CN116908729A - Method and device for identifying abnormal battery cells, server and storage medium - Google Patents
Method and device for identifying abnormal battery cells, server and storage medium Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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- Y02E60/10—Energy storage using batteries
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Abstract
The application relates to the technical field of battery management, in particular to a method and a device for identifying abnormal battery cells, 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 monomer in the battery pack; the charging time length and the initial charging capacity of each battery cell of the battery pack in the charging data in a reference voltage interval are identified, and the actual charging capacity and the reference charging capacity of each battery cell in each charging and discharging cycle are calculated according to the charging time length and/or the initial charging capacity; and calculating capacity increment and increment change rate according to the actual charge capacity and the reference charge capacity of each charge-discharge cycle, and identifying abnormal battery cells with self-discharge abnormality in each battery cell according to the capacity increment and the increment change rate. Therefore, the problems that in the prior art, misjudgment is easy to occur when the self-discharge abnormality is judged by only using a small amount of charging data, the influence of battery aging on the charging capacity is not considered, the application range of the self-discharge abnormality identification method is small, and the like are solved.
Description
Technical Field
The invention relates to the technical field of battery management, in particular to a method and a device for identifying abnormal battery cells, a server and a storage medium.
Background
With the rapid development and popularization of electric vehicles, it is becoming more and more important to ensure the safety of the electric vehicles by using power batteries as core components of the electric vehicles. The accidents such as fire and even explosion of the electric automobile caused by the thermal runaway of the power battery are easy to cause casualties and property loss, and are important points and difficulties in the research of the safety problem of the electric automobile at present.
One of the main causes of thermal runaway in power cells is internal battery short circuits. The internal short circuit causes the internal formation of a loop in the battery and continuously consumes electric quantity, and the external appearance is that the electric quantity of the battery is abnormally reduced, namely, the self-discharge is abnormal. As the severity of internal short circuits increases, the self-discharge of the battery increases abnormally, the amount of heat generated increases, and eventually, thermal runaway of the battery is caused.
The related art discloses a method and a device for detecting micro short circuit of a battery, which specifically realize the method and the device by calculating the internal short circuit leakage current of the battery unit according to the charge capacity difference of the battery unit relative to a reference unit at the end time of two times of charging in the process of two times of charging, and further estimating the internal short circuit resistance value through the average voltage at the end time of two times of charging. And finally, comparing the leakage current and the internal short circuit resistance with corresponding threshold values to judge whether an internal short circuit exists. However, this method has the following problems: 1. only two charging processes are adopted for judgment, and the battery is easy to be influenced by voltage/current data jump, partial data loss and the like when the battery is applied to real vehicle data, and the normal battery is misjudged as an internal short-circuit battery; 2. the degree of aging inconsistency caused when there is inconsistency in the plurality of batteries is not considered; 3. the calculation process is complex, and a plurality of parameters such as reference charging time, reference charging capacity, average voltage, internal short circuit resistance and the like need to be calculated.
Another related patent discloses a quantitative diagnosis method for short circuit in a battery based on the increase of the electric quantity in a charging voltage interval. And calculating the growth coefficient of the battery charge quantity in the voltage interval in the adjacent two charging processes by selecting a specific voltage interval, and comparing the growth coefficient with a threshold value to judge whether the battery is internally short-circuited or not. However, this method has the following problems: 1. only adopting the charge capacity change in the adjacent two charging processes and whether the charge capacity change exceeds a threshold value to judge, and easily generating misjudgment when data jump; 2. the effect of battery age non-uniformity on charge capacity is not considered.
Disclosure of Invention
The invention aims to provide an abnormal battery monomer identification method, which solves the problems that in the prior art, only a small amount of charging data is adopted to judge that self-discharge abnormality is easy to generate misjudgment, and the influence of battery aging on charging capacity is not considered, so that the application range of the self-discharge abnormality identification method is small; the second purpose is to provide a recognition device of abnormal battery cell; a third object is to provide a server; a fourth object is to provide a computer-readable storage medium.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
A method for identifying abnormal battery cells, the method being applied to a server, wherein the method comprises the steps of: acquiring charging data of multiple charging and discharging cycles of each battery monomer in the battery pack; the charging time length and the initial charging capacity of each battery cell of the battery pack in a reference voltage interval are identified in the charging data, and the actual charging capacity and the reference charging capacity of each battery cell in each charging and discharging cycle are calculated according to the charging time length and/or the initial charging capacity; and calculating a capacity increment and an increment change rate according to the actual charge capacity and the reference charge capacity of each charge-discharge cycle, and identifying abnormal battery cells with abnormal self-discharge in each battery cell according to the capacity increment and the increment change rate.
According to the technical means, the embodiment of the application can jointly identify the abnormal battery cells with the self-discharge abnormality according to the capacity increment and the increment change rate of the charge-discharge cycle, avoid misjudgment caused by data jump when only adopting the two charge processes, and enhance the applicability of the self-discharge abnormality identification of the battery cells.
Further, the identifying the abnormal cell in which the self-discharge abnormality exists in the cells according to the capacity increment and the increment change rate includes: judging whether the capacity increment is larger than an increment threshold value and whether the increment change rate is larger than a change rate threshold value; and if the capacity increment is larger than the increment threshold and the increment change rate is larger than the change rate threshold, judging that the battery cell is an abnormal battery cell with self-discharge abnormality.
According to the technical means, the embodiment of the application can judge the abnormal battery cell with the self-discharge abnormality through whether the capacity increment and the increment change rate of the charge-discharge cycle are within the threshold range.
Further, calculating a capacity increment and an increment change rate from the actual charge capacity and the reference charge capacity of each charge-discharge cycle, including: taking the difference value between the actual charge capacity and the reference charge capacity as the capacity increment of each charge-discharge cycle; fitting the capacity increment of each charge-discharge cycle to obtain a curve of the capacity increment changing along with the charge-discharge cycle times, and determining the increment change rate according to the fitting slope of the curve.
According to the technical means, the embodiment of the application can calculate the capacity increment according to the actual charging capacity and the reference charging capacity, and fit the change rate of the charging capacity increment along with the change of the cycle times, so that the abnormal battery cells with the self-discharge abnormality can be identified according to the increment change rate.
Further, the calculating the actual charge capacity and the reference charge capacity of each battery cell in each charge-discharge cycle according to the charge duration and/or the initial charge capacity includes: calculating the actual charging capacity of each battery cell in the reference voltage interval according to the charging duration; and calculating an aging coefficient of the charge capacity of each battery cell according to the change of the actual charge capacity of each battery cell in each charge-discharge cycle along with the charge-discharge cycle times, and calculating the reference charge capacity of each charge-discharge cycle according to the aging coefficient and the initial charge capacity of each battery cell.
According to the technical means, the method and the device can calculate the aging coefficient of the charge capacity changing along with the charge-discharge cycle times according to the actual charge capacity of each battery cell in each charge-discharge cycle, calculate the reference charge capacity of each charge-discharge cycle according to the aging coefficient and the initial charge capacity of each battery cell, consider the influence of the aging inconsistency of each battery on the charge capacity, and improve the applicability of identifying the self-discharge abnormal battery cells in the aged battery cells.
The calculating the actual charging capacity of each battery cell in the reference voltage interval according to the charging duration further includes: and carrying out time integration on the charging current of each battery cell in the reference voltage interval in the charging duration to obtain the actual charging capacity of each battery cell in the reference voltage interval.
According to the technical means, the embodiment of the application can calculate the actual charge capacity of each battery cell in the reference voltage interval according to the charge time length, so that the aging coefficient changing along with the charge and discharge cycle times can be calculated according to the actual charge capacity.
Further, the calculating the aging coefficient of the charge capacity according to the actual charge capacity of each battery cell in each charge-discharge cycle and the change of the charge capacity along with the number of charge-discharge cycles includes: selecting a charging cycle time window of each charging monomer; according to the charging cycle number window, the target cycle number interval of each charging monomer is obtained; calculating the capacity difference between the actual charge capacity and the charge initial capacity of each charge-discharge cycle in the target cycle number interval, fitting the capacity difference of each charge-discharge cycle in the target cycle number interval to obtain a curve of the capacity difference changing along with the charge-discharge cycle number, and determining the aging coefficient according to the curve.
According to the technical means, the embodiment of the application can further determine the aging coefficient of each battery cell by calculating the capacity difference between the actual charge capacity and the charge initial capacity of each charge-discharge cycle in the target cycle number interval and fitting the capacity difference to obtain the curve of the capacity difference changing along with the charge-discharge cycle number, and the application range of the self-discharge abnormality identification of the battery is improved by considering the influence of the battery aging process on the charge capacity.
Further, the identifying the charging duration of each battery cell of the battery pack in the charging data in the reference voltage interval includes: acquiring an upper limit voltage and a lower limit voltage of the reference voltage interval; and acquiring a first moment when each battery cell is at the upper limit voltage and a second moment when each battery cell is at the lower limit voltage, and determining the charging time of each battery cell in a reference voltage interval according to the first moment and the second moment.
According to the technical means, the embodiment of the application can acquire the first time and the second time when each battery cell reaches the upper limit and the lower limit of the reference voltage interval, and determine the charging time of each battery cell in the reference voltage interval according to the first time and the second time so as to calculate the actual charging capacity of the battery cell subsequently.
Further, before acquiring the charge data of multiple charge-discharge cycles of each battery cell in the battery pack, the method further comprises: acquiring charge and discharge data of a battery pack; extracting the actual times of charge and discharge cycles in the charge and discharge data; and if the actual times are greater than the preset times, acquiring charging data of multiple charging and discharging cycles of each battery cell in the battery pack, otherwise, not identifying the abnormal battery cell.
According to the technical means, the embodiment of the application can acquire the charging data of the repeated charging and discharging cycles of each battery cell in the battery pack when the number of the charging and discharging cycles is larger than the preset number, otherwise, the abnormal battery cells are not identified, and the misjudgment caused by data jump when the self-discharging abnormal judgment is carried out only by adopting a few charging and discharging processes is avoided.
Further, after identifying the abnormal cell in which the self-discharge abnormality exists in the respective cells based on the capacity increment and the increment change rate, it further includes: generating preset reminding information; and sending the preset reminding information to a preset terminal so as to carry out self-discharge abnormal reminding according to the preset reminding information.
According to the technical means, after the battery monomer with the self-discharge abnormality is identified, the embodiment of the application can remind a user to timely process the battery monomer, so that the phenomenon of thermal runaway of the power battery is avoided.
Further, after identifying the abnormal cell in which the self-discharge abnormality exists in the respective cells based on the capacity increment and the increment change rate, it further includes: identifying the identity of the abnormal battery cell; and sending the identification to a preset terminal so as to locate the abnormal battery cells in the battery pack according to the identification.
According to the technical means, after the battery cell with the self-discharge abnormality is identified, the identification of the abnormal battery cell can be identified, so that a user can position the abnormal battery cell in the battery pack according to the identification and replace the abnormal battery cell in time.
An apparatus for identifying abnormal battery cells, the apparatus being applied to a server, wherein the apparatus comprises: the acquisition module is used for acquiring charging data of multiple charging and discharging cycles of each battery cell in the battery pack; the calculation module is used for identifying the charging duration and the initial charging capacity of each battery cell of the battery pack in the reference voltage interval in the charging data, and calculating the actual charging capacity and the reference charging capacity of each battery cell in each charging and discharging cycle according to the charging duration and/or the initial charging capacity; and the identification module is used for calculating a capacity increment and an increment change rate according to the actual charge capacity and the reference charge capacity of each charge-discharge cycle, and identifying abnormal battery cells with self-discharge abnormality in each battery cell according to the capacity increment and the increment change rate.
Further, the identification module is further to: judging whether the capacity increment is larger than an increment threshold value and whether the increment change rate is larger than a change rate threshold value; and if the capacity increment is larger than the increment threshold and the increment change rate is larger than the change rate threshold, judging that the battery cell is an abnormal battery cell with self-discharge abnormality.
Further, the identification module is further to: taking the difference value between the actual charge capacity and the reference charge capacity as the capacity increment of each charge-discharge cycle; fitting the capacity increment of each charge-discharge cycle to obtain a curve of the capacity increment changing along with the charge-discharge cycle times, and determining the increment change rate according to the fitting slope of the curve.
Further, the computing module is further to: calculating the actual charging capacity of each battery cell in the reference voltage interval according to the charging duration; and calculating an aging coefficient of the charge capacity of each battery cell according to the change of the actual charge capacity of each battery cell in each charge-discharge cycle along with the charge-discharge cycle times, and calculating the reference charge capacity of each charge-discharge cycle according to the aging coefficient and the initial charge capacity of each battery cell.
Further, the computing module is further to: and carrying out time integration on the charging current of each battery cell in the reference voltage interval in the charging duration to obtain the actual charging capacity of each battery cell in the reference voltage interval.
Further, the computing module is further to: selecting a charging cycle time window of each charging monomer; according to the charging cycle number window, the target cycle number interval of each charging monomer is obtained; calculating the capacity difference between the actual charge capacity and the charge initial capacity of each charge-discharge cycle in the target cycle number interval, fitting the capacity difference of each charge-discharge cycle in the target cycle number interval to obtain a curve of the capacity difference changing along with the charge-discharge cycle number, and determining the aging coefficient according to the curve.
Further, the computing module is further to: acquiring an upper limit voltage and a lower limit voltage of the reference voltage interval; and acquiring a first moment when each battery cell is at the upper limit voltage and a second moment when each battery cell is at the lower limit voltage, and determining the charging time of each battery cell in a reference voltage interval according to the first moment and the second moment.
Further, the device for identifying abnormal battery cells further comprises: the extraction module is used for acquiring charge and discharge data of the battery pack before acquiring charge data of multiple charge and discharge cycles of each battery cell in the battery pack; extracting the actual times of charge and discharge cycles in the charge and discharge data; and if the actual times are greater than the preset times, acquiring charging data of multiple charging and discharging cycles of each battery cell in the battery pack, otherwise, not identifying the abnormal battery cell.
Further, the device for identifying abnormal battery cells further comprises: the reminding module is used for generating preset reminding information after identifying abnormal battery cells with abnormal self-discharge in each battery cell according to the capacity increment and the increment change rate; and sending the preset reminding information to a preset terminal so as to carry out self-discharge abnormal reminding according to the preset reminding information.
Further, the device for identifying abnormal battery cells further comprises: a transmitting module, configured to identify an identifier of an abnormal battery cell after identifying, according to the capacity increment and the increment change rate, that the abnormal battery cell has a self-discharge abnormality in each battery cell; and sending the identification to a preset terminal so as to locate the abnormal battery cells in the battery pack according to the identification.
A server, comprising: the system comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to realize the identification method of the abnormal battery cell as described in the embodiment.
A computer-readable storage medium having stored thereon a computer program that is executed by a processor for implementing the method of identifying abnormal cells as described in the above embodiments.
The application has the beneficial effects that:
(1) The embodiment of the application can jointly identify the abnormal battery cells with the self-discharge abnormality according to the capacity increment and the increment change rate of the charge-discharge cycle, avoid misjudgment caused by data jump when only adopting the two charge processes, and enhance the applicability of the self-discharge abnormality identification of the battery cells.
(2) The embodiment of the application can judge the abnormal battery monomer with the self-discharge abnormality through whether the capacity increment and the increment change rate of the charge-discharge cycle are in the threshold range.
(3) According to the embodiment of the application, the capacity increment can be calculated according to the actual charging capacity and the reference charging capacity, and the change rate of the charging capacity increment along with the change of the circulation times is fitted, so that the abnormal battery monomer with the self-discharge abnormality can be identified according to the increment change rate.
(4) According to the method and the device, the aging coefficient of the charge capacity of each battery cell changing along with the charge-discharge cycle times can be calculated according to the actual charge capacity of each battery cell in each charge-discharge cycle, and the reference charge capacity of each charge-discharge cycle is calculated according to the aging coefficient and the initial charge capacity of each battery cell, so that the influence of the aging inconsistency of each battery on the charge capacity is considered, and the applicability of identifying the self-discharge abnormal battery cell in the aged battery cell is improved.
(5) According to the embodiment of the application, the actual charge capacity of each battery cell in the reference voltage interval can be calculated according to the charge duration, so that the aging coefficient which changes along with the charge and discharge cycle times can be calculated according to the actual charge capacity.
(6) According to the embodiment of the application, the capacity difference between the actual charge capacity and the initial charge capacity of each charge-discharge cycle in the target cycle number interval can be calculated, the capacity difference is fitted to obtain the curve of the capacity difference changing along with the charge-discharge cycle number, the aging coefficient of each battery monomer is further determined, the influence of the aging process of the road battery on the charge capacity is considered, and the application range of the self-discharge abnormality identification of the battery is improved.
(7) The embodiment of the application can acquire the first time and the second time when each battery cell reaches the upper limit and the lower limit of the reference voltage interval, and determine the charging time of each battery cell in the reference voltage interval according to the first time and the second time so as to calculate the actual charging capacity of the battery cell subsequently.
(8) According to the embodiment of the application, when the number of charge and discharge cycles is greater than the preset number, the charge data of the charge and discharge cycles of each battery cell in the battery pack can be obtained, otherwise, the abnormal battery cells are not identified, and the misjudgment caused by data jump when the self-discharge abnormal judgment is carried out only by adopting a few charge and discharge processes is avoided.
(9) According to the embodiment of the application, after the battery monomer with the self-discharge abnormality is identified, the user can be reminded to timely process, and the phenomenon of thermal runaway of the power battery is avoided.
(10) The embodiment of the application can identify the identification of the abnormal battery cell after identifying the battery cell with the self-discharge abnormality, so that a user can position the abnormal battery cell in the battery pack according to the identification and replace the abnormal battery cell in time.
Additional aspects and advantages of the 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 the application.
Drawings
Fig. 1 is a flow chart of a method for identifying an abnormal battery cell according to an embodiment of the present application;
FIG. 2 is a flowchart of a method for identifying abnormal battery cells according to an embodiment of the present application;
Fig. 3 is a schematic block diagram of an apparatus for identifying abnormal battery cells according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a server according to an embodiment of the present invention.
Detailed Description
Further advantages and effects of the present invention will become readily apparent to those skilled in the art from the disclosure herein, by referring to the accompanying drawings and the preferred embodiments. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be understood that the preferred embodiments are presented by way of illustration only and not by way of limitation.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present invention by way of illustration, and only the components related to the present invention are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
Specifically, fig. 1 is a schematic flow chart of a method for identifying an abnormal battery cell according to an embodiment of the present application.
As shown in fig. 1, the method for identifying abnormal battery cells is applied to a server, and comprises the following steps:
in step S101, charge data of a plurality of charge-discharge cycles of each battery cell in the battery pack is acquired.
The embodiment of the application can extract the charging data of each charging and discharging cycle of each battery cell in the battery pack based on the running data of the real vehicle in a long time period, wherein the real vehicle running data refer to the voltage curves of each battery cell in the charging and driving and discharging processes of the vehicle stored in the cloud.
In the embodiment of the application, before acquiring the charging data of multiple charging and discharging cycles of each battery cell in the battery pack, the method further comprises the following steps: acquiring charge and discharge data of a battery pack; extracting the actual times of charge and discharge cycles in the charge and discharge data; if the actual times are greater than the preset times, charging data of multiple charging and discharging cycles of each battery cell in the battery pack are obtained, and otherwise, abnormal battery cells are not identified.
Wherein, the single charge and discharge of the battery cell is considered as one charge and discharge cycle. The preset number of times may be set according to the specific situation, and is not limited thereto, and may be set to 6 times or 7 times, for example.
It can be understood that the embodiment of the application can extract the actual times in the charge and discharge data, and acquire the charge data of the charge and discharge cycles of each battery cell in the battery pack when the charge and discharge cycle times are greater than the preset times, otherwise, the identification of the abnormal battery cell is not performed, and the misjudgment caused by data jump when the self-discharge abnormal judgment is performed only by adopting a small quantity of charge and discharge cycle processes is avoided.
For example, taking the preset number of times N as 7 as an example, when the number of charge and discharge cycles is less than N, no self-discharge abnormality determination is performed, and in each charge and discharge cycle, only the charge process data is extracted for self-discharge abnormality battery determination.
In step S102, the charging duration and the initial charging capacity of each battery cell of the battery pack in the charging data in the reference voltage interval are identified, and the actual charging capacity and the reference charging capacity of each battery cell in each charging and discharging cycle are calculated according to the charging duration and/or the initial charging capacity.
It can be understood that the embodiment of the application can calculate the actual charge capacity and the reference charge capacity of each battery cell in each charge-discharge cycle according to the charge duration and the initial charge capacity of each battery cell in the battery pack in the reference voltage interval.
In an embodiment of the present application, identifying a charging duration of each battery cell of a battery pack in charging data in a reference voltage interval includes: acquiring an upper limit voltage and a lower limit voltage of a reference voltage interval; and acquiring a first moment when the upper limit voltage of each battery cell is at the upper limit voltage and a second moment when the lower limit voltage is at the lower limit voltage, and determining the charging time of each battery cell in the reference voltage interval according to the first moment and the second moment.
It should be noted that, due to the step charging strategy in the real vehicle charging process, in the unused voltage interval [ V x ，V y ]Different charging currents I are adopted x Reference voltage interval V rl ，V rh ]The following should be satisfied: v (V) y ≥V rh ＞V rl ≥V x . The reference voltage interval should be within the voltage interval V x ，V y ]The selection is made in the range and the battery units can be charged as much as possible in the charging process to reach the range of the reference voltage interval. In addition, the selection of the reference voltage interval is not unique, and a plurality of reference voltage intervals can be selected for calculation respectively.
It can be understood that the embodiment of the application can acquire the upper limit voltage and the lower limit voltage of the reference voltage interval, record the charging time when each battery cell reaches the lower limit voltage and the upper limit voltage in the reference voltage interval in each charging process, record the charging time as a first time and a second time respectively, and determine the charging time of each battery cell in the reference voltage interval according to the first time and the second time.
In the embodiment of the application, calculating the actual charge capacity and the reference charge capacity of each battery cell in each charge-discharge cycle according to the charge duration and/or the initial charge capacity comprises the following steps: calculating the actual charging capacity of each battery cell in a reference voltage interval according to the charging time length; and calculating the aging coefficient of the charge capacity of each battery cell according to the change of the actual charge capacity of each battery cell in each charge-discharge cycle along with the charge-discharge cycle times, and calculating the reference charge capacity of each charge-discharge cycle according to the aging coefficient and the initial charge capacity of each battery cell.
Wherein the reference charge capacity is the sum of the initial charge capacity and the aging coefficient in a plurality of charge-discharge cycles; the charge capacity increment is the difference between the charge capacity and the reference charge capacity within the selected reference voltage interval for each charge cycle.
It can be understood that, in the embodiment of the present application, the actual charge capacity of each battery cell in the selected reference voltage interval may be calculated according to the charge duration, the aging coefficient of the relative charge capacity of each battery cell in the selected reference voltage interval according to the change of the cycle times is calculated according to the actual charge capacity of each battery cell in each charge-discharge cycle, and the reference charge capacity in each charge-discharge cycle is calculated by the aging coefficient and the initial charge capacity of each battery cell, and the specific calculation method is described in the following embodiments and is not repeated herein. According to the embodiment of the application, the influence of the aging inconsistency of each battery on the charging capacity is considered, and the applicability of identifying the self-discharge abnormal battery cells in the aged battery cells is improved.
In the embodiment of the application, calculating the actual charge capacity of each battery cell in the reference voltage interval according to the charge duration comprises the following steps: and (3) integrating the charging current of each battery cell in the reference voltage interval in time within the charging time length to obtain the actual charging capacity of each battery cell in the reference voltage interval.
The actual charge capacity of each battery cell in the selected reference voltage interval is calculated as follows:
wherein,,for each battery cell in the kth charging cycle to reach the upper limit V of the reference voltage interval rh At the charging time, i=1, 2, …, n total of n battery cells; />For each battery cell in the kth charging cycle reaching the lower limit V of the reference voltage interval rl Charging time at time I x Charging current in a reference voltage interval; />The charge capacity of each battery cell in the k-th charge cycle in the reference voltage interval.
In the embodiment of the application, according to the actual charge capacity of each battery cell in each charge-discharge cycle, the aging coefficient of the charge capacity changing along with the number of charge-discharge cycles is calculated, which comprises the following steps: selecting a charging cycle time window of each charging monomer; according to the target cycle number interval of each charging monomer of the charging cycle number window; calculating the capacity difference between the actual charge capacity and the initial charge capacity of each charge-discharge cycle in the target cycle number interval, fitting the capacity difference of each charge-discharge cycle in the target cycle number interval to obtain a curve of the capacity difference changing along with the charge-discharge cycle number, and determining an aging coefficient according to the curve.
Specifically, the aging coefficient is calculated by: recording charging data selected charging cycle time window W in the times of multiple charging and discharging cycles; for the first W charge cycles of the long period charge data, in cycle interval [1,1+W]Calculating the difference between the reference voltage interval charge capacity and the initial charge capacity, i.e. the relative charge capacity, in each charge cycleCalculating and fitting according to the relative charge capacity obtained in the previous W charge cycles to obtain a function reflecting the change of the relative charge capacity along with the charge cycle timesNumber, i.e. ageing coefficient->In addition, the method of calculation and fitting is not unique, and linear fitting, quadratic fitting, exponential or other polynomial fitting can be adopted.
The calculation method of the reference charge capacity in each charge-discharge cycle is as follows:
wherein,,initial charge capacity for each battery cell within a reference voltage interval in a first charge cycle over a long period of time; />The aging coefficient of each battery cell in the kth charging cycle is set; />Is the reference charge capacity of each battery cell in the kth charge cycle.
In step S103, the capacity increment and the increment change rate are calculated from the actual charge capacity and the reference charge capacity for each charge-discharge cycle, and abnormal cells in which the self-discharge abnormality exists in each cell are identified from the capacity increment and the increment change rate.
It can be understood that the embodiment of the application can calculate the increment of the charge capacity and the increment change rate according to the actual charge capacity and the reference charge capacity in each charge-discharge cycle, judge whether each battery cell has the self-discharge abnormality according to the increment of the charge capacity and the increment change rate in a long period of time, and avoid the erroneous judgment caused by data jump when only adopting the charge process twice.
In an embodiment of the present application, calculating a capacity increment and an increment change rate from an actual charge capacity and a reference charge capacity for each charge-discharge cycle includes: taking the difference value between the actual charge capacity and the reference charge capacity as the capacity increment of each charge-discharge cycle; fitting the capacity increment of each charge-discharge cycle to obtain a curve of the capacity increment changing along with the charge-discharge cycle times, and determining the increment change rate according to the fitting slope of the curve.
It can be understood that in the embodiment of the application, the charge capacity increment in each charge cycle is calculated according to the actual charge capacity and the reference charge capacity, and the capacity increment is fitted to obtain the change rate of the capacity increment along with the change of the cycle times.
Specifically, the process of judging whether the battery monomer has the self-discharge abnormality according to the increment of the charge capacity and the increment change rate in a long time period is as follows: calculating charge capacity delta during each charge cycle The rate of change of the charge capacity increment with the number of cycles is fitted in a linear fashion.
In the embodiment of the application, identifying abnormal battery cells with self-discharge abnormality in each battery cell according to the capacity increment and the increment change rate comprises the following steps: judging whether the capacity increment is larger than an increment threshold value and whether the increment change rate is larger than a change rate threshold value; if the capacity increment is larger than the increment threshold value and the increment change rate is larger than the change rate threshold value, the battery cell is judged to be an abnormal battery cell with self-discharge abnormality.
It can be appreciated that the embodiment of the present application can determine that the battery cell is a self-discharge abnormal cell by determining the values of the capacity increment and the increment change rate if the capacity increment is greater than the increment threshold k1 and the increment change rate is greater than the threshold k 2.
In the embodiment of the application, after identifying the abnormal battery cells with the self-discharge abnormality in each battery cell according to the capacity increment and the increment change rate, the method further comprises the following steps: generating preset reminding information; and sending preset reminding information to a preset terminal so as to carry out self-discharge abnormal reminding according to the preset reminding information.
The preset reminding information can be set to prompt that the battery monomer with abnormal self-discharge exists in the battery monomer, and prompt a user that the power battery has the danger of thermal runaway. The preset terminal can be a central control display screen of the vehicle.
It can be appreciated that after the battery monomer with the self-discharge abnormality is identified, the embodiment of the application can remind the user to timely process the battery monomer, so that the phenomenon of thermal runaway of the power battery is avoided.
In the embodiment of the application, after identifying the abnormal battery cells with the self-discharge abnormality in each battery cell according to the capacity increment and the increment change rate, the method further comprises the following steps: identifying the identity of the abnormal battery cell; and sending the identification to a preset terminal so as to position the abnormal battery cells in the battery pack according to the identification.
It can be understood that after the battery cells with abnormal self-discharge in the battery pack are identified, the embodiment of the application can identify the identification of the abnormal battery cells, so that a user can position the abnormal battery cells in the battery pack according to the identification and replace the abnormal battery cells in time.
The method for identifying abnormal battery cells according to the embodiment of the present application is described below by way of a specific embodiment, as shown in fig. 2, and includes the following steps:
step 1: and extracting a charging process in each charging and discharging cycle based on the operation data of the real vehicle in a long period of time.
The real vehicle operation data refer to voltage curves of each battery cell in the vehicle charging and driving discharging process stored in the cloud, and the battery cells in the operation data are charged and discharged once to be regarded as a charging and discharging cycle. The long period of time is generally considered that the number of charge and discharge cycles is equal to or greater than N, and the range of values adopted here is, but not limited to, n=7, and when the number of charge and discharge cycles is less than N, no self-discharge abnormality judgment is made. In each charge-discharge cycle, only the charge process data is extracted for self-discharge abnormal battery judgment.
Step 2: and for each battery cell, determining the value range of the reference voltage interval according to the charging voltage curve.
Due to the step charging strategy in the real vehicle charging process, the method is thatDifferent voltage intervals V x ，V y ]Different charging currents I are adopted x Reference voltage interval V rl ，V rh ]The following should be satisfied: v (V) y ≥V rh ＞V rl ≥V x . The reference voltage interval should be within the voltage interval V x ，V y ]The selection is made in the range and the battery units can be charged as much as possible in the charging process to reach the range of the reference voltage interval. In addition, the selection of the reference voltage interval is not unique, and a plurality of reference voltage intervals can be selected for calculation respectively.
Step 3: in each charging process, the charging time when each battery cell reaches the lower limit voltage and the upper limit voltage in the reference voltage interval is recorded respectively.
For real vehicle data charged by adopting the step current, only the charging time when each battery cell reaches the upper limit and the lower limit of the reference voltage interval and is the same as the charging current in the voltage interval.
Step 4: and calculating the charging capacity of each battery cell in the selected reference voltage interval according to the charging time of each battery cell.
The charging capacity calculation process of each battery cell in the selected reference voltage interval is as follows:
In the method, in the process of the invention,for each battery cell in the kth charging cycle to reach the upper limit V of the reference voltage interval rh At the charging time, i=1, 2, …, n total of n battery cells; />For each battery cell in the kth charging cycle reaching the lower limit V of the reference voltage interval rl Charging time at time I x Charging current in a reference voltage interval; />The charge capacity of each battery cell in the k-th charge cycle in the reference voltage interval.
Step 5: and selecting a cycle number window, and calculating an aging coefficient of the relative charge capacity in the selected reference voltage interval along with the change of the cycle number according to the charge data in the window of a long time period.
The ageing coefficient is calculated by the following steps: the initial charge capacity of each battery cell in the reference voltage interval in the first charge cycle of recording the long-time period charge data isSelecting a charging cycle time window W; for the first W charge cycles of the long period charge data, in cycle interval [1,1+W]In the above, the difference between the reference voltage interval charging capacity and the initial charging capacity, i.e., the relative charging capacity, is calculated for each charging cycle>Calculating and fitting according to the relative charge capacity obtained in the previous W charge cycles to obtain a function reflecting the change of the relative charge capacity along with the charge cycle times k, namely the aging coefficient +. >In addition, the method of calculation and fitting is not unique, and linear fitting, quadratic fitting, exponential or other polynomial fitting can be adopted.
Step 6: the reference charge capacity in each charge cycle is calculated for each cell over a reference voltage interval from the aging coefficient and the initial charge capacity over a long period of time.
The reference charge capacity calculation method in each charge cycle comprises the following steps:
in the method, in the process of the invention,initial charge capacity for each battery cell within a reference voltage interval in a first charge cycle over a long period of time; />The aging coefficient of each battery cell in the kth charging cycle is set; />Is the reference charge capacity of each battery cell in the kth charge cycle.
Step 7: judging whether each battery cell has self-discharge abnormality according to the increment of the charge capacity and the increment change rate in a long time period.
The process for judging whether the battery monomer has self-discharge abnormality according to the increment of the charge capacity and the increment change rate in a long time period comprises the following steps: calculating charge capacity delta during each charge cycleFitting the change rate of the charge capacity increment along with the change of the cycle times by adopting a linear form; when the increment of the charge capacity is larger than the threshold k1 and the increment change rate is larger than the threshold k2, the battery cell is judged to be a self-discharge abnormal cell.
According to the method for identifying the abnormal battery cell, which is provided by the embodiment of the application, the abnormal battery cell with the self-discharge abnormality can be identified together according to the capacity increment and the increment change rate of the charge-discharge cycle, so that misjudgment caused by data jump in the process of only adopting twice charge is avoided, the applicability of identifying the battery cell self-discharge abnormality is enhanced, the influence of each battery aging inconsistency on the charge capacity is considered, and the applicability of identifying the self-discharge abnormal battery cell in the aged battery cell is improved.
Next, an apparatus for identifying abnormal battery cells according to an embodiment of the present application will be described with reference to the accompanying drawings.
Fig. 3 is a block diagram illustrating an apparatus for identifying abnormal battery cells according to an embodiment of the present application.
As shown in fig. 3, the abnormal cell identification apparatus 10 includes: an acquisition module 100, a calculation module 200 and an identification module 300.
The acquiring module 100 is configured to acquire charging data of multiple charging and discharging cycles of each battery cell in the battery pack; the calculation module 200 is configured to identify a charging duration and an initial charging capacity of each battery cell of the battery pack in the charging data in a reference voltage interval, and calculate an actual charging capacity and a reference charging capacity of each battery cell in each charging and discharging cycle according to the charging duration and/or the initial charging capacity; the identification module 300 is used for calculating a capacity increment and an increment change rate according to the actual charge capacity and the reference charge capacity of each charge-discharge cycle, and identifying abnormal battery cells in which self-discharge abnormality exists in each battery cell according to the capacity increment and the increment change rate.
In an embodiment of the present application, the identification module 300 is further configured to: judging whether the capacity increment is larger than an increment threshold value and whether the increment change rate is larger than a change rate threshold value; if the capacity increment is larger than the increment threshold value and the increment change rate is larger than the change rate threshold value, the battery cell is judged to be an abnormal battery cell with self-discharge abnormality.
In an embodiment of the present application, the identification module 300 is further configured to: taking the difference value between the actual charge capacity and the reference charge capacity as the capacity increment of each charge-discharge cycle; fitting the capacity increment of each charge-discharge cycle to obtain a curve of the capacity increment changing along with the charge-discharge cycle times, and determining the increment change rate according to the fitting slope of the curve.
In an embodiment of the present application, the computing module 200 is further configured to: calculating the actual charging capacity of each battery cell in a reference voltage interval according to the charging time length; and calculating the aging coefficient of the charge capacity of each battery cell according to the change of the actual charge capacity of each battery cell in each charge-discharge cycle along with the charge-discharge cycle times, and calculating the reference charge capacity of each charge-discharge cycle according to the aging coefficient and the initial charge capacity of each battery cell.
In an embodiment of the present application, the computing module 200 is further configured to: and (3) integrating the charging current of each battery cell in the reference voltage interval in time within the charging time length to obtain the actual charging capacity of each battery cell in the reference voltage interval.
In an embodiment of the present application, the computing module 200 is further configured to: selecting a charging cycle time window of each charging monomer; according to the target cycle number interval of each charging monomer of the charging cycle number window; calculating the capacity difference between the actual charge capacity and the initial charge capacity of each charge-discharge cycle in the target cycle number interval, fitting the capacity difference of each charge-discharge cycle in the target cycle number interval to obtain a curve of the capacity difference changing along with the charge-discharge cycle number, and determining an aging coefficient according to the curve.
In an embodiment of the present application, the computing module 200 is further configured to: acquiring an upper limit voltage and a lower limit voltage of a reference voltage interval; and acquiring a first moment when the upper limit voltage of each battery cell is at the upper limit voltage and a second moment when the lower limit voltage is at the lower limit voltage, and determining the charging time of each battery cell in the reference voltage interval according to the first moment and the second moment.
In the embodiment of the present application, the apparatus 10 of the embodiment of the present application further includes: and an extraction module.
The extraction module is used for acquiring charge and discharge data of the battery pack before acquiring charge data of multiple charge and discharge cycles of each battery cell in the battery pack; extracting the actual times of charge and discharge cycles in the charge and discharge data; if the actual times are greater than the preset times, charging data of multiple charging and discharging cycles of each battery cell in the battery pack are obtained, and otherwise, abnormal battery cells are not identified.
In the embodiment of the present application, the apparatus 10 of the embodiment of the present application further includes: and a reminding module.
The reminding module is used for generating preset reminding information after identifying abnormal battery monomers with abnormal self-discharge in each battery monomer according to the capacity increment and the increment change rate; and sending preset reminding information to a preset terminal so as to carry out self-discharge abnormal reminding according to the preset reminding information.
In the embodiment of the present application, the apparatus 10 of the embodiment of the present application further includes: and a transmitting module.
The sending module is used for identifying the identification of the abnormal battery cell after identifying the abnormal battery cell with the self-discharge abnormality in each battery cell according to the capacity increment and the increment change rate; and sending the identification to a preset terminal so as to position the abnormal battery cells in the battery pack according to the identification.
It should be noted that the foregoing explanation of the embodiment of the method for identifying an abnormal battery cell is also applicable to the device for identifying an abnormal battery cell of this embodiment, and will not be repeated here.
According to the device for identifying the abnormal battery cell, which is provided by the embodiment of the application, the abnormal battery cell with the self-discharge abnormality can be identified together according to the capacity increment and the increment change rate of the charge-discharge cycle, so that misjudgment caused by data jump in the process of only adopting twice charge is avoided, the applicability of identifying the battery cell self-discharge abnormality is enhanced, the influence of each battery aging inconsistency on the charge capacity is considered, and the applicability of identifying the self-discharge abnormal battery cell in the aged battery cell is improved.
Fig. 4 is a schematic structural diagram of a server according to an embodiment of the present application. The server may include:
memory 401, processor 402, and a computer program stored on memory 401 and executable on processor 402.
The processor 402 implements the method of identifying abnormal battery cells provided in the above-described embodiment when executing a program.
Further, the server further includes:
a communication interface 403 for communication between the memory 401 and the processor 402.
A memory 401 for storing a computer program executable on the processor 402.
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 memory.
If the memory 401, the processor 402, and the communication interface 403 are implemented independently, the communication interface 403, the memory 401, and the processor 402 may be connected to each other by a bus and perform communication with each other. The bus may be an ISA (Industry Standard Architecture ) bus, a PCI (Peripheral Component, external device interconnect) bus, or EISA (Extended Industry Standard Architecture ) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is shown in fig. 4, but not only one bus or one type of bus.
Alternatively, in a specific implementation, if the memory 401, the processor 402, and the communication interface 403 are integrated on a chip, the memory 401, the processor 402, and the communication interface 403 may perform communication with each other through internal interfaces.
The processor 402 may be a CPU (Central Processing Unit ) or ASIC (Application Specific Integrated Circuit, application specific integrated circuit) or one or more integrated circuits configured to implement embodiments of the present application.
The embodiment of the application also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the method for identifying abnormal battery cells as above.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, for example, two, three, etc., unless specifically defined otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order from that shown or discussed, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable gate arrays, field programmable gate arrays, and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (13)
1. A method for identifying abnormal battery cells, wherein the method is applied to a server, and wherein the method comprises the following steps:
acquiring charging data of multiple charging and discharging cycles of each battery monomer in the battery pack;
the charging time length and the initial charging capacity of each battery cell of the battery pack in a reference voltage interval are identified in the charging data, and the actual charging capacity and the reference charging capacity of each battery cell in each charging and discharging cycle are calculated according to the charging time length and/or the initial charging capacity;
And calculating a capacity increment and an increment change rate according to the actual charge capacity and the reference charge capacity of each charge-discharge cycle, and identifying abnormal battery cells with abnormal self-discharge in each battery cell according to the capacity increment and the increment change rate.
2. The method for identifying an abnormal cell according to claim 1, wherein the identifying an abnormal cell in which a self-discharge abnormality exists in each cell based on the capacity increment and the increment change rate comprises:
judging whether the capacity increment is larger than an increment threshold value and whether the increment change rate is larger than a change rate threshold value;
and if the capacity increment is larger than the increment threshold and the increment change rate is larger than the change rate threshold, judging that the battery cell is an abnormal battery cell with self-discharge abnormality.
3. The method of identifying an abnormal cell according to claim 1, wherein the calculation of the capacity increment and the increment change rate from the actual charge capacity and the reference charge capacity of each charge-discharge cycle includes:
taking the difference value between the actual charge capacity and the reference charge capacity as the capacity increment of each charge-discharge cycle;
Fitting the capacity increment of each charge-discharge cycle to obtain a curve of the capacity increment changing along with the charge-discharge cycle times, and determining the increment change rate according to the fitting slope of the curve.
4. The method according to claim 1, wherein calculating the actual charge capacity and the reference charge capacity of each battery cell at each charge-discharge cycle according to the charge duration and/or the initial charge capacity comprises:
calculating the actual charging capacity of each battery cell in the reference voltage interval according to the charging duration;
and calculating an aging coefficient of the charge capacity of each battery cell according to the change of the actual charge capacity of each battery cell in each charge-discharge cycle along with the charge-discharge cycle times, and calculating the reference charge capacity of each charge-discharge cycle according to the aging coefficient and the initial charge capacity of each battery cell.
5. The method for identifying abnormal cells according to claim 4, wherein calculating the actual charge capacity of each cell in the reference voltage interval according to the charge duration comprises:
and carrying out time integration on the charging current of each battery cell in the reference voltage interval in the charging duration to obtain the actual charging capacity of each battery cell in the reference voltage interval.
6. The method according to claim 4, wherein the calculating the aging coefficient of the charge capacity with the number of charge-discharge cycles based on the actual charge capacity of each of the battery cells at each charge-discharge cycle comprises:
selecting a charging cycle time window of each charging monomer;
according to the charging cycle number window, the target cycle number interval of each charging monomer is obtained;
calculating the capacity difference between the actual charge capacity and the charge initial capacity of each charge-discharge cycle in the target cycle number interval, fitting the capacity difference of each charge-discharge cycle in the target cycle number interval to obtain a curve of the capacity difference changing along with the charge-discharge cycle number, and determining the aging coefficient according to the curve.
7. The method for identifying abnormal battery cells according to claim 1, wherein the identifying the charging duration of each battery cell of the battery pack in the charging data in the reference voltage interval includes:
acquiring an upper limit voltage and a lower limit voltage of the reference voltage interval;
and acquiring a first moment when each battery cell is at the upper limit voltage and a second moment when each battery cell is at the lower limit voltage, and determining the charging time of each battery cell in a reference voltage interval according to the first moment and the second moment.
8. The method for identifying abnormal cells according to claim 1, further comprising, before acquiring charge data of a plurality of charge-discharge cycles of each cell in the battery pack:
acquiring charge and discharge data of a battery pack;
extracting the actual times of charge and discharge cycles in the charge and discharge data;
and if the actual times are greater than the preset times, acquiring charging data of multiple charging and discharging cycles of each battery cell in the battery pack, otherwise, not identifying the abnormal battery cell.
9. The method for identifying an abnormal cell according to claim 1, further comprising, after identifying an abnormal cell in which a self-discharge abnormality exists in the respective cells based on the capacity increment and the increment change rate:
generating preset reminding information;
and sending the preset reminding information to a preset terminal so as to carry out self-discharge abnormal reminding according to the preset reminding information.
10. The method for identifying an abnormal cell according to claim 1, further comprising, after identifying an abnormal cell in which a self-discharge abnormality exists in the respective cells based on the capacity increment and the increment change rate:
Identifying the identity of the abnormal battery cell;
and sending the identification to a preset terminal so as to locate the abnormal battery cells in the battery pack according to the identification.
11. An apparatus for identifying abnormal cells, wherein the apparatus is applied to a server, and wherein the apparatus comprises:
the acquisition module is used for acquiring charging data of multiple charging and discharging cycles of each battery cell in the battery pack;
the calculation module is used for identifying the charging duration and the initial charging capacity of each battery cell of the battery pack in the reference voltage interval in the charging data, and calculating the actual charging capacity and the reference charging capacity of each battery cell in each charging and discharging cycle according to the charging duration and/or the initial charging capacity;
and the identification module is used for calculating a capacity increment and an increment change rate according to the actual charge capacity and the reference charge capacity of each charge-discharge cycle, and identifying abnormal battery cells with self-discharge abnormality in each battery cell according to the capacity increment and the increment change rate.
12. A server, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method of identifying an abnormal cell according to any one of claims 1-10.
13. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor for realizing the method of identifying an abnormal cell according to any one of claims 1 to 10.
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