnormal battery cell in the battery pack based on the identifier.

[0028] Based on the above technical means, the embodiments of this application can identify the abnormal battery cell after identifying the battery cell with self-discharge abnormality, so that the user can locate the abnormal battery cell in the battery pack according to the identification and replace it in time.

[0029] A device for identifying abnormal battery cells, the device being applied to a server, comprising: an acquisition module for acquiring charging data of each battery cell in a battery pack over multiple charge-discharge cycles; a calculation module for identifying a first charging time when each battery cell reaches a reference voltage in the charging data, and calculating the charging deviation time of each battery cell relative to the reference cell based on the first charging time and a second charging time of a reference cell in the battery pack; and an identification module for fitting the charging deviation time of each battery cell in each charge-discharge cycle to obtain a curve showing the change of charging deviation time with the number of charge-discharge cycles, and identifying abnormal battery cells with self-discharge abnormalities based on the slope of the fitted curve.

[0030] Furthermore, the identification module is further used to: determine whether the fitting slope is greater than a first slope threshold; if the fitting slope is greater than the first slope threshold, then determine that the battery cell is an abnormal battery cell with self-discharge abnormality.

[0031] Furthermore, the identification module is further used to: determine whether the fitting slope is less than a second slope threshold; if the fitting slope is less than the second slope threshold, then determine that the reference cell is an abnormal battery cell with self-discharge abnormality.

[0032] Furthermore, the identification module is further configured to: select a charging cycle number window for each charging cell; determine a target cycle number range for each charging cell based on the charging cycle number window; and fit the charging deviation time of each charge-discharge cycle within the target cycle number range to obtain a curve of the charging deviation time changing with the number of charge-discharge cycles.

[0033] Furthermore, the calculation module is further configured to: take any one of the battery cells in the battery pack as a reference cell; extract the voltage change curve of the reference cell from the charging data, select the voltage that all battery cells can reach as the reference voltage based on the voltage change curve; and obtain the first charging time when each battery cell reaches the reference voltage within any charging voltage range.

[0034] Furthermore, the calculation module is further configured to: obtain the charging current of the reference cell in each charging voltage range; extract all charging voltage ranges of the reference cell from the voltage change curve based on the charging current; and select the voltage that all battery cells can reach within the charging voltage range as the reference voltage.

[0035] Furthermore, the calculation module is further configured to: obtain the selection order of all charging voltage ranges; sequentially select the reference voltage within the charging voltage range according to the selection order, wherein, within any charging voltage range, during the first selection, the median voltage of the charging voltage range is selected; if all battery cells can reach the median voltage, the median voltage is used as the reference voltage; otherwise, the lower limit voltage of the charging voltage range and the average voltage of the median voltage are selected; if all battery cells can reach the average voltage, the average voltage is used as the reference voltage; otherwise, the reference voltage is selected in the next charging voltage range.

[0036] Furthermore, the calculation module is further used to: identify the charging current within the charging voltage range; and record the charging time when a single battery cell reaches the reference voltage and has the same charging current as the charging voltage range.

[0037] Furthermore, the abnormal battery cell identification device also includes: an extraction module, used to acquire the charge and discharge data of the battery pack before acquiring the charging data of each battery cell in the battery pack for multiple charge and discharge cycles; extract the actual number of charge and discharge cycles from the charge and discharge data, and then acquire the charging data of each battery cell in the battery pack for multiple charge and discharge cycles; otherwise, abnormal battery cell identification is not performed.

[0038] Furthermore, the abnormal battery cell identification device also includes: an alert module, used to generate preset alert information after identifying abnormal battery cells with self-discharge abnormalities among the battery cells according to the fitting slope of the curve; and to send the preset alert information to a preset terminal to provide a self-discharge abnormality alert based on the preset alert information.

[0039] Furthermore, the abnormal battery cell identification device further includes: a sending module, used to identify the identifier of the abnormal battery cell after identifying the abnormal battery cell with self-discharge abnormality among the battery cells according to the fitting slope of the curve; and send the identifier to a preset terminal to locate the abnormal battery cell in the battery pack according to the identifier.

[0040] A server is characterized by comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for identifying abnormal battery cells as described in the above embodiments.

[0041] A computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the method for identifying abnormal battery cells as described in the above embodiments.

[0042] The beneficial effects of this invention are:

[0043] (1) The embodiments of this application can obtain the charging data of each battery cell in the battery pack through multiple charge and discharge cycles, and use the slope of the change of charging deviation time in multiple cycles to determine whether the battery has abnormal self-discharge. This avoids the misjudgment caused by data jump when only two charging processes are used. The self-discharge is determined directly by using the slope of the change of charging deviation time. There is no need to perform test calibration, establish a complex model or perform additional complex calculations in advance, which reduces the amount of calculation and complexity of determining the self-discharge abnormal battery.

[0044] (2) The embodiments of this application can directly use the fitting slope and the first slope threshold to determine whether a battery cell is an abnormal battery cell with self-discharge abnormality, without the need for additional complex calculations, thus reducing the amount of calculation.

[0045] (3) The embodiments of this application can directly use the fitting slope and the magnitude of the two slope thresholds to determine whether a battery cell is an abnormal battery cell with self-discharge abnormality, without the need for additional complex calculations, thus reducing the amount of calculation.

[0046] (4) In this embodiment of the application, the target cycle number range of each charging cell can be determined according to the charging cycle number window, and the charging deviation time of each charge and discharge cycle within the target cycle number range can be fitted to obtain the curve of the charging deviation time changing with the number of charge and discharge cycles, which can be used to determine the subsequent curve based on the fitting slope.

[0047] (5) In this embodiment of the application, any single battery cell in the battery pack can be selected as the reference cell, avoiding additional determination before calculation. The reference voltage is determined according to the voltage change curve during the charging process. The selection of the reference voltage is not unique, and multiple reference voltages can be selected for calculation.

[0048] (6) In this embodiment, the reference voltage range can be extracted from the voltage change curve of the reference cell in each charging voltage range based on the charging current of the reference cell, and the voltage that can be reached by all battery cells in the charging voltage range can be selected as the reference voltage.

[0049] (7) The embodiments of this application can select the reference voltage according to the selection order of the charging voltage range, and fully consider the influence of the polarization internal resistance on the reference voltage when the current switches between steps.

[0050] (8) The embodiments of this application can record the first charging time when each battery cell reaches the reference voltage in any voltage range, so as to be used for subsequent calculation of charging deviation time.

[0051] (9) In this embodiment of the application, when the number of charge-discharge cycles is greater than a preset number, the charging data of each battery cell in the battery pack is obtained after multiple charge-discharge cycles. Otherwise, abnormal battery cells are not identified, thus avoiding misjudgment caused by data jumps when only a few charge-discharge processes are used to judge self-discharge abnormalities.

[0052] (10) In this embodiment of the application, after identifying a battery cell with abnormal self-discharge, the user can be reminded to take timely action to avoid thermal runaway of the power battery.

[0053] (11) In this embodiment of the application, after identifying a battery cell with self-discharge abnormality, the abnormal battery cell can be identified so that the user can locate the abnormal battery cell in the battery pack according to the identification and replace it in time.

[0054] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0055] Figure 1 A flowchart illustrating the method for identifying abnormal battery cells provided in an embodiment of the present invention;

[0056] Figure 2 A graph showing the change in charging deviation time with the number of cycles provided in an embodiment of the present invention;

[0057] Figure 3 This is a scatter plot of the slope value of the charging deviation time change provided in an embodiment of the present invention;

[0058] Figure 4 A flowchart illustrating a method for identifying abnormal battery cells according to an embodiment of the present invention;

[0059] Figure 5 A schematic diagram of an abnormal battery cell identification device provided in an embodiment of the present invention;

[0060] Figure 6 This is a schematic diagram of the server structure provided in an embodiment of the present invention. Detailed Implementation

[0061] The embodiments of the present invention will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention and not for limiting the scope of protection of the present invention.

[0062] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0063] Specifically, Figure 1 This is a flowchart illustrating a method for identifying abnormal battery cells provided in an embodiment of this application.

[0064] like Figure 1 As shown, the method for identifying this abnormal battery cell includes the following steps:

[0065] In step S101, charging data of each individual battery cell in the battery pack for multiple charge-discharge cycles is obtained.

[0066] This application embodiment can extract the charging data of each battery cell in the battery pack for each charge-discharge cycle based on the long-term operation data of the actual vehicle. The actual vehicle operation data refers to the voltage curve of each battery cell during the vehicle charging and driving discharge process stored in the cloud. The battery pack in this application embodiment takes a ternary lithium battery as an example.

[0067] In this embodiment of the application, before obtaining the charging data of each battery cell in the battery pack for multiple charge-discharge cycles, the method further includes: obtaining the charge-discharge data of the battery pack; extracting the actual number of charge-discharge cycles from the charge-discharge data; if the actual number of cycles is greater than a preset number, then obtaining the charging data of each battery cell in the battery pack for multiple charge-discharge cycles, otherwise not identifying abnormal battery cells.

[0068] One charge-discharge cycle is defined as one complete charge and discharge cycle of a single battery cell. The preset number of cycles can be set according to specific circumstances and is not specifically limited; for example, it can be set to 6 or 7 cycles.

[0069] It is understood that the embodiments of this application can extract the actual number of times in the charge and discharge data. When the number of charge and discharge cycles is greater than the preset number, the charging data of each battery cell in the battery pack is obtained from multiple charge and discharge cycles. Otherwise, abnormal battery cells are not identified, thus avoiding misjudgment caused by data jumps when only a few charge and discharge processes are used to judge self-discharge abnormalities.

[0070] For example, taking a preset number of times N as 7 times, when the number of charge-discharge cycles is less than N, no self-discharge abnormality judgment is performed. In each charge-discharge cycle, only the charging process data is extracted for the judgment of self-discharge abnormal battery.

[0071] In step S102, the first charging time when each battery cell reaches the reference voltage in the charging data is identified, and the charging deviation time of each battery cell relative to the reference cell is calculated based on the first charging time and the second charging time of the reference cell of the battery pack.

[0072] It is understood that, according to the embodiments of this application, the charging deviation time of each battery cell relative to the reference cell can be calculated based on the first charging time when each battery cell reaches the reference voltage and the second charging time of the reference cell of the battery pack, so as to identify abnormal battery cells with self-discharge abnormalities by using the charging deviation time.

[0073] The method for calculating the charging deviation time of the reference cell can be as follows:

[0074]

[0075] in, The first charging moment when the reference cell reaches the reference voltage in the k-th charging cycle; The second charging moment when all other battery cells reach the reference voltage in the k-th charging cycle, i = 1, 2, ..., n, for a total of n battery cells; This represents the relative charging deviation time of each of the remaining battery cells in the k-th charging cycle. A positive relative charging deviation time indicates that the battery cell reaches the reference voltage before the reference cell, resulting in a higher battery capacity; a negative relative charging deviation time indicates that the battery cell reaches the reference voltage after the reference cell, resulting in a lower battery capacity.

[0076] In this embodiment of the application, identifying the first charging moment when each battery cell in the charging data reaches the reference voltage includes: taking any battery cell in the battery pack as a reference cell; extracting the voltage change curve of the reference cell in the charging data, and selecting the voltage that all battery cells can reach as the reference voltage based on the voltage change curve; and obtaining the first charging moment when each battery cell reaches the reference voltage within any charging voltage range.

[0077] The reference cell is any cell randomly selected from the individual cells in the battery pack, and the reference voltage is the voltage that each individual cell can reach under the same charging step current during the actual vehicle charging process.

[0078] It is understood that, in the embodiments of this application, each battery cell of the battery pack can be used as a reference cell, the voltage change curve of the reference cell can be extracted from the charging data, the reference voltage can be determined based on the voltage change curve during the charging process, and the first charging moment when each battery cell reaches the reference voltage within any charging voltage range can be obtained.

[0079] In this embodiment of the application, selecting a reference voltage that can be reached by all battery cells based on the voltage change curve includes: obtaining the charging current of the reference cell in each charging voltage range; extracting all charging voltage ranges of the reference cell from the voltage change curve based on the charging current; and selecting a reference voltage that can be reached by all battery cells within the charging voltage range.

[0080] It is understood that, in the embodiments of this application, all charging voltage ranges of the reference cell are extracted from the voltage change curve of the reference cell at each charging voltage, and the voltage that all batteries can reach within the charging voltage range is selected as the reference voltage.

[0081] Due to the stepped charging strategy used in actual vehicle charging, at different voltage ranges [V x V y Different charging currents I were used inside. x The reference voltage should be within the voltage range [V]. x V y The reference voltage is selected within a certain range, ensuring that as many reference cells as possible reach the reference voltage during the charging process. Furthermore, the selection of the reference voltage is not unique, and multiple reference voltages can be selected for calculation.

[0082] In this embodiment of the application, selecting a reference voltage that all battery cells can reach within a charging voltage range includes: obtaining the selection order of all charging voltage ranges; sequentially selecting reference voltages within the charging voltage ranges according to the selection order, wherein, within any charging voltage range, during the first selection, the median voltage of the charging voltage range is selected; if all battery cells can reach the median voltage, the median voltage is used as the reference voltage; otherwise, the average voltage of the lower limit voltage and the median voltage of the charging voltage range is selected; if all battery cells can reach the average voltage, the average voltage is used as the reference voltage; otherwise, a reference voltage is selected in the next charging voltage range.

[0083] It is understood that the reference voltage in this application embodiment can be selected according to the selection order of the charging voltage range. When selecting the reference voltage for the first time, the median voltage of the charging voltage range is selected. If all battery cells can reach the median voltage, the median voltage is used as the reference voltage. Otherwise, the average voltage of the lower limit voltage and the median voltage of the charging voltage range is selected. If all battery cells can reach the average voltage, the average voltage is used as the reference voltage. Otherwise, the reference voltage is selected in the next charging voltage range.

[0084] Specifically, since the actual vehicle adopts a tiered charging strategy, the reference voltage should be selected based on the different charging stages and charging currents during the charging process. The specific method for selecting the reference voltage is as follows:

[0085] Taking a three-stage charging process as an example, the battery voltage segments are [V1, V2), [V2, V3), and [V3, V4), with corresponding currents I1, I2, and I3 for each segment. When a battery cell experiences self-discharge abnormalities, the charging time deviation between individual cells increases as the battery voltage rises during charging. To facilitate the identification of self-discharge anomalies within the charging steps under the same current, a reference voltage is first selected within the highest voltage range [V3, V4). Voltage drops occur during current switching between steps. To avoid the influence of polarization resistance during current changes, the reference voltage must be selected within the range of (V3, V4) and ensure that all battery cells reach the reference voltage. Specifically, in the first charging cycle within a long-term period, (V3+V4) / 2 is used as the reference voltage to determine if all cells within that charging step reach the reference voltage. If so, it is determined whether there are more than N charging cycles within the long-term period that satisfy the condition that all cells reach the reference voltage. If so, this is selected as the reference voltage for calculation. Otherwise, a new reference voltage of (V3+(V3+V4) / 2) / 2 is selected for further evaluation. If the above conditions are met, this is used as the reference voltage. If not, the same evaluation and selection process is repeated within the second voltage range [V2, V3) until a reference voltage is selected.

[0086] Furthermore, obtaining the first charging moment when each battery cell reaches the reference voltage within any voltage range includes: identifying the charging current of the charging voltage range; and recording the charging moment when the battery cell reaches the reference voltage and has the same charging current as the charging voltage range.

[0087] It is understood that in the embodiments of this application, any battery cell can be selected as a reference cell, the voltage change curve of the reference cell can be extracted from the charging data, the reference voltage can be determined according to the voltage change curve, and the charging time when each battery cell reaches the reference voltage and the charging current in the voltage range is the same during each charging process can be recorded as the first charging time.

[0088] In step S103, the charging deviation time of each battery cell in each charge-discharge cycle is fitted to obtain a curve showing the change of charging deviation time with the number of charge-discharge cycles. Based on the slope of the fitted curve, abnormal battery cells with self-discharge abnormalities are identified.

[0089] It is understood that, according to the calculation results of each charging cycle, the curve of the relative charging deviation time changing with the number of charge and discharge cycles can be obtained. The number of cycles is selected as the window, the slope of the relative charging deviation time change is fitted, and the self-discharge abnormality of each battery cell is determined based on the fitted slope value of the relative charging deviation time. The self-discharge is determined directly by using the slope of the relative charging deviation time change over a long period of time. There is no need to perform test calibration, establish complex models, or perform additional complex calculations in advance, which reduces the amount of calculation and complexity of determining the self-discharge abnormality battery.

[0090] In this embodiment of the application, fitting the charging deviation time of each battery cell in each charge-discharge cycle to obtain a curve of the charging deviation time changing with the number of charge-discharge cycles includes: selecting a charging cycle number window for each charging cell; determining a target cycle number range for each charging cell based on the charging cycle number window; and fitting the charging deviation time of each charge-discharge cycle within the target cycle number range to obtain a curve of the charging deviation time changing with the number of charge-discharge cycles.

[0091] The specific fitting process for the slope of the charging deviation time change is as follows: Select the charging cycle number window W, and on the cycle number interval [kW, k], use the form y = mx + b to fit the relative charging deviation time, and obtain the slope m of the relative charging deviation time changing with the cycle number.

[0092] It should be noted that, as Figure 2 As shown, the curve of relative charging deviation time of a self-discharge abnormal battery cell as a function of cycle number is significantly different from that of a normal cell.

[0093] In this embodiment of the application, identifying abnormal battery cells with self-discharge abnormalities among each battery cell based on the fitting slope of the curve includes: determining whether the fitting slope is greater than a first slope threshold; if the fitting slope is greater than the first slope threshold, then determining that the battery cell is an abnormal battery cell with self-discharge abnormalities.

[0094] The first slope threshold can be set as a positive threshold K+.

[0095] It is understood that, in the embodiments of this application, when the fitted slope value of a battery cell is positive and greater than a first slope threshold, the battery cell can be determined to be a cell with abnormal self-discharge, such as... Figure 3 As shown.

[0096] In this embodiment of the application, identifying abnormal battery cells with self-discharge abnormalities among each battery cell based on the fitting slope of the curve includes: determining whether the fitting slope is less than a second slope threshold; if the fitting slope is less than the second slope threshold, then determining the reference cell as an abnormal battery cell with self-discharge abnormalities.

[0097] The second slope threshold can be set as a negative threshold K-.

[0098] It is understood that, in the embodiments of this application, when the fitting slope value of a battery cell is negative and less than the second slope threshold, the battery cell can be determined to be a self-discharge abnormal cell.

[0099] In this embodiment of the application, after identifying abnormal battery cells with self-discharge abnormalities in each battery cell based on the curve fitting slope, the method further includes: generating preset reminder information; sending the preset reminder information to a preset terminal to provide a self-discharge abnormality reminder based on the preset reminder information.

[0100] The preset reminder message can be set to indicate that a battery cell has an abnormal self-discharge, alerting the user to the risk of thermal runaway in the power battery. The preset terminal can be the vehicle's central control display screen.

[0101] It is understood that, in this application embodiment, after identifying a battery cell with abnormal self-discharge, the user can be alerted to take timely action to avoid thermal runaway of the power battery.

[0102] In this embodiment of the application, after identifying abnormal battery cells with self-discharge abnormalities in each battery cell based on the fitting slope of the curve, the method further includes: identifying the identifier of the abnormal battery cell; sending the identifier to a preset terminal to locate the abnormal battery cell in the battery pack based on the identifier.

[0103] It is understood that, in the embodiments of this application, after identifying a battery cell with abnormal self-discharge in the battery pack, the abnormal battery cell can be identified, so that the user can locate the abnormal battery cell in the battery pack according to the identification and replace it in a timely manner.

[0104] The following specific embodiment illustrates the method for identifying abnormal battery cells according to this application. Figure 4 As shown, it includes the following steps:

[0105] Step 1: Based on the long-term operating data of the actual vehicle, extract the charging process in each charge-discharge cycle.

[0106] The actual vehicle operation data refers to the voltage curves of each battery cell during the vehicle's charging and discharging processes, stored in the cloud. One charge and discharge cycle for each battery cell in the operation data is considered a single charge-discharge cycle. Long-term cycles are generally considered to have ≥N charge-discharge cycle counts; the range used here is, but not limited to, N=7. When the number of charge-discharge cycles is less than N, no self-discharge anomaly detection is performed. Within each charge-discharge cycle, only the charging process data is extracted for identifying batteries with self-discharge anomalies.

[0107] Step 2: Select a single battery cell as a reference cell and determine the reference voltage based on the voltage change curve during charging.

[0108] The reference cell can be any battery cell during the charging and discharging process. Due to the stepped charging strategy used in actual vehicle charging, different voltage ranges [V] are observed. x V y Different charging currents I were used inside. x The reference voltage should be within the voltage range [V]. x V y The reference voltage is selected within a certain range to ensure that as many reference cells as possible reach the reference voltage during the charging process. Furthermore, the selection of the reference voltage is not unique, and multiple reference voltages can be selected for calculation.

[0109] Step 3: During each charging process, record the charging time when each battery cell reaches the reference voltage.

[0110] For real-vehicle data using stepped current charging, only the charging moments when each battery cell reaches the reference voltage and has the same charging current as the voltage range it is in are recorded.

[0111] Step 4: Calculate the charging deviation time of each battery cell relative to the reference cell based on the charging time of each individual battery cell.

[0112] The calculation process for the charging deviation time of the reference cell is as follows:

[0113]

[0114] In the formula, The first charging moment when the reference cell reaches the reference voltage in the k-th charging cycle; The second charging moment when all other battery cells reach the reference voltage in the k-th charging cycle, i = 1, 2, ..., n, for a total of n battery cells; This represents the relative charging deviation time of each of the remaining battery cells in the k-th charging cycle. A positive relative charging deviation time indicates that the battery cell reaches the reference voltage before the reference cell, resulting in a higher battery capacity; a negative relative charging deviation time indicates that the battery cell reaches the reference voltage after the reference cell, resulting in a lower battery capacity.

[0115] Step 5: Based on the calculation results of each charging cycle, obtain the curve of the relative charging deviation time changing with the number of charge and discharge cycles, select the number of cycles window, and fit the slope of the relative charging deviation time change.

[0116] like Figure 2 As shown, the curve of relative charging deviation time as a function of cycle number for battery cells with abnormal self-discharge is significantly different from that of normal cells. The specific fitting process for the slope of the relative charging deviation time is as follows: select the charging cycle number window W; within the cycle number interval [kW, k], use a form of y = mx + b to fit the relative charging deviation time, and obtain the slope m of the relative charging deviation time as a function of cycle number.

[0117] Step 6: Determine whether there is any self-discharge abnormality in each battery cell based on the slope value of the relative charging deviation time fitting.

[0118] The method for determining whether self-discharge is abnormal based on the relative charging deviation time fitting slope value is as follows: if the fitting slope value of the battery cell is positive and greater than the preset positive threshold K+, then the battery cell is determined to be a self-discharge abnormal cell. Figure 3 As shown in the figure; if the fitting slope value of the battery cell is negative and less than the preset negative threshold K-, then the reference cell is determined to be a self-discharge abnormal cell.

[0119] According to the abnormal battery cell identification method proposed in the embodiments of this application, the charging data of each battery cell in the battery pack through multiple charge-discharge cycles can be obtained. The slope of the change in charging deviation time within multiple cycles can be used to determine whether the battery has abnormal self-discharge. This avoids the misjudgment caused by data jumps when only two charging processes are used. The self-discharge is determined directly by using the slope of the change in charging deviation time. There is no need to perform test calibration, establish complex models or perform additional complex calculations in advance. This reduces the amount of calculation and complexity of determining abnormal self-discharge batteries. Furthermore, the reference cell can be arbitrarily selected, avoiding additional judgment before calculation.

[0120] Next, with reference to the accompanying drawings, an identification device for abnormal battery cells according to an embodiment of this application is described.

[0121] Figure 5 This is a block diagram of an abnormal battery cell identification device according to an embodiment of this application.

[0122] like Figure 5 As shown, the identification device 10 for the abnormal battery cell includes: an acquisition module 100, a calculation module 200, and an identification module 300.

[0123] The acquisition module 100 is used to acquire charging data of each battery cell in the battery pack during multiple charge-discharge cycles; the calculation module 200 is used to identify the first charging time when each battery cell reaches the reference voltage in the charging data, and calculate the charging deviation time of each battery cell relative to the reference cell based on the first charging time and the second charging time of the reference cell in the battery pack; the identification module 300 is used to fit the charging deviation time of each battery cell in each charge-discharge cycle to obtain a curve of the charging deviation time changing with the number of charge-discharge cycles, and identify abnormal battery cells with self-discharge abnormalities based on the slope of the fitted curve.

[0124] In this embodiment of the application, the identification module 300 is further used to: determine whether the fitting slope is greater than the first slope threshold; if the fitting slope is greater than the first slope threshold, then determine that the battery cell is an abnormal battery cell with self-discharge abnormality.

[0125] In this embodiment of the application, the identification module 300 is further used to: determine whether the fitting slope is less than the second slope threshold; if the fitting slope is less than the second slope threshold, then determine that the reference cell is an abnormal battery cell with self-discharge abnormality.

[0126] In this embodiment, the identification module 300 is further configured to: select a charging cycle number window for each charging cell; determine a target cycle number range for each charging cell based on the charging cycle number window; and fit the charging deviation time of each charge-discharge cycle within the target cycle number range to obtain a curve of the charging deviation time changing with the number of charge-discharge cycles.

[0127] In this embodiment of the application, the calculation module 200 is further configured to: take any one of the battery cells in the battery pack as a reference cell; extract the voltage change curve of the reference cell from the charging data, select the voltage that all battery cells can reach as the reference voltage according to the voltage change curve; and obtain the first charging time when each battery cell reaches the reference voltage within any charging voltage range.

[0128] In this embodiment, the calculation module 200 is further configured to: obtain the charging current of the reference cell in each charging voltage range; extract all charging voltage ranges of the reference cell from the voltage change curve based on the charging current; and select the voltage that all battery cells can reach within the charging voltage range as the reference voltage.

[0129] In this embodiment of the application, the calculation module 200 is further configured to: obtain the selection order of all charging voltage ranges; select reference voltages sequentially within the charging voltage ranges according to the selection order, wherein, within any charging voltage range, during the first selection, the median voltage of the charging voltage range is selected; if all battery cells can reach the median voltage, the median voltage is used as the reference voltage; otherwise, the average voltage of the lower limit voltage and the median voltage of the charging voltage range is selected; if all battery cells can reach the average voltage, the average voltage is used as the reference voltage; otherwise, a reference voltage is selected in the next charging voltage range.

[0130] In this embodiment, the calculation module 200 is further configured to: identify the charging current within the charging voltage range; and record the charging time when a single battery cell reaches a reference voltage and has the same charging current as the charging voltage range.

[0131] In this embodiment of the application, the apparatus 10 further includes an extraction module.

[0132] The extraction module is used to acquire the charge and discharge data of the battery pack before acquiring the charging data of each individual battery cell in the battery pack through multiple charge and discharge cycles; extract the actual number of charge and discharge cycles from the charge and discharge data; if the actual number of cycles is greater than the preset number, then acquire the charging data of each individual battery cell in the battery pack through multiple charge and discharge cycles, otherwise, do not identify abnormal individual battery cells.

[0133] In this embodiment of the application, the device 10 further includes a reminder module.

[0134] The reminder module is used to generate a preset reminder message after identifying abnormal battery cells with self-discharge abnormalities in each battery cell based on the curve fitting slope; and to send the preset reminder message to a preset terminal to provide a self-discharge abnormality reminder based on the preset reminder message.

[0135] In this embodiment of the application, the apparatus 10 further includes a sending module.

[0136] The sending module is used to identify abnormal battery cells with self-discharge abnormalities in each battery cell after identifying them based on the curve fitting slope; and to send the identifier to a preset terminal to locate the abnormal battery cell in the battery pack based on the identifier.

[0137] It should be noted that the explanation of the aforementioned method for identifying abnormal battery cells also applies to the device for identifying abnormal battery cells in this embodiment, and will not be repeated here.

[0138] The abnormal battery cell identification device proposed in the embodiments of this application can determine whether the battery has abnormal self-discharge by acquiring the charging data of each battery cell in the battery pack through multiple charge-discharge cycles and using the slope of the change in the charging deviation time within multiple cycles. This avoids the misjudgment caused by data jumps when only two charging processes are used. The self-discharge is determined directly by using the slope of the change in the charging deviation time. There is no need to perform pre-test calibration, establish complex models, or perform additional complex calculations. This reduces the amount of calculation and complexity of determining abnormal self-discharge batteries. Furthermore, the reference cell can be arbitrarily selected, avoiding additional judgments before calculation.

[0139] Figure 6 A schematic diagram of the structure of a server provided in an embodiment of this application. The server may include:

[0140] The memory 601, the processor 602, and the computer program stored on the memory 601 and capable of running on the processor 602.

[0141] When the processor 602 executes the program, it implements the method for identifying abnormal battery cells provided in the above embodiments.

[0142] Furthermore, the server also includes:

[0143] Communication interface 603 is used for communication between memory 601 and processor 602.

[0144] The memory 601 is used to store computer programs that can run on the processor 602.

[0145] The memory 601 may include high-speed RAM (Random Access Memory) memory, and may also include non-volatile memory, such as at least one disk storage.

[0146] If the memory 601, processor 602, and communication interface 603 are implemented independently, then the communication interface 603, memory 601, and processor 602 can be interconnected via a bus to complete communication between them. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0147] Optionally, in a specific implementation, if the memory 601, processor 602, and communication interface 603 are integrated on a single chip, then the memory 601, processor 602, and communication interface 603 can communicate with each other through an internal interface.

[0148] The processor 602 may be a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of this application.

[0149] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for identifying abnormal battery cells.

[0150] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0151] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0152] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0153] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (FPGAs), field-programmable gate arrays (FPGAs), etc.

[0154] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0155] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for identifying abnormal battery cells, characterized in that, The method is applied to a server, and the method includes the following steps: Acquire charging data for each individual battery cell in the battery pack after multiple charge-discharge cycles; Identify the first charging time when each battery cell reaches the reference voltage in the charging data, and calculate the charging deviation time of each battery cell relative to the reference cell based on the first charging time and the second charging time of the reference cell of the battery pack; By fitting the charging deviation time of each battery cell in each charge-discharge cycle, a curve showing the change of charging deviation time with the number of charge-discharge cycles is obtained. Based on the slope of the fitted curve, abnormal battery cells with self-discharge abnormalities are identified.

2. The method for identifying abnormal battery cells according to claim 1, characterized in that, The step of identifying abnormal battery cells with self-discharge abnormalities based on the slope of the fitted curve includes: Determine whether the fitted slope is greater than a first slope threshold; If the fitting slope is greater than the first slope threshold, then the battery cell is determined to be an abnormal battery cell with self-discharge abnormality.

3. The method for identifying abnormal battery cells according to claim 1 or 2, characterized in that, The step of identifying abnormal battery cells with self-discharge abnormalities based on the slope of the fitted curve includes: Determine whether the fitted slope is less than the second slope threshold; If the fitting slope is less than the second slope threshold, then the reference cell is determined to be an abnormal battery cell with self-discharge abnormality.

4. The method for identifying abnormal battery cells according to claim 1, characterized in that, The process of fitting the charging deviation time of each individual battery cell in each charge-discharge cycle to obtain a curve of charging deviation time changing with the number of charge-discharge cycles includes: Select the charging cycle count window for each battery cell; The target cycle number range for each battery cell is determined based on the charging cycle number window. By fitting the charging deviation time of each charge-discharge cycle within the target cycle range, a curve of the charging deviation time changing with the number of charge-discharge cycles is obtained.

5. The method for identifying abnormal battery cells according to claim 1, characterized in that, The identification of the first charging moment when each battery cell in the charging data reaches the reference voltage includes: Take any one of the battery cells in the battery pack as a reference cell; Extract the voltage change curve of the reference cell from the charging data, and select the voltage that all battery cells can reach as the reference voltage based on the voltage change curve; Obtain the first charging moment when each battery cell reaches the reference voltage within any charging voltage range.

6. The method for identifying abnormal battery cells according to claim 5, characterized in that, The step of selecting the reference voltage, which can be achieved by all battery cells, based on the voltage change curve includes: Obtain the charging current of the reference cell in each charging voltage range; Extract all charging voltage ranges of the reference cell from the voltage change curve based on the charging current; The reference voltage is selected as the voltage that all individual battery cells can reach within the charging voltage range.

7. The method for identifying abnormal battery cells according to claim 6, characterized in that, The step of selecting the reference voltage as the voltage that all individual battery cells can reach within the charging voltage range includes: Obtain the selection order of all charging voltage ranges; The reference voltage is selected sequentially within the charging voltage range according to the selection order. Specifically, in any charging voltage range, during the first selection, the median voltage of the charging voltage range is selected. If all battery cells can reach the median voltage, the median voltage is used as the reference voltage; otherwise, the lower limit voltage of the charging voltage range and the average voltage of the median voltage are selected. If all battery cells can reach the average voltage, the average voltage is used as the reference voltage; otherwise, the reference voltage is selected in the next charging voltage range.

8. The method for identifying abnormal battery cells according to claim 5, characterized in that, The step of obtaining the first charging moment when each battery cell reaches the reference voltage within any charging voltage range includes: Identify the charging current within the charging voltage range; Record the charging time when the battery cell reaches the reference voltage and the charging current is the same as that in the charging voltage range.

9. The method for identifying abnormal battery cells according to claim 1, characterized in that, Before acquiring charging data from multiple charge-discharge cycles of each individual cell in the battery pack, the following steps are also included: Obtain battery pack charge and discharge data; Extract the actual number of charge-discharge cycles from the charge-discharge data; If the actual number of times is greater than the preset number of times, the charging data of each battery cell in the battery pack for multiple charge-discharge cycles will be obtained; otherwise, abnormal battery cell identification will not be performed.

10. The method for identifying abnormal battery cells according to claim 1, characterized in that, After identifying abnormal battery cells with self-discharge anomalies based on the slope of the curve, the method further includes: Generate preset reminder messages; The preset reminder information is sent to a preset terminal to provide an alert for abnormal self-discharge based on the preset reminder information.

11. The method for identifying abnormal battery cells according to claim 1, characterized in that, After identifying abnormal battery cells with self-discharge anomalies based on the slope of the curve, the method further includes: Identify the identifier of the abnormal battery cell; The identifier is sent to a preset terminal to locate the abnormal battery cell in the battery pack based on the identifier.

12. A device for identifying abnormal battery cells, characterized in that, The device is used in a server, wherein the device includes: The acquisition module is used to acquire charging data of each battery cell in the battery pack during multiple charge-discharge cycles. The calculation module is used to identify the first charging time when each battery cell reaches the reference voltage in the charging data, and to calculate the charging deviation time of each battery cell relative to the reference cell based on the first charging time and the second charging time of the reference cell of the battery pack. The identification module is used to fit the charging deviation time of each battery cell in each charge-discharge cycle to obtain a curve of the charging deviation time changing with the number of charge-discharge cycles, and to identify abnormal battery cells with self-discharge abnormalities based on the slope of the fitted curve.

13. A server, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the method for identifying abnormal battery cells as described in any one of claims 1-11.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the method for identifying abnormal battery cells as described in any one of claims 1-11.

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