Methods, devices, servers, and storage media for identifying abnormal battery cells.

Abstract

This application relates to the field of battery management technology, and in particular to a method, apparatus, server, and storage medium for identifying abnormal battery cells. The method includes: acquiring charging data from multiple charge-discharge cycles of each battery cell in a battery pack; identifying the charging duration and initial charging capacity of each battery cell in the charging data within a reference voltage range; calculating the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle based on the charging duration and / or initial charging capacity; calculating the capacity increment and rate of change of the increment based on the actual charging capacity and reference charging capacity in each charge-discharge cycle; and identifying abnormal battery cells with self-discharge anomalies based on the capacity increment and rate of change of the increment. This solves the problems of existing technologies that rely on only a small amount of charging data to determine self-discharge anomalies, leading to misjudgments, and that fail to consider the impact of battery aging on charging capacity, resulting in a limited applicability of the self-discharge anomaly identification method.

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 charging cycles. Furthermore, it estimates the internal short-circuit resistance using the average voltage at the end of the two charging cycles. 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 cycles 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. It does not consider the inconsistent aging levels caused by inconsistencies among multiple batteries; 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.

[0005] Another related patent discloses a quantitative diagnostic method for internal short circuits in batteries based on the increase in charge within a charging voltage range. By selecting a specific voltage range, the method calculates the growth coefficient of the battery charge within that range during two adjacent charging cycles, and compares this growth coefficient with a threshold to determine whether an internal short circuit has occurred. However, this method has the following problems: 1. It only uses the change in charging capacity and whether it exceeds a threshold during two adjacent charging cycles for judgment, which can easily lead to misjudgments when the data changes abruptly; 2. It does not consider the impact of inconsistent battery aging on charging capacity. Summary of the Invention

[0006] One objective of this invention is to provide a method for identifying abnormal battery cells, in order to solve the problem that existing technologies, which rely on only a small amount of charging data to determine self-discharge abnormalities, are prone to misjudgment and do not take into account the impact of battery aging on charging capacity, resulting in a limited scope of application for self-discharge abnormality identification methods; 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.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] 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 charging duration and initial charging capacity of each battery cell in the battery pack within a reference voltage range in the charging data; calculating the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle based on the charging duration and / or the initial charging capacity; calculating the capacity increment and rate of change of the increment based on the actual charging capacity and the reference charging capacity in each charge-discharge cycle; and identifying abnormal battery cells among the battery cells that exhibit self-discharge abnormalities based on the capacity increment and the rate of change of the increment.

[0009] Based on the above technical means, the embodiments of this application can identify abnormal battery cells with self-discharge abnormalities by combining the capacity increment and the rate of change of increment during charge and discharge cycles, avoiding misjudgments caused by data jumps when only two charging processes are used, and enhancing the applicability of battery cell self-discharge abnormality identification.

[0010] Furthermore, the step of identifying abnormal battery cells with self-discharge abnormalities among the battery cells based on the capacity increment and the increment change rate includes: determining whether the capacity increment is greater than an increment threshold and whether the increment change rate is greater than a change rate threshold; if the capacity increment is greater than the increment threshold and the increment change rate is greater than the change rate threshold, then the battery cell is determined to be an abnormal battery cell with self-discharge abnormalities.

[0011] Based on the above technical means, the embodiments of this application can determine whether there is an abnormal battery cell with self-discharge abnormality by whether the capacity increment and the rate of change of increment during charge and discharge cycles are within the threshold range.

[0012] Further, the capacity increment and the rate of change of increment are calculated based on the actual charging capacity and the reference charging capacity for each charge-discharge cycle, including: using the difference between the actual charging capacity and the reference charging capacity as the capacity increment for each charge-discharge cycle; fitting the capacity increment for each charge-discharge cycle to obtain a curve of the capacity increment changing with the number of charge-discharge cycles; and determining the rate of change of increment based on the slope of the fitted curve.

[0013] Based on the above technical means, the embodiments of this application can calculate the capacity increment based on the actual charging capacity and the reference charging capacity, and fit the rate of change of the charging capacity increment with the number of cycles, so as to identify abnormal battery cells with self-discharge abnormalities based on the rate of change of the increment.

[0014] Furthermore, the step of calculating the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle based on the charging duration and / or the initial charging capacity includes: calculating the actual charging capacity of each battery cell in the reference voltage range based on the charging duration; calculating the aging coefficient of the charging capacity as a function of the number of charge-discharge cycles based on the actual charging capacity of each battery cell in each charge-discharge cycle; and calculating the reference charging capacity for each charge-discharge cycle based on the aging coefficient and the initial charging capacity of each battery cell.

[0015] Based on the above technical means, this application can calculate the aging coefficient of the charging capacity as a function of the number of charge-discharge cycles based on the actual charging capacity of each battery cell in each charge-discharge cycle, and calculate the reference charging capacity for each charge-discharge cycle based on the aging coefficient and the initial charging capacity of each battery cell. This takes into account the impact of inconsistent aging of each battery cell on the charging capacity, and improves the applicability of identifying battery cells with abnormal self-discharge among aged battery cells.

[0016] Further, calculating the actual charging capacity of each battery cell in the reference voltage range based on the charging time includes: integrating the charging current of each battery cell in the reference voltage range over time during the charging time to obtain the actual charging capacity of each battery cell in the reference voltage range.

[0017] Based on the above technical means, the embodiments of this application can calculate the actual charging capacity of each battery cell in the reference voltage range according to the charging time, so as to calculate the aging coefficient that changes with the number of charge and discharge cycles based on the actual charging capacity.

[0018] Furthermore, the step of calculating the aging coefficient of the charging capacity as a function of the number of charge-discharge cycles based on the actual charging capacity of each battery cell in each charge-discharge cycle includes: selecting a charging cycle number window for each battery cell; determining a target cycle number range for each battery cell based on the charging cycle number window; calculating the capacity difference between the actual charging capacity and the initial charging capacity in each charge-discharge cycle within the target cycle number range; fitting the capacity difference in each charge-discharge cycle within the target cycle number range to obtain a curve showing the change of the capacity difference as a function of the number of charge-discharge cycles; and determining the aging coefficient based on the curve.

[0019] Based on the above technical means, the embodiments of this application can calculate the capacity difference between the actual charging capacity and the initial charging capacity of each charge-discharge cycle within the target cycle range, fit the capacity difference to obtain the curve of the capacity difference changing with the number of charge-discharge cycles, and further determine the aging coefficient of each battery cell. Considering the impact of the battery aging process on the charging capacity, the applicability of battery self-discharge abnormality identification is improved.

[0020] Furthermore, identifying the charging time of each battery cell in the battery pack within the reference voltage range in the charging data includes: obtaining the upper limit voltage and the lower limit voltage of the reference voltage range; obtaining the first moment when the upper limit voltage is reached and the second moment when the lower limit voltage is reached for each battery cell; and determining the charging time of each battery cell within the reference voltage range based on the first moment and the second moment.

[0021] Based on the above technical means, the embodiments of this application can obtain the first time and the second time when each battery cell reaches the upper and lower limits of the reference voltage range, and determine the charging time of each battery cell in the reference voltage range based on the first time and the second time, so as to calculate the actual charging capacity of the battery cell in the subsequent calculation.

[0022] 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.

[0023] 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.

[0024] Furthermore, after identifying abnormal battery cells with self-discharge abnormalities among the battery cells based on the capacity increment and the rate of change of the increment, 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.

[0025] 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.

[0026] Furthermore, after identifying abnormal battery cells with self-discharge abnormalities among the individual battery cells based on the capacity increment and the rate of change of the increment, 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.

[0027] 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.

[0028] 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 the charging duration and initial charging capacity of each battery cell in the battery pack within a reference voltage range in the charging data, and calculating the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle based on the charging duration and / or the initial charging capacity; and an identification module for calculating the capacity increment and rate of change of the increment based on the actual charging capacity and the reference charging capacity in each charge-discharge cycle, and identifying abnormal battery cells among the battery cells that exhibit self-discharge abnormalities based on the capacity increment and the rate of change of the increment.

[0029] Furthermore, the identification module is further used to: determine whether the capacity increment is greater than the increment threshold and whether the increment change rate is greater than the change rate threshold; if the capacity increment is greater than the increment threshold and the increment change rate is greater than the change rate threshold, then the battery cell is determined to be an abnormal battery cell with self-discharge abnormality.

[0030] Furthermore, the identification module is further configured to: use the difference between the actual charging capacity and the reference charging capacity as the capacity increment for each charge-discharge cycle; fit the capacity increment for each charge-discharge cycle to obtain a curve showing the change in capacity increment with the number of charge-discharge cycles; and determine the rate of change of the increment based on the slope of the fitted curve.

[0031] Furthermore, the calculation module is further configured to: calculate the actual charging capacity of each battery cell in the reference voltage range based on the charging duration; calculate the aging coefficient of the charging capacity as a function of the number of charge-discharge cycles based on the actual charging capacity of each battery cell in each charge-discharge cycle; and calculate the reference charging capacity for each charge-discharge cycle based on the aging coefficient and the initial charging capacity of each battery cell.

[0032] Furthermore, the calculation module is further used to: integrate the charging current of each battery cell in the reference voltage range over time during the charging duration to obtain the actual charging capacity of each battery cell in the reference voltage range.

[0033] Furthermore, the calculation module is further configured to: select a charging cycle number window for each battery cell; calculate the capacity difference between the actual charging capacity and the initial charging capacity for each charge-discharge cycle within the target cycle number window; fit the capacity difference for each charge-discharge cycle within the target cycle number range to obtain a curve showing the change of capacity difference with the number of charge-discharge cycles; and determine the aging coefficient based on the curve.

[0034] Furthermore, the calculation module is further configured to: obtain the upper limit voltage and lower limit voltage of the reference voltage range; obtain the first time when the upper limit voltage is reached and the second time when the lower limit voltage is reached for each battery cell; and determine the charging time of each battery cell in the reference voltage range based on the first time and the second time.

[0035] 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; if the actual number of cycles is greater than a preset number, then acquire the charging data of each battery cell in the battery pack for multiple charge and discharge cycles, otherwise, do not identify abnormal battery cells.

[0036] 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 based on the capacity increment and the increment change rate; and to send the preset alert information to a preset terminal to provide a self-discharge abnormality alert based on the preset alert information.

[0037] 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 capacity increment and the increment change rate; and send the identifier to a preset terminal to locate the abnormal battery cell in the battery pack according to the identifier.

[0038] A server includes: 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 the above embodiments.

[0039] 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.

[0040] The beneficial effects of this invention are:

[0041] (1) The embodiments of this application can identify abnormal battery cells with self-discharge abnormalities by combining the capacity increment and the rate of change of increment during charge and discharge cycles, avoiding misjudgment caused by data jumps when only two charging processes are used, and enhancing the applicability of battery cell self-discharge abnormality identification.

[0042] (2) In this embodiment of the application, the presence of abnormal battery cells with self-discharge abnormality can be determined by whether the capacity increment and the rate of change of increment during charge and discharge cycles are within the threshold range.

[0043] (3) The embodiment of this application can calculate the capacity increment based on the actual charging capacity and the reference charging capacity, and fit the rate of change of the charging capacity increment with the number of cycles, so as to identify abnormal battery cells with self-discharge abnormality based on the rate of change of increment.

[0044] (4) The implementation of this application can calculate the aging coefficient of the charging capacity as a function of the number of charge-discharge cycles based on the actual charging capacity of each battery cell in each charge-discharge cycle, and calculate the reference charging capacity for each charge-discharge cycle based on the aging coefficient and the initial charging capacity of each battery cell. It takes into account the impact of the inconsistency of aging of each battery cell on the charging capacity, and improves the applicability of identifying the self-discharge abnormal battery cells in the aged battery cells.

[0045] (5) The embodiments of this application can calculate the actual charging capacity of each battery cell in the reference voltage range based on the charging time, so as to calculate the aging coefficient that changes with the number of charge and discharge cycles based on the actual charging capacity.

[0046] (6) The embodiments of this application can calculate the capacity difference between the actual charging capacity and the initial charging capacity of each charge-discharge cycle within the target cycle range, fit the capacity difference to obtain the curve of the capacity difference changing with the number of charge-discharge cycles, further determine the aging coefficient of each battery cell, consider the impact of the road battery aging process on the charging capacity, and improve the applicability of battery self-discharge abnormality identification.

[0047] (7) The embodiments of this application can obtain the first time and the second time when each battery cell reaches the upper and lower limits of the reference voltage range, and determine the charging time of each battery cell in the reference voltage range based on the first time and the second time, so as to calculate the actual charging capacity of the battery cell in the future.

[0048] (8) In this embodiment of the application, when the number of charge-discharge cycles is greater than the 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 abnormality.

[0049] (9) 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.

[0050] (10) In this embodiment of the application, after a battery cell with self-discharge abnormality is identified, 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.

[0051] 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

[0052] Figure 1 A flowchart illustrating the method for identifying abnormal battery cells provided in an embodiment of the present invention;

[0053] Figure 2 A flowchart illustrating a method for identifying abnormal battery cells according to an embodiment of the present invention;

[0054] Figure 3 A block diagram illustrating the device for identifying abnormal battery cells provided in an embodiment of the present invention;

[0055] Figure 4 This is a schematic diagram of the server structure provided in an embodiment of the present invention. Detailed Implementation

[0056] 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.

[0057] 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.

[0058] Specifically, Figure 1 This is a flowchart illustrating a method for identifying abnormal battery cells provided in an embodiment of this application.

[0059] like Figure 1 As shown, the method for identifying abnormal battery cells, applied to a server, includes the following steps:

[0060] In step S101, charging data of each individual battery cell in the battery pack for multiple charge-discharge cycles is obtained.

[0061] 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 operating data of the real vehicle. The real vehicle operating data refers to the voltage curve of each battery cell during the vehicle charging and driving discharge process stored in the cloud.

[0062] 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.

[0063] 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 limited; for example, it can be set to 6 or 7 cycles.

[0064] It is understood that the embodiments of this application can extract the actual number of charge and discharge cycles from 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 using only a small number of charge and discharge cycles to judge self-discharge abnormalities.

[0065] 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.

[0066] In step S102, the charging time and initial charging capacity of each battery cell in the battery pack within the reference voltage range are identified in the charging data, and the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle are calculated based on the charging time and / or initial charging capacity.

[0067] It is understood that, according to the embodiments of this application, the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle can be calculated based on the charging time and initial charging capacity of each battery cell in the reference voltage range.

[0068] In this embodiment of the application, identifying the charging time of each battery cell in the battery pack within the reference voltage range in the charging data includes: obtaining the upper limit voltage and lower limit voltage of the reference voltage range; obtaining a first moment when each battery cell is at the upper limit voltage and a second moment when it is at the lower limit voltage; and determining the charging time of each battery cell within the reference voltage range based on the first moment and the second moment.

[0069] It should be noted that due to the tiered charging strategy used in actual vehicle charging, different voltage ranges [V] are used. x V y Different charging currents I were used inside. x Reference voltage range [V rl V rh It should satisfy: V y ≥V rh >V rl ≥V x The reference voltage range should be within the voltage range [V]. x V y The reference voltage range is selected to ensure that as many individual battery cells as possible are charged to the reference voltage range during the charging process. Furthermore, the selection of the reference voltage range is not unique, and multiple reference voltage ranges can be selected for separate calculations.

[0070] It is understood that the embodiments of this application can obtain the upper limit voltage and lower limit voltage of the reference voltage range. In each charging process, the charging time when each battery cell reaches the lower limit voltage and upper limit voltage of the reference voltage range is recorded and recorded as the first time and the second time, respectively. The charging time of each battery cell in the reference voltage range is determined based on the first time and the second time.

[0071] In this embodiment of the application, calculating the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle based on the charging time and / or initial charging capacity includes: calculating the actual charging capacity of each battery cell in the reference voltage range based on the charging time; calculating the aging coefficient of the charging capacity as a function of the number of charge-discharge cycles based on the actual charging capacity of each battery cell in each charge-discharge cycle; and calculating the reference charging capacity for each charge-discharge cycle based on the aging coefficient and the initial charging capacity of each battery cell.

[0072] The reference charging capacity is the sum of the initial charging capacity and the aging factor within multiple charge-discharge cycles; the charging capacity increment is the difference between the charging capacity and the reference charging capacity within the selected reference voltage range for each charging cycle.

[0073] It is understood that the embodiments of this application can calculate the actual charging capacity of each battery cell in the selected reference voltage range based on the charging time, and calculate the aging coefficient of the relative charging capacity with the number of cycles in the selected reference voltage range based on the actual charging capacity of each battery cell in each charge-discharge cycle. The reference charging capacity in each charge-discharge cycle is calculated by using the aging coefficient and the initial charging capacity of each battery cell. The specific calculation method is described in the following embodiments and will not be repeated here. The embodiments of this application take into account the impact of inconsistent aging of each battery on the charging capacity, and improve the applicability of identifying battery cells with abnormal self-discharge among aged battery cells.

[0074] In this embodiment of the application, the actual charging capacity of each battery cell in the reference voltage range is calculated based on the charging time, including: integrating the charging current of each battery cell in the reference voltage range over time during the charging time to obtain the actual charging capacity of each battery cell in the reference voltage range.

[0075] The actual charging capacity of each battery cell within the selected reference voltage range is calculated as follows:

[0076] ,

[0077] in, For each battery cell to reach the upper limit of the reference voltage range during the k-th charging cycle. The charging time is i = 1, 2, ..., n, for a total of n battery cells; For each battery cell to reach the lower limit of the reference voltage range during the k-th charging cycle. During the charging time, The charging current is within the reference voltage range; This represents the charging capacity of each battery cell within the reference voltage range during the k-th charging cycle.

[0078] In this embodiment of the application, the aging coefficient of the charging capacity as a function of the number of charge-discharge cycles is calculated based on the actual charging capacity of each battery cell in each charge-discharge cycle. This includes: selecting a charging cycle number window for each battery cell; determining the target cycle number range for each battery cell based on the charging cycle number window; calculating the capacity difference between the actual charging capacity and the initial charging capacity in each charge-discharge cycle within the target cycle number range; fitting the capacity difference in each charge-discharge cycle within the target cycle number range to obtain a curve showing the change of the capacity difference as a function of the number of charge-discharge cycles; and determining the aging coefficient based on the curve.

[0079] Specifically, the aging factor calculation process is as follows: Record charging data within multiple charge-discharge cycles and select a charging cycle window W; for the first W charging cycles of long-term periodic charging data, calculate the difference between the charging capacity within the reference voltage range and the initial charging capacity in each charging cycle within the cycle number interval [1, 1+W], i.e., the relative charging capacity. Based on the relative charging capacity obtained from the first W charging cycles, a function reflecting the change in relative charging capacity with the number of charging cycles, i.e., the aging coefficient, is obtained by calculation and fitting. Furthermore, there is no single method for calculation and fitting; linear fitting, quadratic fitting, exponential fitting, or other polynomial fitting can be used.

[0080] The method for calculating the reference charging capacity within each charge-discharge cycle is as follows:

[0081] ,

[0082] in, The initial charging capacity of each battery cell within the reference voltage range during the first charging cycle over a long period; Let be the aging coefficient of each battery cell in the k-th charging cycle; This represents the reference charging capacity of each battery cell in the k-th charging cycle.

[0083] In step S103, the capacity increment and increment change rate are calculated based on the actual charging capacity and reference charging capacity of each charge-discharge cycle, and abnormal battery cells with self-discharge abnormalities are identified based on the capacity increment and increment change rate.

[0084] It is understood that the embodiments of this application can calculate the increment and rate of change of the charging capacity based on the actual charging capacity and the reference charging capacity in each charge-discharge cycle, and determine whether there is a self-discharge abnormality in each battery cell based on the increment and rate of change of the charging capacity over a long period of time, thus avoiding misjudgment caused by data jumps when only two charging processes are used.

[0085] In this embodiment of the application, the capacity increment and the rate of change of increment are calculated based on the actual charging capacity and the reference charging capacity for each charge-discharge cycle, including: using the difference between the actual charging capacity and the reference charging capacity as the capacity increment for each charge-discharge cycle; fitting the capacity increment for each charge-discharge cycle to obtain a curve of the capacity increment changing with the number of charge-discharge cycles; and determining the rate of change of increment based on the slope of the fitted curve.

[0086] It is understood that, in the embodiments of this application, the charging capacity increment in each charging cycle is calculated based on the actual charging capacity and the reference charging capacity, and the rate of change of the capacity increment with the number of cycles is obtained by fitting the capacity increment.

[0087] Specifically, in this application embodiment, the process of determining whether a battery cell has a self-discharge abnormality based on the increase in charging capacity and the rate of change of the increase over a long period is as follows: Calculate the increase in charging capacity during each charging cycle. The rate of change of charging capacity increment with the number of cycles was fitted using a linear form.

[0088] In this embodiment of the application, identifying abnormal battery cells with self-discharge abnormalities among each battery cell based on capacity increment and increment change rate includes: determining whether the capacity increment is greater than an increment threshold and whether the increment change rate is greater than a change rate threshold; if the capacity increment is greater than the increment threshold and the increment change rate is greater than the change rate threshold, then the battery cell is determined to be an abnormal battery cell with self-discharge abnormality.

[0089] It is understood that, according to the embodiments of this application, if the capacity increment is greater than the increment threshold k1 and the increment change rate is greater than the threshold k2, the battery cell is determined to be a self-discharge abnormal cell.

[0090] In this embodiment of the application, after identifying abnormal battery cells with self-discharge abnormalities in each battery cell based on the capacity increment and the rate of change of the increment, 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.

[0091] 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.

[0092] 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.

[0093] In this embodiment of the application, after identifying abnormal battery cells with self-discharge abnormalities in each battery cell based on the capacity increment and the rate of change of increment, 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.

[0094] 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.

[0095] The following specific embodiment illustrates the method for identifying abnormal battery cells according to this application. Figure 2 As shown, it includes the following steps:

[0096] Step 1: Based on the long-term operating data of the actual vehicle, extract the charging process in each charge-discharge cycle.

[0097] 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.

[0098] Step 2: For each individual battery cell, determine the range of reference voltage values ​​based on the charging voltage curve.

[0099] 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 Reference voltage range [V rl V rh It should satisfy: V y ≥V rh >V rl ≥V x The reference voltage range should be within the voltage range [V]. x V y The reference voltage range is selected to ensure that as many individual battery cells as possible are charged to the reference voltage range during the charging process. Furthermore, the selection of the reference voltage range is not unique, and multiple reference voltage ranges can be selected for separate calculations.

[0100] Step 3: During each charging process, record the charging time when each battery cell reaches the lower limit voltage and the upper limit voltage within the reference voltage range.

[0101] For real-vehicle data using stepped current charging, only the charging times when each battery cell reaches the upper or lower limit of the reference voltage range and has the same charging current as the voltage range it is in are recorded.

[0102] Step 4: Calculate the charging capacity of each battery cell within the selected reference voltage range based on the charging time of each individual battery cell.

[0103] The calculation process for the charging capacity of each battery cell within the selected reference voltage range is as follows:

[0104] ,

[0105] In the formula, For each battery cell to reach the upper limit of the reference voltage range during the k-th charging cycle. The charging time is i = 1, 2, ..., n, for a total of n battery cells; For each battery cell to reach the lower limit of the reference voltage range during the k-th charging cycle. During the charging time, The charging current is within the reference voltage range; This represents the charging capacity of each battery cell within the reference voltage range during the k-th charging cycle.

[0106] Step 5: Select the cycle number window, and calculate the aging coefficient of the relative charging capacity as a function of the cycle number within the selected reference voltage range based on the charging data within the window over a long period.

[0107] The aging factor is calculated as follows: During the first charging cycle of recording long-term periodic charging data, the initial charging capacity of each battery cell within the reference voltage range is... Select the charging cycle number window W; for the first W charging cycles of long-term periodic charging data, calculate the difference between the charging capacity in the reference voltage range and the initial charging capacity in each charging cycle within the cycle number interval [1, 1+W], i.e., the relative charging capacity. The relative charging capacity obtained from the first W charging cycles is calculated and fitted to obtain a result reflecting the relative charging capacity as a function of the number of charging cycles. A changing function, i.e., the aging coefficient. Furthermore, there is no single method for calculation and fitting; linear fitting, quadratic fitting, exponential fitting, or other polynomial fitting can be used.

[0108] Step 6: For each battery cell within the reference voltage range, calculate the reference charging capacity for each charging cycle using the aging factor and the initial charging capacity over a long period.

[0109] The method for calculating the reference charging capacity within each charging cycle is as follows:

[0110] ,

[0111] In the formula, The initial charging capacity of each battery cell within the reference voltage range during the first charging cycle over a long period; Let be the aging coefficient of each battery cell in the k-th charging cycle; This represents the reference charging capacity of each battery cell in the k-th charging cycle.

[0112] Step 7: Determine whether there is any self-discharge abnormality in each battery cell based on the increase in charging capacity and the rate of change of the increase over a long period of time.

[0113] The process of determining whether a battery cell has a self-discharge abnormality based on the increase in charging capacity and the rate of change of the increase over a long period is as follows: calculate the increase in charging capacity during each charging cycle. The rate of change of the charging capacity increment with the number of cycles is fitted using a linear form. When the charging capacity increment is greater than the threshold k1 and the rate of change of the increment is greater than the threshold k2, the battery cell is judged to be an abnormal self-discharge cell.

[0114] The method for identifying abnormal battery cells proposed in this application can identify abnormal battery cells with self-discharge abnormalities based on the capacity increment and rate of change of the increment during charge and discharge cycles. This avoids misjudgments caused by data jumps when only two charging processes are used, enhances the applicability of identifying battery cell self-discharge abnormalities, and considers the impact of inconsistent aging of individual batteries on charging capacity, thus improving the applicability of identifying battery cells with self-discharge abnormalities among aged battery cells.

[0115] Next, with reference to the accompanying drawings, an identification device for abnormal battery cells according to an embodiment of this application is described.

[0116] Figure 3 This is a block diagram of an abnormal battery cell identification device according to an embodiment of this application.

[0117] like Figure 3 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.

[0118] The acquisition module 100 is used to acquire charging data of each battery cell in the battery pack over multiple charge-discharge cycles; the calculation module 200 is used to identify the charging time and initial charging capacity of each battery cell in the battery pack within the reference voltage range in the charging data, and calculate the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle based on the charging time and / or initial charging capacity; the identification module 300 is used to calculate the capacity increment and rate of change of increment based on the actual charging capacity and reference charging capacity in each charge-discharge cycle, and identify abnormal battery cells with self-discharge abnormalities based on the capacity increment and rate of change of increment.

[0119] In this embodiment of the application, the identification module 300 is further used to: determine whether the capacity increment is greater than the increment threshold and whether the increment change rate is greater than the change rate threshold; if the capacity increment is greater than the increment threshold and the increment change rate is greater than the change rate threshold, then the battery cell is determined to be an abnormal battery cell with self-discharge abnormality.

[0120] In this embodiment of the application, the identification module 300 is further configured to: use the difference between the actual charging capacity and the reference charging capacity as the capacity increment for each charge-discharge cycle; fit the capacity increment for each charge-discharge cycle to obtain a curve of the capacity increment changing with the number of charge-discharge cycles, and determine the rate of change of increment based on the slope of the fitted curve.

[0121] In this embodiment of the application, the calculation module 200 is further configured to: calculate the actual charging capacity of each battery cell in the reference voltage range based on the charging time; calculate the aging coefficient of the charging capacity as a function of the number of charge-discharge cycles based on the actual charging capacity of each battery cell in each charge-discharge cycle; and calculate the reference charging capacity for each charge-discharge cycle based on the aging coefficient and the initial charging capacity of each battery cell.

[0122] In this embodiment of the application, the calculation module 200 is further used to: integrate the charging current of each battery cell in the reference voltage range over a period of time to obtain the actual charging capacity of each battery cell in the reference voltage range.

[0123] In this embodiment of the application, the calculation module 200 is further configured to: select a charging cycle number window for each battery cell; calculate the capacity difference between the actual charging capacity and the initial charging capacity for each charge-discharge cycle within the target cycle number window; fit the capacity difference for each charge-discharge cycle within the target cycle number range to obtain a curve showing the change of capacity difference with the number of charge-discharge cycles; and determine the aging coefficient based on the curve.

[0124] In this embodiment of the application, the calculation module 200 is further configured to: obtain the upper limit voltage and the lower limit voltage of the reference voltage range; obtain the first moment when the upper limit voltage is reached and the second moment when the lower limit voltage is reached for each battery cell; and determine the charging time of each battery cell in the reference voltage range based on the first moment and the second moment.

[0125] In this embodiment of the application, the apparatus 10 further includes an extraction module.

[0126] 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.

[0127] In this embodiment of the application, the device 10 further includes a reminder module.

[0128] 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 capacity increment and the rate of change of the increment; and to send the preset reminder message to a preset terminal to provide a self-discharge abnormality reminder based on the preset reminder message.

[0129] In this embodiment of the application, the apparatus 10 further includes a sending module.

[0130] The sending module is used to identify abnormal battery cells with self-discharge abnormalities in each battery cell after identifying them based on capacity increment and rate of change of increment; and to send the identifier to a preset terminal to locate the abnormal battery cell in the battery pack based on the identifier.

[0131] 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.

[0132] The abnormal battery cell identification device proposed in the embodiments of this application can identify abnormal battery cells with self-discharge abnormalities based on the capacity increment and increment change rate of the charge and discharge cycle. This avoids misjudgment caused by data jumps when only two charging processes are used, enhances the applicability of battery cell self-discharge abnormality identification, and considers the impact of inconsistent aging of each battery on the charging capacity, thus improving the applicability of identifying battery cells with self-discharge abnormalities among aged battery cells.

[0133] Figure 4 A schematic diagram of the structure of a server provided in an embodiment of this application. The server may include:

[0134] The memory 401, the processor 402, and the computer program stored on the memory 401 and capable of running on the processor 402.

[0135] When the processor 402 executes the program, it implements the method for identifying abnormal battery cells provided in the above embodiments.

[0136] Furthermore, the server also includes:

[0137] Communication interface 403 is used for communication between memory 401 and processor 402.

[0138] The memory 401 is used to store computer programs that can run on the processor 402.

[0139] The memory 401 may include high-speed RAM (Random Access Memory) memory, and may also include non-volatile memory, such as at least one disk storage.

[0140] If the memory 401, processor 402, and communication interface 403 are implemented independently, then the communication interface 403, memory 401, and processor 402 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 4 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.

[0141] Optionally, in a specific implementation, if the memory 401, processor 402, and communication interface 403 are integrated on a single chip, then the memory 401, processor 402, and communication interface 403 can communicate with each other through an internal interface.

[0142] Processor 402 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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: Obtain charging data for each individual battery cell in the battery pack after multiple charge-discharge cycles; Identify the charging duration and initial charging capacity of each battery cell in the battery pack within the reference voltage range in the charging data, and calculate the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle based on the charging duration and / or the initial charging capacity. The capacity increment and the rate of change of increment are calculated based on the actual charging capacity and the reference charging capacity of each charge-discharge cycle. Abnormal battery cells with self-discharge abnormalities are identified based on the capacity increment and the rate of change of increment. The capacity increment and rate of change are calculated based on the actual charging capacity and reference charging capacity for each charge-discharge cycle, including: The difference between the actual charging capacity and the reference charging capacity is used as the capacity increment for each charge-discharge cycle. The capacity increment for each charge-discharge cycle is fitted to obtain a curve showing the change in capacity increment with the number of charge-discharge cycles. The rate of change of the increment is determined based on the slope of the fitted curve. The calculation of the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle based on the charging duration and / or the initial charging capacity includes: Calculate the actual charging capacity of each battery cell in the reference voltage range based on the charging time; The aging coefficient of the charging capacity as a function of the number of charge-discharge cycles is calculated based on the actual charging capacity of each battery cell in each charge-discharge cycle. The reference charging capacity for each charge-discharge cycle is then calculated based on the aging coefficient and the initial charging capacity of each battery cell.

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 among the battery cells based on the capacity increment and the rate of change of the increment includes: Determine whether the capacity increment is greater than the increment threshold and whether the rate of change of the increment is greater than the rate of change threshold; If the capacity increment is greater than the increment threshold and the rate of change of the increment is greater than the rate of change 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, characterized in that, The calculation of the actual charging capacity of each battery cell in the reference voltage range based on the charging time includes: The actual charging capacity of each battery cell in the reference voltage range is obtained by integrating the charging current of each battery cell over the time period during the charging period.

4. The method for identifying abnormal battery cells according to claim 1, characterized in that, The calculation of the aging coefficient based on the actual charging capacity of each battery cell in each charge-discharge cycle as a function of the number of charge-discharge cycles includes: Select the charging cycle count window for each battery cell; According to the target cycle number range of each battery cell in the charging cycle number window; Calculate the capacity difference between the actual charging capacity and the initial charging capacity for each charge-discharge cycle within the target cycle range, and fit the capacity difference for each charge-discharge cycle within the target cycle range to obtain a curve showing the change of capacity difference with the number of charge-discharge cycles. Determine the aging coefficient based on the curve.

5. The method for identifying abnormal battery cells according to claim 1, characterized in that, The step of identifying the charging time of each individual cell in the battery pack within the reference voltage range in the charging data includes: Obtain the upper and lower limits of the reference voltage range; The charging time of each battery cell in the reference voltage range is determined based on the first moment when the upper limit voltage is reached and the second moment when the lower limit voltage is reached.

6. 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.

7. The method for identifying abnormal battery cells according to claim 1, characterized in that, After identifying abnormal battery cells with self-discharge anomalies among the individual battery cells based on the capacity increment and the rate of change of the increment, 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.

8. The method for identifying abnormal battery cells according to claim 1, characterized in that, After identifying abnormal battery cells with self-discharge abnormalities among the individual battery cells based on the capacity increment and the rate of change of the increment, 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.

9. A device for identifying abnormal battery cells, characterized in that, The device is applied to a server to implement the method for identifying abnormal battery cells as described in any one of claims 1-8, wherein the device comprises: 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 charging time and initial charging capacity of each battery cell in the battery pack in the reference voltage range in the charging data, and to calculate the actual charging capacity and reference charging capacity of each battery cell in each charge-discharge cycle based on the charging time and / or the initial charging capacity. The identification module is used to calculate the capacity increment and the rate of change of the increment based on the actual charging capacity and the reference charging capacity of each charge-discharge cycle, and to identify abnormal battery cells with self-discharge abnormalities among the battery cells based on the capacity increment and the rate of change of the increment.

10. 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 1-8.

11. 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 1-8.

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