WO2022001197A1 - 电芯内部短路故障的检测方法、装置、设备和介质 - Google Patents

电芯内部短路故障的检测方法、装置、设备和介质 Download PDF

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WO2022001197A1
WO2022001197A1 PCT/CN2021/081241 CN2021081241W WO2022001197A1 WO 2022001197 A1 WO2022001197 A1 WO 2022001197A1 CN 2021081241 W CN2021081241 W CN 2021081241W WO 2022001197 A1 WO2022001197 A1 WO 2022001197A1
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parameter
cell
cells
circuit fault
target
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PCT/CN2021/081241
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English (en)
French (fr)
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郝浴沧
陈小波
李婷
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宁德时代新能源科技股份有限公司
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Priority to EP21800970.2A priority Critical patent/EP3961235B1/en
Priority to KR1020227023944A priority patent/KR20220114038A/ko
Priority to JP2022542954A priority patent/JP7344393B2/ja
Priority to US17/566,694 priority patent/US11614494B2/en
Publication of WO2022001197A1 publication Critical patent/WO2022001197A1/zh

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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]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • 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]
    • G01R31/3644—Constructional arrangements
    • G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
    • 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
    • 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
    • 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
    • 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
    • G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
    • G01R31/52—Testing for short-circuits, leakage current or ground faults
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/4285—Testing apparatus
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • H01M10/482—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte for several batteries or cells simultaneously or sequentially
    • 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
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

Definitions

  • the present application relates to the field of battery technology, and in particular, to a method, device, equipment and medium for detecting short-circuit faults within a battery cell.
  • the method, device, device, and medium for detecting an internal short-circuit fault of a battery cell provided by the embodiments of the present application can accurately detect a battery cell with an internal short-circuit.
  • a method for detecting an internal short-circuit fault of a battery cell including:
  • the electrical signal values of m cells of the battery pack at multiple times are obtained respectively, wherein the preset condition includes the current nth detection process for the internal short-circuit fault of the cell, m, n is a positive integer;
  • the target cell Under the condition that the second parameter is greater than the preset parameter threshold, it is determined that the target cell has an internal short-circuit fault.
  • the first parameter is calculated.
  • the change rate of the electrical signal of the faulty cell with an internal short-circuit fault will be different from the change rate of the electrical signal of the normal cell, and the fluctuation degree of the electrical signal of the faulty cell will also be different from that of the normal cell.
  • the degree of electrical signal fluctuation of other normal cells Since the first parameter can represent the degree of electrical signal fluctuation, the first parameter of the faulty cell is also different from the first parameter of the normal cell.
  • the dispersion of the first parameter of the faulty cell and the first parameter of the other cells will be larger than that of the normal cell. Therefore, using the second parameter that can characterize the degree of dispersion between the first parameter of each cell and the first parameters of other cells, since the second parameter has a positive correlation with the degree of dispersion, when the second parameter of a certain cell is When the parameter is greater than the preset parameter threshold, the cell with internal short circuit is accurately detected.
  • the preset condition when n is an integer greater than 1, the preset condition further includes: in the first n-1 detection processes for the internal short-circuit fault of the battery cell, the second parameter of the target battery cell is greater than the preset parameter threshold value .
  • whether the battery pack has an internal short-circuit fault can be detected according to the second parameter in the first n detection processes, so that the influence of accidental factors on the accuracy of the internal short-circuit fault can be avoided, and the detection of the internal short-circuit fault of the battery cell can be improved. Accuracy.
  • the preset reference threshold is positively correlated with the number of m cells.
  • the relationship between the total number of cells and the preset reference threshold can be considered, thereby improving the detection accuracy of short-circuit faults inside the cells.
  • the first parameter of the target cell is the standard deviation of electrical signal values of the target cell at multiple times.
  • the size of the standard deviation can accurately reflect the cell numbers of the target electrical cell at multiple times.
  • the degree of fluctuation of the value thereby improving the accuracy of the internal short-circuit fault of the cell.
  • the second parameter is the coefficient of variation
  • the ratio of the target difference to the target standard deviation is calculated, and the ratio is determined as the coefficient of variation of the target cell, wherein the target difference is the difference between the first parameter of the target cell and the average value.
  • the second parameters in different time periods in the charging and discharging process can be unified, so that it is convenient to check whether the target cells in different time periods have internal short-circuit faults
  • the criteria for judging are unified.
  • a device for detecting a short-circuit fault inside a battery cell including:
  • the data acquisition module is used to obtain the electrical signal values of the m cells of the battery pack at multiple times under the preset condition of the battery pack, wherein the preset condition includes the current nth time for the internal short-circuit fault of the cell During the detection process, m and n are positive integers;
  • the first calculation module is used to calculate the first parameter of the target cell by using the electrical signal values of the target cell at multiple times for the target cell of the battery pack, wherein the first parameter is used to characterize the electric power of the target cell. the degree of fluctuation of the signal value;
  • the second calculation module is configured to calculate, for the target cell of the battery pack, a second parameter representing the degree of dispersion between the first parameter of the target cell and the first parameters of other cells, wherein the second parameter and the degree of dispersion are positive Relevant relationship, other cells are the cells other than the target cell among the m cells;
  • the fault detection module is configured to, for the target cell of the battery pack, determine that the target cell has an internal short-circuit fault under the condition that the second parameter is greater than the preset parameter threshold.
  • the first parameter is calculated.
  • the change rate of the electrical signal of the faulty cell with an internal short-circuit fault will be different from the change rate of the electrical signal of the normal cell, and the fluctuation degree of the electrical signal of the faulty cell will also be different from that of the normal cell.
  • the degree of electrical signal fluctuation of other normal cells Since the first parameter can represent the degree of electrical signal fluctuation, the first parameter of the faulty cell is also different from the first parameter of the normal cell.
  • the dispersion of the first parameter of the faulty cell and the first parameter of the other cells will be larger than that of the normal cell. Therefore, using the second parameter that can characterize the degree of dispersion between the first parameter of each cell and the first parameters of other cells, since the second parameter has a positive correlation with the degree of dispersion, when the second parameter of a certain cell is When the parameter is greater than the preset parameter threshold, the cell with internal short circuit is accurately detected.
  • the preset condition further includes: during the first n-1 detections of the internal short-circuit fault of the battery cell under charging and discharging conditions, the coefficient of variation of the target battery cell is all greater than the preset parameter threshold.
  • whether the battery pack has an internal short-circuit fault can be detected according to the second parameter in the first n detection processes, so that the influence of accidental factors on the accuracy of the internal short-circuit fault can be avoided, and the detection of the internal short-circuit fault of the battery cell can be improved. Accuracy.
  • the preset reference threshold is positively correlated with the number of m cells.
  • the relationship between the total number of cells and the preset reference threshold can be considered, thereby improving the detection accuracy of short-circuit faults inside the cells.
  • a device for detecting a short-circuit fault inside a battery cell including: a memory for storing a program; a processor for running the program stored in the memory to execute the first aspect or any one of the first aspects.
  • a method for detecting an internal short-circuit fault of a battery cell is provided by a selected embodiment.
  • the detection device for the internal short-circuit fault of the battery cell in the current n-th detection process for the internal short-circuit fault of the battery cell under the charging and discharging condition, it is possible to Signal value, the first parameter is calculated.
  • the change rate of the electrical signal of the faulty cell with an internal short-circuit fault will be different from the change rate of the electrical signal of the normal cell, and the fluctuation degree of the electrical signal of the faulty cell will also be different from that of the normal cell.
  • the degree of electrical signal fluctuation of other normal cells Since the first parameter can represent the degree of electrical signal fluctuation, the first parameter of the faulty cell is also different from the first parameter of the normal cell.
  • the dispersion of the first parameter of the faulty cell and the first parameter of the other cells will be larger than that of the normal cell. Therefore, using the second parameter that can characterize the degree of dispersion between the first parameter of each cell and the first parameters of other cells, since the second parameter has a positive correlation with the degree of dispersion, when the second parameter of a certain cell is When the parameter is greater than the preset parameter threshold, the cell with internal short circuit is accurately detected.
  • a fourth aspect provides a computer storage medium, where computer program instructions are stored on the computer storage medium, and when the computer program instructions are executed by a processor, the internal battery cells provided by the first aspect or any optional implementation manner of the first aspect are implemented. Short circuit fault detection method.
  • the calculation of the nth a parameter in the current nth detection process for the internal short-circuit fault of the battery cell under the charging and discharging condition, the calculation of the nth a parameter.
  • the change rate of the electrical signal of the faulty cell with an internal short-circuit fault will be different from the change rate of the electrical signal of the normal cell, and the fluctuation degree of the electrical signal of the faulty cell will also be different from that of the normal cell.
  • the degree of electrical signal fluctuation of other normal cells Since the first parameter can represent the degree of electrical signal fluctuation, the first parameter of the faulty cell is also different from the first parameter of the normal cell.
  • the dispersion of the first parameter of the faulty cell and the first parameter of the other cells will be larger than that of the normal cell. Therefore, using the second parameter that can characterize the degree of dispersion between the first parameter of each cell and the first parameters of other cells, since the second parameter has a positive correlation with the degree of dispersion, when the second parameter of a certain cell is When the parameter is greater than the preset parameter threshold, the cell with internal short circuit is accurately detected.
  • FIG. 1 is an exemplary schematic diagram of voltage changes of normal cells and faulty cells over time during the charging process of a battery pack with a total number of internal cells of 30;
  • FIG. 2 is an exemplary schematic diagram of voltage changes of normal cells and faulty cells over time during the charging process of a battery pack with a total number of 192 internal cells;
  • FIG. 3 is a schematic flowchart of a method for detecting an internal short-circuit fault in a battery cell provided by an embodiment of the present application
  • FIG. 4 is a schematic flowchart of an exemplary method for detecting an internal short-circuit fault of a battery cell provided by an embodiment of the present application
  • FIG. 5 is an exemplary simulation schematic diagram of the coefficient of variation of the cells of the battery pack provided by the embodiment of the present application.
  • FIG. 6 is another exemplary simulation schematic diagram of the variation coefficient of the cells of the battery pack provided by the embodiment of the present application.
  • FIG. 7 is a schematic flowchart of an exemplary method for detecting an internal short-circuit fault of a battery cell provided by an embodiment of the present application
  • FIG. 8 is a schematic structural diagram of a device for detecting an internal short-circuit fault of a battery cell provided by an embodiment of the present application.
  • FIG. 9 is a structural diagram of an exemplary hardware architecture of a device for detecting a short-circuit fault inside a cell in an embodiment of the present application.
  • Embodiments of the present application provide a method, device, device, and medium for detecting an internal short-circuit fault of a battery cell, which can be applied to an application scenario of detecting an internal short-circuit fault of a battery cell.
  • the specific application scenario of internal short-circuit fault detection for cells in a stationary battery or the specific application scenario of internal short-circuit fault detection for cells in a charging state, and for example The specific application scenario of the internal short-circuit fault detection of the cells in the state of the battery.
  • the battery pack in the embodiment of the present application may be a battery pack in an energy storage device, or may be a battery pack in an electric vehicle.
  • Internal short circuit mainly refers to the short circuit caused by physical contact inside the cell.
  • the internal short circuit fault is not discovered in time, it may cause a thermal runaway accident such as a sudden rise in battery temperature, smoke, fire or even explosion due to the internal short circuit, which will seriously affect the safety of the battery and the service life of the battery.
  • the battery has an internal short-circuit failure, it will also seriously affect the market's acceptance of the electric vehicle.
  • FIG. 1 is an exemplary schematic diagram of voltage changes of normal cells and faulty cells over time during charging of a battery pack with a total number of 30 internal cells.
  • FIG. 2 is an exemplary schematic diagram of voltage changes of normal cells and faulty cells over time during the charging process of a battery pack with a total number of 192 internal cells.
  • the embodiments of the present application provide a detection solution for an internal short-circuit fault of a battery cell.
  • FIG. 3 is a schematic flowchart of a method for detecting an internal short-circuit fault of a battery cell according to an embodiment of the present application.
  • the method 300 for detecting an internal short-circuit fault of a battery cell in this embodiment may include the following steps S310 to S340 .
  • the battery pack may be a high-voltage battery pack, a low-voltage battery, a battery module, or a battery device including m cells, where m is a positive integer.
  • the embodiments of the present application do not limit the specific form of the battery pack.
  • the preset conditions include currently being in the nth detection process for the internal short-circuit fault of the battery cell, where n is a positive integer. That is to say, before the battery leaves the factory, or during the process of the battery leaving the factory and being put into use, multiple internal short-circuit fault detections can be performed on the battery pack.
  • the fault detection results of the first n-1 detection processes may be ignored, and the detection results of the nth detection process may be used to confirm whether the target cell has an internal short-circuit fault.
  • the preset conditions further include: during the first n-1 detections for the internal short-circuit fault of the battery cell, the second parameter of the target battery cell is all greater than the preset parameter threshold, where n is an integer greater than 1. That is to say, in the first n detection processes, a second parameter needs to be calculated in each detection process, and the second parameter calculated in each detection process needs to be larger than the preset parameter threshold.
  • n in the embodiment of the present application may represent a relative number, and is not limited to the nth time since the fault detection of the battery pack is started.
  • the number of detections can be reset to 0 every preset time interval. , or the number of detections may be reset to 0 when the second parameter is less than the preset parameter threshold in a certain detection process.
  • the n-time fault detection in the embodiment of the present application may be the fault detection when the battery pack is in a static condition, a charging condition, and a discharging condition.
  • the preset condition further includes: the battery pack is under a target charge-discharge condition. That is to say, the current detection can be the nth fault detection process when the battery is in a charging state or a discharging state.
  • the solution of judging the internal short-circuit fault by the voltage difference is not only easy to cause misdiagnosis, but also can only be effectively identified when the internal short-circuit is serious, which greatly shortens the fault repair time, and this solution is only suitable for the specific detection of the battery under static conditions.
  • the internal short-circuit detection requirements in complex charging and discharging conditions cannot be met.
  • the detection method provided by the embodiment of the present application can only detect the internal short-circuit fault of the battery cell regardless of whether the battery pack is in the static condition, the charging condition or the discharging condition, which improves the versatility of the detection method.
  • the electrical signal value is the value of the electrical signal with difference between the normal cell and the faulty cell.
  • it may be a voltage value or a current value.
  • the following parts of the embodiments of the present application will mainly take voltage values as an example for specific explanations.
  • electrical signal values at p times may be obtained. That is to say, for the i-th time in the p time points, the voltage values of m cells need to be obtained respectively.
  • p is an integer greater than 1
  • i is any positive integer not greater than p.
  • S320 for the target cell of the battery pack, use the electrical signal values of the target cell at multiple times to calculate the first parameter of the target cell.
  • the target cell refers to the cell in the battery pack that needs to be diagnosed with internal short-circuit faults.
  • m cells may be sequentially used as target cells for fault detection. That is to say, for any one of the cells, such as the jth cell, after the internal short-circuit fault detection is completed, the next cell, that is, the j+1th cell, can be used as the target cell, and the It performs internal short circuit fault detection.
  • j+1 is a positive integer not less than m.
  • the first parameter is used to characterize the degree of fluctuation of the electrical signal value of the target cell.
  • the first parameter is small. Conversely, if the difference between the p electrical signal values of the target cell is large, that is, the fluctuation degree of the p electrical signal values of the target cell is large, the first parameter is large.
  • the first parameter may be the standard deviation, average difference, or variance of the cell values at m times, which is not limited.
  • the standard deviation ⁇ j of the target cell satisfies the formula (1):
  • the target cell is the jth cell among the m cells, and j is any positive integer less than or equal to m.
  • V ij is the voltage value of the jth cell at the ith moment, and i is any positive integer less than or equal to p.
  • the second parameter of the target cell is used to represent the degree of dispersion between the first parameter of the target cell and the first parameters of other cells.
  • the other cells are cells other than the target cell among the m cells.
  • the second parameter may be the standard deviation or the coefficient of variation of the first parameter of the m cells.
  • a dimensionless coefficient of variation may be selected for the second parameters.
  • the calculation method of the first parameter of the other cells is the same as the calculation method of the first parameter of the target cell, and details are not described herein again.
  • the second parameter is positively correlated with the degree of dispersion. That is to say, the larger the degree of dispersion between the first parameter of the target cell and the first parameters of the other m ⁇ 1 cells is, the larger the second parameter of the target cell is.
  • the difference between the change curves of normal cells is small, and they are mainly concentrated in one area. For the target cell, the closer its variation curve is to the gathering area of the normal cell variation curve, the smaller the second parameter; on the other hand, if its variation curve is farther from the gathering area of the normal battery variation curve.
  • the target battery if the second parameter of the target cell is the coefficient of variation, the target battery
  • ⁇ j is the first parameter of the target cell
  • ⁇ mean is the average value of the first parameters of m cells
  • ⁇ ⁇ is the target standard deviation
  • FIG. 4 is a schematic flowchart of an exemplary method for detecting an internal short-circuit fault of a battery cell provided by an embodiment of the present application.
  • a specific implementation of S330 may include steps S331 and S332.
  • the target standard deviation ⁇ ⁇ is used to characterize the dispersion degree of the first parameter of m cells, and the calculation formula of the target standard deviation ⁇ ⁇ is formula (3):
  • the target difference d is the difference between the first parameter ⁇ j of the target cell and the average value ⁇ mean .
  • the preset parameter threshold is positively correlated with the number of m cells.
  • the second parameter as the coefficient of variation as an example to explain the preset parameter threshold in detail.
  • the applicant sets the preset parameter thresholds in a step-by-step manner according to the cell data. If the total number of cells in the battery pack is less than 50, the preset parameter threshold can be set to 4. That is, if the variation coefficient B j of the target cell is greater than 4, the target cell is determined to be a faulty cell. If the total number of cells in the battery pack is between 50 and 100, the preset parameter threshold can be set to 5. That is, if the variation coefficient B j of the target cell is greater than 5, the target cell is determined to be a faulty cell. If the total number of cells in the battery pack is between 100 and 150, the preset parameter threshold can be set to 6.
  • the target cell is determined to be a faulty cell. If the total number of cells in the battery pack is greater than 150, the preset parameter threshold can be set to 10. That is, if the variation coefficient B j of the target cell is greater than 10, the target cell is determined to be a faulty cell.
  • FIG. 5 an exemplary simulation result of the coefficient of variation of the cells of the battery pack in the embodiment of the present application may be shown in FIG. 5 .
  • the coefficient of variation B of faulty cells fluctuates between 4 and 6 most of the time, while the coefficient of variation B of normal cells basically does not exceed 2, that is to say, the coefficient of variation B of normal cells is 0 fluctuates between -2.
  • an exemplary simulation result of the coefficient of variation of the cells of the battery pack in the embodiment of the present application may be as shown in FIG. 6 .
  • the coefficient of variation B of faulty cells fluctuates between 10-12 in most cases, while the maximum value of the coefficient of variation B of normal cells may be slightly larger than 4, and the coefficient of variation B of normal cells is basically Fluctuates between 0-4.
  • the target battery cell in the current n-th detection process for an internal short-circuit fault of a battery cell under the charging and discharging conditions, can be detected at multiple times according to the target battery cell
  • the electrical signal value of calculates the first parameter. For m cells belonging to the same battery pack, the change rate of the electrical signal of the faulty cell with an internal short-circuit fault will be different from the change rate of the electrical signal of the normal cell, and the fluctuation degree of the electrical signal of the faulty cell will also be different from that of the normal cell. The degree of electrical signal fluctuation of other normal cells.
  • the first parameter can represent the degree of electrical signal fluctuation
  • the first parameter of the faulty cell is also different from the first parameter of the normal cell.
  • the dispersion of the first parameter of the faulty cell and the first parameter of the other cells will be larger than that of the normal cell. Therefore, using the second parameter that can characterize the degree of dispersion between the first parameter of each cell and the first parameters of other cells, since the second parameter has a positive correlation with the degree of dispersion, when the When the second parameter is greater than the preset parameter threshold, the battery cell with an internal short circuit is accurately detected.
  • FIG. 7 is a schematic flowchart of an exemplary method for detecting an internal short-circuit fault of a battery cell provided by an embodiment of the present application.
  • the method 700 for detecting an internal short-circuit fault of a cell includes S710 to S790.
  • S710 collect voltage data, and establish a t ⁇ m voltage matrix. Specifically, during the charging process of the battery pack, the voltage data of all m cells of the battery pack in the total t seconds of the whole process are collected, and a t ⁇ m voltage matrix is established according to the voltage data of the m cells for t seconds.
  • the t ⁇ m voltage matrix is specifically expressed as:
  • the i-th row data in the t ⁇ m voltage matrix is the respective voltage data of the m cells at the i-th second
  • the j-th column data in the voltage matrix is the voltage data of the j-th cell within t seconds.
  • t in this embodiment is equal to 96 seconds.
  • S730 Intercept the voltage data of m cells from the nth second to the n+p-1th second from the t ⁇ m voltage matrix, and establish a p ⁇ m voltage matrix in the nth detection process.
  • the p ⁇ m voltage matrix is specifically expressed as:
  • the standard deviation of m cells can be expressed as a 1 ⁇ m standard deviation matrix:
  • the embodiment of the present application uses the first n seconds, for example, 96 seconds of voltage data from the occurrence of the internal short circuit, to determine whether the battery cell has an internal short circuit fault.
  • n seconds for example, 96 seconds of voltage data from the occurrence of the internal short circuit
  • FIG. 8 is a schematic structural diagram of an apparatus for detecting an internal short-circuit fault of a battery cell provided by an embodiment of the present application.
  • the device 800 for detecting a short-circuit fault inside a cell includes a data acquisition module 810 , a first calculation module 820 , a second calculation module 830 and a fault detection module 840 .
  • the data acquisition module 810 is configured to acquire the electrical signal values of the m cells of the battery pack at multiple times when the battery pack is in a preset condition.
  • the preset condition includes that the current is in the nth detection process for the internal short-circuit fault of the battery cell, and m and n are positive integers.
  • the first calculation module 820 is configured to calculate the first parameter of the target cell by using the electrical signal values of the target cell at multiple times for the target cell of the battery pack.
  • the first parameter is used to characterize the degree of fluctuation of the electrical signal value of the target cell.
  • the second calculation module 830 is configured to calculate, for the target cell of the battery pack, a second parameter representing the degree of dispersion between the first parameter of the target cell and the first parameters of other cells.
  • the second parameter is positively correlated with the degree of dispersion
  • the other cells are the cells other than the target cell among the m cells.
  • the fault detection module 840 is configured to, for the target cell of the battery pack, determine that the target cell has an internal short-circuit fault under the condition that the second parameter is greater than the preset parameter threshold.
  • the preset condition when n is an integer greater than 1, the preset condition further includes: in the first n-1 detection processes for the internal short-circuit fault of the battery cell, the second parameter of the target battery cell is greater than the preset parameter threshold value .
  • the preset reference threshold is positively correlated with the number of m cells.
  • the first parameter of the target cell is a standard deviation of electrical signal values of the target cell at multiple times.
  • the second parameter is the coefficient of variation
  • the second computing module 830 specifically includes a first computing unit and a second computing unit.
  • the first calculation unit is configured to calculate a target standard deviation representing the degree of dispersion of the first parameters of the m cells, and calculate the average value of the first parameters of the m cells.
  • the second calculation unit is configured to calculate the ratio of the target difference to the target standard deviation, and determine the ratio as the variation coefficient of the target cell.
  • the target difference is the difference between the first parameter of the target cell and the average value.
  • the device for detecting an internal short-circuit fault of a battery cell in the embodiment of the present application, during the current n-th detection process for an internal short-circuit fault of a battery cell under the charging and discharging conditions, it can The electrical signal value of , calculates the first parameter.
  • the change rate of the electrical signal of the faulty cell with an internal short-circuit fault will be different from the change rate of the electrical signal of the normal cell, and the fluctuation degree of the electrical signal of the faulty cell will also be different from that of the normal cell.
  • the degree of electrical signal fluctuation of other normal cells Since the first parameter can represent the degree of electrical signal fluctuation, the first parameter of the faulty cell is also different from the first parameter of the normal cell.
  • the dispersion of the first parameter of the faulty cell and the first parameter of the other cells will be larger than that of the normal cell. Therefore, using the second parameter that can characterize the degree of dispersion between the first parameter of each cell and the first parameters of other cells, since the second parameter has a positive correlation with the degree of dispersion, when the When the second parameter is greater than the preset parameter threshold, the battery cell with an internal short circuit is accurately detected.
  • FIG. 9 shows a schematic diagram of a hardware structure of a device for detecting a short-circuit fault inside a cell provided by an embodiment of the present application.
  • the device for detecting a short circuit fault inside a cell may include a processor 901 and a memory 902 storing computer program instructions.
  • the above-mentioned processor 901 may include a central processing unit (Central Processing Unit, CPU), or a specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application .
  • CPU Central Processing Unit
  • ASIC Application Specific Integrated Circuit
  • Memory 902 may include mass storage for data or instructions.
  • memory 902 may include a Hard Disk Drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a Universal Serial Bus (USB) drive or two or more A combination of more than one of the above.
  • HDD Hard Disk Drive
  • floppy disk drive a flash memory
  • optical disk a magneto-optical disk
  • magnetic tape magnetic tape
  • USB Universal Serial Bus
  • USB Universal Serial Bus
  • memory 902 may include removable or non-removable (or fixed) media, or memory 902 is non-volatile solid-state memory.
  • the memory 902 may be internal or external to the detection device for short circuit failures inside the cells.
  • memory 902 may be a read only memory (ROM).
  • the ROM may be a mask programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory or both A combination of one or more of the above.
  • Memory 902 may include read only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical/tangible memory storage devices.
  • ROM read only memory
  • RAM random access memory
  • magnetic disk storage media devices typically, magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical/tangible memory storage devices.
  • a memory typically, includes one or more tangible (non-transitory) computer-readable storage media (eg, memory devices) encoded with software including computer-executable instructions, and when the software is executed (eg, by a or multiple processors), it is operable to perform the operations described with reference to a method according to an aspect of the present disclosure.
  • the processor 901 reads and executes the computer program instructions stored in the memory 902 to implement the methods in the embodiments shown in Figs. The technical effects are not repeated here for the sake of brevity.
  • the detection device for short-circuit fault inside the cell may further include a communication interface 903 and a bus 910 .
  • the processor 901 , the memory 902 , and the communication interface 903 are connected through the bus 910 and communicate with each other.
  • the communication interface 903 is mainly used to implement communication between modules, apparatuses, units and/or devices in the embodiments of the present application.
  • the bus 910 includes hardware, software, or both, coupling the components of the online data flow metering device to each other.
  • the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Super Transport (Hyper Transport, HT) interconnect, Industry Standard Architecture (ISA) bus, Infiniband interconnect, Low Pin Count (LPC) bus, Memory bus, Micro Channel Architecture (MCA) bus, Peripheral Component Interconnect Connectivity (PCI) bus, PCI-Express (PCI-X) bus, Serial Advanced Technology Attachment (SATA) bus, Video Electronics Standards Association Local (VLB) bus or other suitable bus or two or more of these combination.
  • Bus 910 may include one or more buses, where appropriate. Although embodiments of this application describe and illustrate a particular bus, this application contemplates any suitable bus or interconnect.
  • the device for detecting an internal short-circuit fault in a cell can implement the method for detecting an internal short-circuit fault in a cell in the embodiments of the present application, thereby implementing the method and device for detecting an internal short-circuit fault in a cell described in conjunction with FIGS. 1 to 8 .
  • the embodiment of the present application may provide a computer storage medium for implementation.
  • Computer program instructions are stored on the computer storage medium; when the computer program instructions are executed by the processor, any method for detecting a short-circuit fault inside a battery cell in the foregoing embodiments is implemented.
  • the functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof.
  • it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), suitable firmware, a plug-in, a function card, and the like.
  • ASIC application specific integrated circuit
  • elements of the present application are programs or code segments used to perform the required tasks.
  • the program or code segments may be stored in a machine-readable medium or transmitted over a transmission medium or communication link by a data signal carried in a carrier wave.
  • a "machine-readable medium” may include any medium that can store or transmit information.
  • machine-readable media examples include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, etc. Wait.
  • the code segments may be downloaded via a computer network such as the Internet, an intranet, or the like.
  • processors may be, but are not limited to, general purpose processors, special purpose processors, application specific processors, or field programmable logic circuits. It will also be understood that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can also be implemented by special purpose hardware for performing the specified functions or actions, or by special purpose hardware and/or A combination of computer instructions is implemented.

Abstract

一种电芯内部短路故障的检测方法、装置、设备和介质，涉及电池技术领域。该方法包括：在电池组处于预设条件下，分别获取电池组的m个电芯在多个时刻的电信号值（S310），其中预设条件包括当前处于针对电芯内部短路故障的第n次检测过程中；针对电池组的目标电芯，执行如下步骤：利用目标电芯在多个时刻的电信号值，计算目标电芯的第一参数（S320）；计算表征目标电芯的第一参数与其他电芯的第一参数之间离散程度的第二参数（S330）；在第二参数大于预设参数阈值的条件下，确定目标电芯发生内部短路故障（S340）。电芯内部短路故障的检测方法、装置、设备和介质，可以准确的对发生内部短路的电芯进行检测。

Description

电芯内部短路故障的检测方法、装置、设备和介质
相关申请的交叉引用
本申请要求享有于2020年06月30日提交的名称为“电芯内部短路故障的检测方法、装置、设备和介质”的中国专利申请202010616755.X的优先权，该申请的全部内容通过引用并入本文中。
技术领域
本申请涉及电池技术领域，特别是涉及电芯内部短路故障的检测方法、装置、设备和介质。
背景技术
随着新能源的发展，越来越多的领域采用新能源作为动力。由于具有能量密度高、可循环充电、安全环保等优点，电池组被广泛应用于新能源汽车、消费电子、储能系统等领域中。
然而近年来，随着电池组的推广应用，因电芯内部短路导致的事故时有发生，例如因电池温度骤升、冒烟、起火甚至爆炸的热失控事故，严重影响了市场对电池组的接受程度。
然而，电芯从发生内部短路到最终发生安全事故需要经历数小时的时间。因此在这几小时内如何尽早地检测到内部短路，对于电池组的安全至关重要。
发明内容
本申请实施例提供的电芯内部短路故障的检测方法、装置、设备和 介质，可以准确的对发生内部短路的电芯进行检测。
第一方面，提供一种电芯内部短路故障的检测方法，包括：
在电池组处于预设条件下，分别获取电池组的m个电芯在多个时刻的电信号值，其中预设条件包括当前处于针对电芯内部短路故障的第n次检测过程中，m、n为正整数；
针对电池组的目标电芯，执行如下步骤：
利用目标电芯在多个时刻的电信号值，计算目标电芯的第一参数，其中，第一参数用于表征目标电芯的电信号值的波动程度；
计算表征目标电芯的第一参数与其他电芯的第一参数之间离散程度的第二参数，其中，其他电芯为m个电芯中除目标电芯以外的电芯，第二参数与离散程度呈正相关关系；
在第二参数大于预设参数阈值的条件下，确定目标电芯发生内部短路故障。
根据本申请实施例中的电芯内部短路故障的检测方法，在当前处于针对充放电工况下的电芯内部短路故障的第n次检测过程中，可以根据目标电芯在多个时刻的电信号值，计算第一参数。对于属于同一电池组的m个电芯，发生内部短路故障的故障电芯的电信号变化速率会不同于正常电芯的电信号变化速率，相应地故障电芯的电信号波动程度也会不同于其他正常电芯的电信号波动程度。由于第一参数能够表征电信号波动程度，故障电芯的第一参数也不同于正常电芯的第一参数。当电池组的m个电芯中存在故障电芯时，故障电芯的第一参数与其他电芯的第一参数的离散度会大于正常电芯。因此，利用可以表征每一电芯的第一参数与其他电芯的第一参数之间的离散程度的第二参数，由于第二参数与离散程度呈正相关关系，当某一电芯的第二参数大于预设参数阈值时，准确的对发生内部短路的电芯进行了检测。
在一些实施方式中，当n为大于1的整数时，预设条件还包括：针对电芯内部短路故障的前n-1次检测过程中，目标电芯的第二参数均大于预设参数阈值。
在本实施方式中，可以根据前n次检测过程中的第二参数检测电池 组是否发生内部短路故障，从而能够避免偶然因素对内部短路故障准确性的影响，提高了电芯内部短路故障的检测准确度。
在一些实施方式中，预设参考阈值与m个电芯的数量呈正相关关系。
在本实施方式中，可以考虑到电芯的总数与预设参考阈值之间的关系，从而提高了电芯内部短路故障的检测准确度。
在一些实施方式中，目标电芯的第一参数为目标电芯在多个时刻的电信号值的标准差。
在本实施方式中，通过将目标电芯在多个时刻的电信号值的标准差作为目标电芯的第一参数，可以通过标准差的大小来准确反映目标电学的多个时刻的电芯号值的波动程度，进而提高电芯内部短路故障的准确性。
在一些实施方式中，第二参数为变异系数，
计算表征目标电芯的第一参数与其他电芯的第一参数之间离散程度的第二参数，具体包括：
计算表征m个电芯的第一参数的离散程度的目标标准差，以及计算m个电芯的第一参数的平均值；
计算目标差值与目标标准差的比值，并将比值确定为目标电芯的变异系数，其中，目标差值为目标电芯的第一参数与平均值的差值。
在本实施方式中，通过将无量纲的变异系数作为第二参数，可以对充放电过程中不同时间段的第二参数进行统一，进而便于通过对不同时间段的目标电芯是否存在内部短路故障的判别标准进行统一。
第二方面，提供一种电芯内部短路故障的检测装置，包括：
数据获取模块，用于在电池组处于预设条件下，分别获取电池组的m个电芯在多个时刻的电信号值，其中预设条件包括当前处于针对电芯内部短路故障的第n次检测过程中，m、n为正整数；
第一计算模块，用于针对电池组的目标电芯，利用目标电芯在多个时刻的电信号值，计算目标电芯的第一参数，其中，第一参数用于表征目标电芯的电信号值的波动程度；
第二计算模块，用于针对电池组的目标电芯，计算表征目标电芯的 第一参数与其他电芯的第一参数之间离散程度的第二参数，其中，第二参数与离散程度呈正相关关系，其他电芯为m个电芯中除目标电芯以外的电芯；
故障检测模块，用于针对电池组的目标电芯，在第二参数大于预设参数阈值的条件下，确定目标电芯发生内部短路故障。
根据本申请实施例中的电芯内部短路故障的检测装置，在当前处于针对充放电工况下的电芯内部短路故障的第n次检测过程中，可以根据目标电芯在多个时刻的电信号值，计算第一参数。对于属于同一电池组的m个电芯，发生内部短路故障的故障电芯的电信号变化速率会不同于正常电芯的电信号变化速率，相应地故障电芯的电信号波动程度也会不同于其他正常电芯的电信号波动程度。由于第一参数能够表征电信号波动程度，故障电芯的第一参数也不同于正常电芯的第一参数。当电池组的m个电芯中存在故障电芯时，故障电芯的第一参数与其他电芯的第一参数的离散度会大于正常电芯。因此，利用可以表征每一电芯的第一参数与其他电芯的第一参数之间的离散程度的第二参数，由于第二参数与离散程度呈正相关关系，当某一电芯的第二参数大于预设参数阈值时，准确的对发生内部短路的电芯进行了检测。
在一些实施方式中，当n为大于1的整数时，预设条件还包括：针对充放电工况下的电芯内部短路故障的前n-1次检测过程中，目标电芯的变异系数均大于预设参数阈值。
在本实施方式中，可以根据前n次检测过程中的第二参数检测电池组是否发生内部短路故障，从而能够避免偶然因素对内部短路故障准确性的影响，提高了电芯内部短路故障的检测准确度。
在一些实施方式中，预设参考阈值与m个电芯的数量呈正相关关系。
在本实施方式中，可以考虑到电芯的总数与预设参考阈值之间的关系，从而提高了电芯内部短路故障的检测准确度。
第三方面，提供一种电芯内部短路故障的检测设备，包括：存储器，用于存储程序；处理器，用于运行存储器中存储的程序，以执行第一 方面或第一方面的任一可选的实施方式提供的电芯内部短路故障的检测方法。
根据本申请实施例中的电芯内部短路故障的检测设备，在当前处于针对充放电工况下的电芯内部短路故障的第n次检测过程中，可以根据目标电芯在多个时刻的电信号值，计算第一参数。对于属于同一电池组的m个电芯，发生内部短路故障的故障电芯的电信号变化速率会不同于正常电芯的电信号变化速率，相应地故障电芯的电信号波动程度也会不同于其他正常电芯的电信号波动程度。由于第一参数能够表征电信号波动程度，故障电芯的第一参数也不同于正常电芯的第一参数。当电池组的m个电芯中存在故障电芯时，故障电芯的第一参数与其他电芯的第一参数的离散度会大于正常电芯。因此，利用可以表征每一电芯的第一参数与其他电芯的第一参数之间的离散程度的第二参数，由于第二参数与离散程度呈正相关关系，当某一电芯的第二参数大于预设参数阈值时，准确的对发生内部短路的电芯进行了检测。
第四方面，提供一种计算机存储介质，计算机存储介质上存储有计算机程序指令，计算机程序指令被处理器执行时实现第一方面或第一方面的任一可选的实施方式提供的电芯内部短路故障的检测方法。
根据本申请实施例中的计算机存储介质，在当前处于针对充放电工况下的电芯内部短路故障的第n次检测过程中，可以根据目标电芯在多个时刻的电信号值，计算第一参数。对于属于同一电池组的m个电芯，发生内部短路故障的故障电芯的电信号变化速率会不同于正常电芯的电信号变化速率，相应地故障电芯的电信号波动程度也会不同于其他正常电芯的电信号波动程度。由于第一参数能够表征电信号波动程度，故障电芯的第一参数也不同于正常电芯的第一参数。当电池组的m个电芯中存在故障电芯时，故障电芯的第一参数与其他电芯的第一参数的离散度会大于正常电芯。因此，利用可以表征每一电芯的第一参数与其他电芯的第一参数之间的离散程度的第二参数，由于第二参数与离散程度呈正相关关系，当某一电芯的第二参数大于预设参数阈值时，准确的对发生内部短路的电芯进行了检测。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对本申请实施例中所需要使用的附图作简单地介绍，显而易见地，下面所描述的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据附图获得其他的附图。
图1是一种示例性的在内部电芯总数为30的电池组的充电过程中正常电芯和故障电芯的电压随时间变化的示意图；
图2是一种示例性的在内部电芯总数为192的电池组的充电过程中正常电芯和故障电芯的电压随时间变化的示意图；
图3是本申请实施例提供的一种电芯内部短路故障的检测方法的示意流程图；
图4是本申请实施例提供的一种示例性地电芯内部短路故障的检测方法的示意流程图；
图5是本申请实施例提供的一种示例性的对电池组的电芯的变异系数的仿真示意图；
图6是本申请实施例提供的另一种示例性的对电池组的电芯的变异系数的仿真示意图；
图7是本申请实施例提供了一种示例性的电芯内部短路故障的检测方法的示意流程图；
图8是本申请实施例提供的电芯内部短路故障的检测装置的结构示意图；
图9是本申请实施例中电芯内部短路故障的检测设备的示例性硬件架构的结构图；
在附图中，附图并未按照实际的比例绘制。
具体实施方式
下面结合附图和实施例对本申请的实施方式作进一步详细描述。以下实施例的详细描述和附图用于示例性地说明本申请的原理，但不能用来限制本申请的范围，即本申请不限于所描述的实施例。
在本申请的描述中，需要说明的是，除非另有说明，“多个”的含义是两个以上；术语“上”、“下”、“左”、“右”、“内”、“外”等指示的方位或位置关系仅是为了便于描述本申请和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本申请的限制。此外，术语“第一”、“第二”、“第三”等仅用于描述目的，而不能理解为指示或暗示相对重要性。
下述描述中出现的方位词均为图中示出的方向，并不是对本申请的具体结构进行限定。在本申请的描述中，还需要说明的是，除非另有明确的规定和限定，术语“安装”、“相连”、“连接”应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或一体地连接；可以是直接相连，也可以通过中间媒介间接相连。对于本领域的普通技术人员而言，可视具体情况理解上述术语在本申请中的具体含义。
下面将详细描述本申请的各个方面的特征和示例性实施例，为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细描述。应理解，此处所描述的具体实施例仅被配置为解释本申请，并不被配置为限定本申请。对于本领域技术人员来说，本申请可以在不需要这些具体细节中的一些细节的情况下实施。下面对实施例的描述仅仅是为了通过示出本申请的示例来提供对本申请更好的理解。
需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
本申请实施例提供一种电芯内部短路故障的检测方法、装置、设 备和介质，可以应用于对电池的电芯进行内部短路故障检测的应用场景中。例如，对处于静置状态的电池内的电芯进行内部短路故障检测的具体应用场景，又例如对处于充电状态的电池内的电芯进行内部短路故障检测的具体应用场景，再例如对处于放电状态的电池内的电芯进行内部短路故障检测的具体应用场景。示例性地，本申请实施例中的电池组可以是储能装置中的电池组，或者可以是电动车辆内的电池组。
为了更好的理解本申请，本申请实施例对内部短路等概念作具体解释说明。
内部短路主要是指电芯内部发生物理接触而产生的短路。例如，因为铜箔与铝箔的毛刺穿破隔膜，或是锂原子的树枝状结晶穿破膈膜所造成短路等造成的内部短路。由于这些细小的针状金属很细有一定的电阻值，因此，短路电流不见得会很大。但是如果内部短路故障没有被及时发现，将有可能因内部短路导致电池温度骤升、冒烟、起火甚至爆炸的热失控事故，严重影响电池安全性、电池使用寿命。对于安装了电池的电动汽车，如果电池发生内部短路故障，还将严重影响市场对该电动汽车的接受程度。
因此，需要一种能够检测出电芯内部短路故障的检测方案。
申请人从大量试验数据和仿真结果看出，对于发生内部短路故障的电芯，其电压变化趋势会与正常电芯电压存在差异。例如，图1是一种示例性的在内部电芯总数为30的电池组的充电过程中正常电芯和故障电芯的电压随时间变化的示意图。图2是一种示例性的在内部电芯总数为192的电池组的充电过程中正常电芯和故障电芯的电压随时间变化的示意图。
通过图1和图2可知，无论电池组内部电芯的多少，对于发生内部短路故障的故障电芯来说，在充电过程中，在发生热失控之前的一段时间内，其电压仍然保持上升状态，但上升程度和正常电芯电压存在差异。
针对上述发现，本申请实施例提供了一种电芯内部短路故障的检测方案。
为了更好的理解本申请，下面将结合附图，详细描述根据本申请 实施例的电芯内部短路故障的检测方法、装置、设备和介质，应注意，这些实施例并不用来限制本申请公开的范围。
图3是本申请实施例提供的一种电芯内部短路故障的检测方法的示意流程图。如图3所示，本实施例中的电芯内部短路故障的检测方法300可以包括以下步骤S310至S340。
S310，在电池组处于预设条件下，分别获取电池组的m个电芯在多个时刻的电信号值。
首先，针对本申请实施例中的电池组，电池组可以是高压电池包、低压蓄电池、电池模组等包括m个电芯的电池装置，其中，m为正整数。本申请实施例对电池组的具体形式不作限定。
其次，针对预设条件，预设条件包括当前处于针对电芯内部短路故障的第n次检测过程中，其中，n为正整数。也就是说，在电池出厂前、或者电池出厂并投入使用的过程中，可以对电池组进行多次内部短路故障检测。
在一些实施例中，可以不用考虑前n-1次检测过程的故障检测结果，利用第n次检测过程的检测结果确认目标电芯是否发生内部短路故障。
在另一些实施例中，为了避免偶然因素对内部短路故障准确性的影响，预设条件还包括：针对电芯内部短路故障的前n-1次检测过程中，目标电芯的第二参数均大于预设参数阈值，其中n为大于1的整数。也就是说，在前n次检测过程中，每次检测过程中都需要计算一个第二参数，且每次检测过程中计算的第二参数均需要大于预设参数阈值。
需要说明的是，本申请实施例的中的数值n可以表示一个相对数字，并非限定于自开始对电池组进行故障检测开始的第n次，可以每间隔预设时长将检测次数重置为0，或者可以在某一次检测过程中第二参数小于预设参数阈值时将检测次数重置为0。
本申请实施例中的n次故障检测，可以是电池组处于静置工况、充电工况和放电工况下的故障检测。在一些实施例中，预设条件还包括：电池组处于目标充放电工况下。也就是说，当前次检测可以是电池处于充 电状态或者放电状态下的第n次故障检测过程。
在一些情形下，需要在静态工况，即充放电电流为0时通过各单体电芯间的电压差判断电芯是否发生内部短路故障。然而，通过压差判断内部短路故障的方案不仅容易造成误诊断，且只能在内短路较严重时有效识别，严重缩短了故障修复时间，而且该方案仅适用于电池处于静态工况的具体检测场景中，无法满足复杂的充放电工况中的内部短路检测需求。而本申请实施例提供的检测方法，无论电池组处于静置工况、充电工况还是放电工况下，仅能够对电芯内部短路故障进行检测，提高了检测方法的通用性。
然后，对于电信号值，电信号值为正常电芯、故障电芯之间存在差异性的电信号的数值。示例性地，可以是电压值或者电流值。为了便于理解本申请，本申请实施例的下述部分将主要以电压值为例进行具体解释说明。
最后，对于S310，对于电池组的每一电芯，可以获取p个时刻的电信号值。也就是说，对于p个时刻中的第i个时刻，需要分别获取m个电芯的电压值。其中，p为大于1的整数，i为不大于p的任意正整数。
S320，针对电池组的目标电芯，利用目标电芯在多个时刻的电信号值，计算目标电芯的第一参数。
首先，对于目标电芯，目标电芯是指电池组中需要进行内部短路故障诊断的电芯。示例性地，在检测过程中，可以将m个电芯依次作为目标电芯进行故障检测。也就是说，对于其中任意一个电芯，比如第j个电芯，完成对其的内部短路故障检测之后，可以将下一个电芯，即第j+1个电芯作为目标电芯，并对其进行内部短路故障检测。其中，j+1是不小于m的正整数。然后，对于第一参数，第一参数用于表征目标电芯的电信号值的波动程度。如果目标电芯的p个电信号值的差值较小，即目标电芯的p个电信号值的波动程度较小，则第一参数较小。相反地，如果目标电芯的p个电信号值的差值较大，即目标电芯的p个电信号值的波动程度较大，则第一参数较大。
在一些实施例中，第一参数可以是m个时刻的电芯值的标准 差、平均差或者方差等，对此不作限定。
在一个具体的实施例中，以第一参数为标准差为例，目标电芯标准差σ j满足公式(1)：
Figure PCTCN2021081241-appb-000001
其中，目标电芯为m个电芯中的第j电芯，j为小于或等于m的任意正整数。V ij为第j个电芯在第i个时刻的电压值，i为小于或等于p的任意正整数。
S330，针对电池组的目标电芯，计算目标电芯的第二参数。
其中，对于目标电芯的第二参数。
目标电芯的第二参数用于表征目标电芯的第一参数与其他电芯的第一参数之间离散程度。其中，其他电芯为m个电芯中除目标电芯以外的电芯。具体地，第二参数可以是m个电芯的第一参数的标准差或者变异系数。在一个示例中，由于在充放电过程中，电芯电压随着时间变化逐渐增大，为了便于对不同时间段的第二参数进行统一，第二参数可以选用无量纲的变异系数。需要说明的是，其他电芯的第一参数的计算方法与目标电芯的第一参数的计算方法相同，在此不再赘述。
第二参数与该离散程度呈正相关关系。也就是说，目标电芯的第一参数与其他m-1个电芯的第一参数之间的离散程度越大时，目标电芯的第二参数越大。继续以图1为例，正常电芯的变化曲线之间相差较小，且主要聚集在一个区域内。对于目标电芯，其变化曲线越靠近正常电芯变化曲线的聚集区域，其第二参数越小；反言之，如果其变化曲线越远离正常电芯变化曲线的聚集区域。
在一些实施例中，若目标电芯的第二参数为变异系数，则目标电
Figure PCTCN2021081241-appb-000002
其中，σ j为目标电芯的第一参数，σ mean为m个电芯的第一参数的平均值，σ σ为目标标准差。
相应地，图4是本申请实施例提供的一种示例性地电芯内部短路故障的检测方法的示意流程图。如图4所示，S330的具体实施方式可以包 括步骤S331和S332。
S331，计算目标标准差σ σ，以及计算m个电芯的第一参数的平均值σ mean。
其中，目标标准差σ σ用于表征m个电芯的第一参数的离散程度，目标标准差σ σ的计算公式为公式(3)：
Figure PCTCN2021081241-appb-000003
其中，m个电芯的第一参数的平均值σ mean的计算公式为公式(4)：
Figure PCTCN2021081241-appb-000004
S332，计算目标差值d与目标标准差σ σ的比值d/σ σ，并将比值d/σ σ确定为目标电芯的变异系数B j。
其中，目标差值d为目标电芯的第一参数σ j与平均值σ mean的差值。
S340，针对电池组的目标电芯，在第二参数大于预设参数阈值的条件下，确定目标电芯发生内部短路故障。
在一些实施例中，预设参数阈值与m个电芯的数量呈正相关关系。为了便于说明，本申请实施例下述部分将以第二参数为变异系数为例，对预设参数阈值展开具体解释说明。
表1电芯总数与预设参数阈值的对应关系
电芯总数 <50 50-100 100-150 >150
预设参数阈值 4 5 6 10
如上述表1所示，申请人基于大量试验数据和仿真结果，按照电芯数据对预设参数阈值进行阶梯式设置。如果电池组内的电芯总数小于50时，可以将预设参数阈值设置为4。也就是说，若目标电芯的变异系数B j大于4，则确定目标电芯为故障电芯。如果电池组内的电芯总数在50至100之间时，可以将预设参数阈值设置为5。也就是说，若目标电芯的变异系数B j大于5，则确定目标电芯为故障电芯。如果电池组内的电芯总数在100至150之间时，可以将预设参数阈值设置为6。也就是说，若目标电芯的变异系数B j大于6，则确定目标电芯为故障电芯。如果电池组内的 电芯总数大于150时，可以将预设参数阈值设置为10。也就是说，若目标电芯的变异系数B j大于10，则确定目标电芯为故障电芯。
示例性地，当电池组内电芯数量为30时，本申请实施例的电池组的电芯的变异系数的示例性的仿真结果可以如图5所示。如图5所示，故障电芯的变异系数B大多数时间在4-6之间波动，而正常电芯的变异系数B基本不会超过2，也就是说正常电芯的变异系数B在0-2之间波动。
又一示例性地，当电池组内电芯数量为192时，本申请实施例的电池组的电芯的变异系数的示例性的仿真结果可以如图6所示。如图6所示，故障电芯的变异系数B在大多数情况下在10-12之间波动，而正常电芯的变异系数B的最大值可能略大于4，正常电芯的变异系数B基本在0-4之间波动。
通过图5和图6对比可知，若电池组内电芯数量为192时的预设参数阈值与电池组内电芯数量为30时的预设参数阈值同为4，则当电池组内电芯数量较多时，可能会将正常电芯误诊断为发生了内部短路故障。另外，若电池组内电芯数量为30时的预设参数阈值与电池组内电芯数量为192时的预设参数阈值同为10，则当电池组内电芯数量较少时，可能将无法诊断出发生内部短路故障的故障电芯。
根据本申请实施例中的电芯内部短路故障的检测方法，在当前处于针对所述充放电工况下的电芯内部短路故障的第n次检测过程中，可以根据目标电芯在多个时刻的电信号值，计算第一参数。对于属于同一电池组的m个电芯，发生内部短路故障的故障电芯的电信号变化速率会不同于正常电芯的电信号变化速率，相应地故障电芯的电信号波动程度也会不同于其他正常电芯的电信号波动程度。由于第一参数能够表征电信号波动程度，故障电芯的第一参数也不同于正常电芯的第一参数。当电池组的m个电芯中存在故障电芯时，故障电芯的第一参数与其他电芯的第一参数的离散度会大于正常电芯。因此，利用可以表征每一电芯的第一参数与其他电芯的第一参数之间的离散程度的第二参数，由于第二参数与所述离散程度呈正相关关系，当某一电芯的第二参数大于预设参数阈值时，准确的对发生内部短路的电芯进行了检测。
为了更好的理解本申请，图7是本申请实施例提供了一种示例性的电芯内部短路故障的检测方法的示意流程图。如图7所示，电芯内部短路故障的检测方法700包括S710至S790。
S710，采集电压数据，并建立t×m电压矩阵。具体地，在电池组处于充电过程中，采集电池组的全部m个电芯在全程总计t秒内的电压数据，并按照m个电芯的t秒的电压数据建立t×m电压矩阵。
其中，t×m电压矩阵具体表示为：
Figure PCTCN2021081241-appb-000005
其中，t×m电压矩阵中的第i行数据为第i秒时m个电芯各自的电压数据，电压矩阵中的第j列数据为第j个电芯在t秒内的电压数据。示例性地，本实施例中的t等于96秒。
S720，获取参数n。其中，n的初始值为1。
S730，从t×m电压矩阵中截取m个电芯在第n秒至第n+p-1秒的电压数据，并建立第n次检测过程中的p×m电压矩阵。
其中，p×m电压矩阵具体表示为：
Figure PCTCN2021081241-appb-000006
S740，利用上一步骤的p×m电压矩阵，计算每个电芯在第n秒至第n+p-1秒的标准差σ，并生成1×m标准差矩阵。具体地，利用p×m电压矩阵中每一列的p个电压数据，可以计算得到一个标准差σ。
其中，m个电芯的标准差可以表示为1×m标准差矩阵：
(σ 1，1，…，σ 1，m)
标准差σ的具体内容可参见本申请上述实施例对第一参数计算方式的相关描述，不再赘述。
S750，利用上一步骤的1×m标准差矩阵，计算m个电芯的标准差的平均值σ mean和标准差σ σ。
其中，平均值σ mean和标准差σ σ的具体内容可参见本申请上述实施例S330部分对平均值σ mean和目标标准差σ σ的相关描述，不再赘述。
S760，利用上一步骤计算得到的平均值σ mean和标准差σ σ，计算每个电芯在第n秒至第n+p-1秒的变异系数。
S780，若上一步骤计算得到的任意电芯j的变异系数B j大于预设阈值x，则确定电芯j发生内部短路故障。
S790，将n更新为n+1，并返回步骤S710，直到n＝t+1-p，也就是完成对所有电压数据的处理。
由于电池从发生内部短路到最终热失控往往需要经历数小时的时间，从发生内部短路开始本申请实施例利用前n秒，例如96秒的电压数据即可判断电芯是否发生内部短路故障，在内部短路故障早期即可及时识别故障电芯，最大程度避免热失控的发生，最大程度保证电池安全。
基于相同的申请构思，本申请实施例除了提供了电芯内部短路故障的检测方法之外，还提供了与之对应的电芯内部短路故障的检测装置。下面结合附图，详细介绍根据本申请实施例的装置。图8是本申请实施例提供的电芯内部短路故障的检测装置的结构示意图。
如图8所示，电芯内部短路故障的检测装置800包括数据获取模块810、第一计算模块820、第二计算模块830和故障检测模块840。
数据获取模块810，用于在电池组处于预设条件下，分别获取电池组的m个电芯在多个时刻的电信号值。
其中预设条件包括当前处于针对电芯内部短路故障的第n次检测过程中，m、n为正整数。
第一计算模块820，用于针对电池组的目标电芯，利用目标电芯在多个时刻的电信号值，计算目标电芯的第一参数。
其中，第一参数用于表征目标电芯的电信号值的波动程度。
第二计算模块830，用于针对电池组的目标电芯，计算表征目标电芯的第一参数与其他电芯的第一参数之间离散程度的第二参数。
其中，第二参数与离散程度呈正相关关系，其他电芯为m个电芯中除目标电芯以外的电芯。
故障检测模块840，用于针对电池组的目标电芯，在第二参数大于预设参数阈值的条件下，确定目标电芯发生内部短路故障。
在一些实施例中，当n为大于1的整数时，预设条件还包括：针对电芯内部短路故障的前n-1次检测过程中，目标电芯的第二参数均大于预设参数阈值。
在一些实施例中，预设参考阈值与m个电芯的数量呈正相关关系。
在一些实施例中，目标电芯的第一参数为目标电芯在多个时刻的电信号值的标准差。
在一些实施例中，第二参数为变异系数，
第二计算模块830，具体包括第一计算单元和第二计算单元。
第一计算单元，用于计算表征m个电芯的第一参数的离散程度的目标标准差，以及计算m个电芯的第一参数的平均值。
第二计算单元，用于计算目标差值与目标标准差的比值，并将比值确定为目标电芯的变异系数。
其中，目标差值为目标电芯的第一参数与平均值的差值。
根据本申请实施例中的电芯内部短路故障的检测装置，在当前处于针对所述充放电工况下的电芯内部短路故障的第n次检测过程中，可以根据目标电芯在多个时刻的电信号值，计算第一参数。对于属于同一电池组的m个电芯，发生内部短路故障的故障电芯的电信号变化速率会不同于正常电芯的电信号变化速率，相应地故障电芯的电信号波动程度也会不同于其他正常电芯的电信号波动程度。由于第一参数能够表征电信号波动程度，故障电芯的第一参数也不同于正常电芯的第一参数。当电池组的m个电芯中存在故障电芯时，故障电芯的第一参数与其他电芯的第一参数的离散度会大于正常电芯。因此，利用可以表征每一电芯的第一参数与其他电芯的第一参数之间的离散程度的第二参数，由于第二参数与所述离散程度呈正相关关系，当某一电芯的第二参数大于预设参数阈值时，准确的对发生内部短路的电芯进行了检测。
根据本申请实施例的电芯内部短路故障的检测装置的其他细节，与以上结合图1至图7所示实例描述的电芯内部短路故障的检测方法类似，并能达到其相应的技术效果，为简洁描述，在此不再赘述。
图9示出了本申请实施例提供的电芯内部短路故障的检测设备的硬件结构示意图。
在电芯内部短路故障的检测设备可以包括处理器901以及存储有计算机程序指令的存储器902。
具体地，上述处理器901可以包括中央处理器(Central Processing Unit，CPU)，或者特定集成电路(Application Specific Integrated Circuit，ASIC)，或者可以被配置成实施本申请实施例的一个或多个集成电路。
存储器902可以包括用于数据或指令的大容量存储器。举例来说而非限制，存储器902可包括硬盘驱动器(Hard Disk Drive，HDD)、软盘驱动器、闪存、光盘、磁光盘、磁带或通用串行总线(Universal Serial Bus，USB)驱动器或者两个或更多个以上这些的组合。在一些实例中，存储器902可以包括可移除或不可移除(或固定)的介质，或者存储器902是非易失性固态存储器。在一些实施例中，存储器902可在电芯内部短路故障的检测设备的内部或外部。
在一些实例中，存储器902可以是只读存储器(Read Only Memory，ROM)。在一个实例中，该ROM可以是掩模编程的ROM、可编程ROM(PROM)、可擦除PROM(EPROM)、电可擦除PROM(EEPROM)、电可改写ROM(EAROM)或闪存或者两个或更多个以上这些的组合。
存储器902可以包括只读存储器(ROM)，随机存取存储器(RAM)，磁盘存储介质设备，光存储介质设备，闪存设备，电气、光学或其他物理/有形的存储器存储设备。因此，通常，存储器包括一个或多个编码有包括计算机可执行指令的软件的有形(非暂态)计算机可读存储介质(例如，存储器设备)，并且当该软件被执行(例如，由一个或多个处理器)时，其可操作来执行参考根据本公开的一方面的方法所描述的操作。
处理器901通过读取并执行存储器902中存储的计算机程序指令，以实现图1至图7所示实施例中的方法，并达到图1至图7所示实例 执行其方法/步骤达到的相应技术效果，为简洁描述在此不再赘述。
在一个示例中，电芯内部短路故障的检测设备还可包括通信接口903和总线910。其中，如图9所示，处理器901、存储器902、通信接口903通过总线910连接并完成相互间的通信。
通信接口903，主要用于实现本申请实施例中各模块、装置、单元和/或设备之间的通信。
总线910包括硬件、软件或两者，将在线数据流量计费设备的部件彼此耦接在一起。举例来说而非限制，总线可包括加速图形端口(Accelerated Graphics Port，AGP)或其他图形总线、增强工业标准架构(Extended Industry Standard Architecture，EISA)总线、前端总线(Front Side Bus，FSB)、超传输(Hyper Transport，HT)互连、工业标准架构(Industry Standard Architecture，ISA)总线、无限带宽互连、低引脚数(LPC)总线、存储器总线、微信道架构(MCA)总线、外围组件互连(PCI)总线、PCI-Express(PCI-X)总线、串行高级技术附件(SATA)总线、视频电子标准协会局部(VLB)总线或其他合适的总线或者两个或更多个以上这些的组合。在合适的情况下，总线910可包括一个或多个总线。尽管本申请实施例描述和示出了特定的总线，但本申请考虑任何合适的总线或互连。
该电芯内部短路故障的检测设备可以执行本申请实施例中的电芯内部短路故障的检测方法，从而实现结合图1至图8描述的电芯内部短路故障的检测方法和装置。
另外，结合上述实施例中的电芯内部短路故障的检测方法，本申请实施例可提供一种计算机存储介质来实现。该计算机存储介质上存储有计算机程序指令；该计算机程序指令被处理器执行时实现上述实施例中的任意一种电芯内部短路故障的检测方法。
需要明确的是，本申请并不局限于上文所描述并在图中示出的特定配置和处理。为了简明起见，这里省略了对已知方法的详细描述。在上述实施例中，描述和示出了若干具体的步骤作为示例。但是，本申请的方法过程并不限于所描述和示出的具体步骤，本领域的技术人员可以在领会 本申请的精神后，作出各种改变、修改和添加，或者改变步骤之间的顺序。
以上所述的结构框图中所示的功能块可以实现为硬件、软件、固件或者它们的组合。当以硬件方式实现时，其可以例如是电子电路、专用集成电路(Application Specific Integrated Circuit，ASIC)、适当的固件、插件、功能卡等等。当以软件方式实现时，本申请的元素是被用于执行所需任务的程序或者代码段。程序或者代码段可以存储在机器可读介质中，或者通过载波中携带的数据信号在传输介质或者通信链路上传送。“机器可读介质”可以包括能够存储或传输信息的任何介质。机器可读介质的例子包括电子电路、半导体存储器设备、ROM、闪存、可擦除ROM(EROM)、软盘、CD-ROM、光盘、硬盘、光纤介质、射频(Radio Frequency，RF)链路，等等。代码段可以经由诸如因特网、内联网等的计算机网络被下载。
还需要说明的是，本申请中提及的示例性实施例，基于一系列的步骤或者装置描述一些方法或系统。但是，本申请不局限于上述步骤的顺序，也就是说，可以按照实施例中提及的顺序执行步骤，也可以不同于实施例中的顺序，或者若干步骤同时执行。
上面参考根据本公开的实施例的方法、装置、设备及和计算机程序产品的流程图和/或框图描述了本公开的各方面。应当理解，流程图和/或框图中的每个方框以及流程图和/或框图中各方框的组合可以由计算机程序指令实现。这些计算机程序指令可被提供给通用计算机、专用计算机、或其它可编程数据处理装置的处理器，以产生一种机器，使得经由计算机或其它可编程数据处理装置的处理器执行的这些指令使能对流程图和/或框图的一个或多个方框中指定的功能/动作的实现。这种处理器可以是但不限于是通用处理器、专用处理器、特殊应用处理器或者现场可编程逻辑电路。还可理解，框图和/或流程图中的每个方框以及框图和/或流程图中的方框的组合，也可以由执行指定的功能或动作的专用硬件来实现，或可由专用硬件和计算机指令的组合来实现。
以上所述，仅为本申请的具体实施方式，所属领域的技术人员可 以清楚地了解到，为了描述的方便和简洁，上述描述的系统、模块和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。应理解，本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本申请的保护范围之内。

Claims (10)

  1. 一种电芯内部短路故障的检测方法，包括：
    在电池组处于预设条件下，分别获取所述电池组的m个电芯在多个时刻的电信号值，其中所述预设条件包括当前处于针对电芯内部短路故障的第n次检测过程中，m、n为正整数；
    针对所述电池组的目标电芯，执行如下步骤：
    利用所述目标电芯在所述多个时刻的电信号值，计算所述目标电芯的第一参数，其中，所述第一参数用于表征所述目标电芯的电信号值的波动程度；
    计算表征所述目标电芯的第一参数与其他电芯的第一参数之间离散程度的第二参数，其中，所述其他电芯为所述m个电芯中除所述目标电芯以外的电芯，所述第二参数与所述离散程度呈正相关关系；
    在所述第二参数大于预设参数阈值的条件下，确定所述目标电芯发生内部短路故障。
  2. 根据权利要求1所述的电芯内部短路故障的检测方法，其中，当n为大于1的整数时，所述预设条件还包括：
    针对电芯内部短路故障的前n-1次检测过程中，所述目标电芯的第二参数均大于预设参数阈值。
  3. 根据权利要求1或2所述的电芯内部短路故障的检测方法，其中，所述预设参考阈值与所述m个电芯的数量呈正相关关系。
  4. 根据权利要求1-3任一项所述的电芯内部短路故障的检测方法，其中，所述目标电芯的第一参数为所述目标电芯在所述多个时刻的电信号值的标准差。
  5. 根据权利要求1或权利要求4所述的电芯内部短路故障的检测方法，其中，所述第二参数为变异系数，
    所述计算表征所述目标电芯的第一参数与其他电芯的第一参数之间离散程度的第二参数，包括：
    计算表征所述m个电芯的第一参数的离散程度的目标标准差，以及计 算所述m个电芯的第一参数的平均值；
    计算目标差值与所述目标标准差的比值，并将所述比值确定为所述目标电芯的变异系数，其中，所述目标差值为所述目标电芯的第一参数与所述平均值的差值。
  6. 一种电芯内部短路故障的检测装置，包括：
    数据获取模块，用于在电池组处于预设条件下，分别获取所述电池组的m个电芯在多个时刻的电信号值，其中所述预设条件包括当前处于针对电芯内部短路故障的第n次检测过程中，m、n为正整数；
    第一计算模块，用于针对所述电池组的目标电芯，利用所述目标电芯在所述多个时刻的电信号值，计算所述目标电芯的第一参数，其中，所述第一参数用于表征所述目标电芯的电信号值的波动程度；
    第二计算模块，用于针对所述电池组的目标电芯，计算表征所述目标电芯的第一参数与其他电芯的第一参数之间离散程度的第二参数，其中，所述第二参数与所述离散程度呈正相关关系，所述其他电芯为所述m个电芯中除所述目标电芯以外的电芯；
    故障检测模块，用于针对所述电池组的目标电芯，在所述第二参数大于预设参数阈值的条件下，确定所述目标电芯发生内部短路故障。
  7. 根据权利要求6所述的电芯内部短路故障的检测装置，其中，当n为大于1的整数时，所述预设条件还包括：
    针对所述充放电工况下的电芯内部短路故障的前n-1次检测过程中，所述目标电芯的变异系数均大于预设参数阈值。
  8. 根据权利要求6或7所述的电芯内部短路故障的检测装置，其中，所述预设参考阈值与所述m个电芯的数量呈正相关关系。
  9. 一种电芯内部短路故障的检测设备，包括：
    存储器，用于存储程序；
    处理器，用于运行所述存储器中存储的所述程序，以执行权利要求1-5任一项所述的电芯内部短路故障的检测方法。
  10. 一种计算机存储介质，所述计算机存储介质上存储有计算机程序指令，所述计算机程序指令被处理器执行时实现权利要求1-5任一项所述 的电芯内部短路故障的检测方法。
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