Battery short circuit fault warning information generation method, device, equipment, and medium

Abstract

This embodiment provides a method, device, equipment, and medium for generating battery short-circuit fault warning information, which are applied to the discharge process and belong to the field of fault diagnosis technology. The method includes: obtaining discharge data of a discharge process, wherein the discharge data includes sampling time, discharge current, and voltages of at least two single cells; calculating the difference in open-circuit voltage of each single cell compared to the average cell at each data sampling point based on the discharge current and the voltage of the single cell; calculating the open-circuit voltage difference eigenvalue matrix based on the open-circuit voltage difference of each single cell at each data sampling point; and generating battery short-circuit fault warning information during the discharge process based on the open-circuit voltage difference eigenvalue matrix. By analyzing the discharge data of the battery discharge process uploaded to the cloud, battery short-circuit fault diagnosis and warning can be performed in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of fault diagnosis, and in particular to a method, device, equipment, and medium for generating battery short circuit fault warning information. Background Art

[0002] In related technologies, the method of diagnosing and warning battery short-circuit faults through the voltage difference of single cells is easily affected by current, temperature, and sampling, resulting in false alarms. In order to reduce false alarms, the warning threshold is generally set high, and a warning is only issued when the voltage difference caused by the short circuit of the single cell is very large, resulting in a delay in fault diagnosis. In addition, the method of diagnosing and warning battery short-circuit faults through the SOC of the single cell requires knowing the battery's OCV-SOC curve, and has high requirements for the sampling synchronization and sampling frequency of the voltage and current data. The calculation is complex and is easily affected by the consistency of the single cell capacity, resulting in false alarms. Summary of the Invention

[0003] The main purpose of the embodiments of the present disclosure is to propose a method and device, equipment, and medium for generating battery short-circuit fault warning information, which are applied to the discharge process, can perform real-time analysis of battery discharge process data uploaded to the cloud, and perform battery short-circuit fault diagnosis and warning.

[0004] To achieve the above objectives, a first aspect of an embodiment of the present disclosure provides a method for generating battery short circuit fault warning information, which is applied to a discharge process and includes:

[0005] Acquire discharge data of a discharge process, wherein the discharge data includes sampling time, discharge current, and voltages of at least two single cells;

[0006] Calculating, based on the discharge current and the voltage of the single battery, a difference in open circuit voltage of each single battery compared to an average battery at each data sampling point;

[0007] Calculating an open circuit voltage difference eigenvalue matrix according to the open circuit voltage difference value of each of the single cells at each of the data sampling points;

[0008] According to the open circuit voltage difference eigenvalue matrix, battery short circuit fault warning information during the discharge process is generated.

[0009] In some embodiments, calculating the difference in open circuit voltage of each single cell compared to an average cell at each data sampling point based on the discharge current and the voltage of the single cell includes:

[0010] Calculating a first open-circuit voltage of the single cell at the data sampling point and a second open-circuit voltage of the average cell at the data sampling point according to the discharge current at the data sampling point and the voltage at the data sampling point;

[0011] The open circuit voltage difference value of the single battery at the data sampling point is calculated according to the first open circuit voltage and the second open circuit voltage.

[0012] In some embodiments, the first open-circuit voltage and the second open-circuit voltage are calculated using extended Kalman filtering or recursive least squares method.

[0013] In some embodiments, calculating the open circuit voltage difference eigenvalue matrix according to the open circuit voltage difference value of each single cell at each data sampling point includes:

[0014] Dividing the operating voltage range of the single battery into at least two sub-ranges, wherein the operating voltage range is a range from a discharge cut-off voltage to a charge cut-off voltage;

[0015] Classifying each of the data sampling points into a plurality of subintervals according to an average open circuit voltage value of the battery at each of the data sampling points;

[0016] Calculating a characteristic value of the open circuit voltage difference of the single cell in the subinterval according to the open circuit voltage difference value of the single cell at the data sampling point in the subinterval;

[0017] The open circuit voltage difference eigenvalue matrix is ​​calculated based on the open circuit voltage difference eigenvalues ​​of the single battery in the sub-interval.

[0018] In some embodiments, generating battery short circuit fault warning information during the discharge process according to the open circuit voltage difference eigenvalue matrix includes:

[0019] Obtain an open circuit voltage difference eigenvalue reference matrix;

[0020] The battery short circuit fault warning information is generated according to the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix.

[0021] In some embodiments, the battery short circuit fault warning information includes first fault warning information, and generating the battery short circuit fault warning information according to the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix includes:

[0022] Obtaining a first test result based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix; the first test result includes that none of the elements at corresponding positions are null values;

[0023] Obtaining a second test result based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix; the second test result includes that the element difference at the corresponding position is less than a preset threshold;

[0024] First fault warning information is generated according to the first inspection result and the second inspection result.

[0025] In some embodiments, the battery short circuit fault warning information includes second fault warning information, and generating the battery short circuit fault warning information during the discharge process according to the open circuit voltage difference eigenvalue matrix includes:

[0026] Calculating an open circuit voltage difference eigenvalue long-term evolution matrix based on the open circuit voltage difference eigenvalue matrix;

[0027] Calculating the evolution rate of the open circuit voltage difference eigenvalues ​​of the single battery cells according to the long-term evolution matrix of the open circuit voltage difference eigenvalues;

[0028] The second fault warning information is generated according to the evolution speed.

[0029] A second aspect of the embodiments of the present disclosure provides a device for generating battery short circuit fault warning information, which is applied to a discharge process and includes:

[0030] A first acquisition module is used to acquire discharge data of a discharge process, wherein the discharge data includes sampling time, discharge current, and voltages of at least two single cells;

[0031] A first calculation module is configured to calculate, based on the discharge current and the voltage of the single battery, a difference in open circuit voltage between each single battery and an average battery at each data sampling point;

[0032] A second calculation module is configured to calculate an open circuit voltage difference eigenvalue matrix according to the open circuit voltage difference value of each single cell at each data sampling point;

[0033] The fault warning information generation module is used to generate battery short circuit fault warning information during the discharge process according to the open circuit voltage difference eigenvalue matrix.

[0034] A third aspect of the embodiments of the present disclosure provides a computer device, comprising a memory and a processor, wherein the memory stores a program, and when the program is executed by the processor, the processor is used to execute the method described in any one of the embodiments of the first aspect of the application.

[0035] The fourth aspect of the embodiments of the present disclosure proposes a storage medium, which is a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a computer, the computer is used to execute the method described in any one of the embodiments of the first aspect of the present application.

[0036] The battery short-circuit fault warning information generation method, device, equipment, and medium proposed in the embodiments of the present disclosure are applied to the discharge process. Discharge data of a discharge process is obtained, and the discharge data includes a sampling time, a discharge current, and the voltage of at least two single cells. The discharge data is sampled according to the sampling time to obtain at least two data sampling points. The open-circuit voltage difference value of each single cell compared to the average cell at each data sampling point is calculated based on the discharge current and the voltage of the single cell. An open-circuit voltage difference eigenvalue matrix is ​​calculated based on the open-circuit voltage difference value. The open-circuit voltage difference eigenvalue matrix is ​​used to generate battery short-circuit fault warning information during the discharge process. This enables short-circuit fault diagnosis and warning of the battery based on the discharge data of the battery discharge process. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a first flow chart of a method for generating battery short circuit fault warning information provided by an embodiment of the present disclosure;

[0038] Figure 2 yes Figure 1 Flowchart of step S120 in FIG.

[0039] Figure 3 yes Figure 1 Flowchart of step S130 in FIG.

[0040] Figure 4 yes Figure 1 The first flow chart of step S140 in FIG.

[0041] Figure 5 yes Figure 4 Flowchart of step S420 in FIG.

[0042] Figure 6 yes Figure 1 A second flow chart of step S140 in FIG.

[0043] Figure 7 This is a second flow chart of the method for generating battery short circuit fault warning information provided by an embodiment of the present disclosure;

[0044] Figure 8 This is a third flow chart of the method for generating battery short circuit fault warning information provided by an embodiment of the present disclosure;

[0045] Figure 9This is a module structure diagram of a device for generating battery short circuit fault warning information provided by an embodiment of the present disclosure;

[0046] Figure 10 It is a schematic diagram of the hardware structure of the computer device provided in the embodiment of the present disclosure. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0048] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention pertains. The terms used herein are for the purpose of describing embodiments of the present invention only and are not intended to limit the present invention.

[0050] Currently, short-circuit fault diagnosis and early warning methods based on battery discharge data generally use cell voltage differentials to determine whether a fault has occurred and issue an early warning. If the cell voltage differential or the rate of change in the voltage differential exceeds a preset threshold, an early warning is issued for that cell. Alternatively, methods use the SOC values ​​of each cell during the battery system's discharge process to perform fault diagnosis and early warning. This method first uses discharge data from the battery system to identify the SOC value of each cell in real time. This SOC value is then used to calculate the SOC difference between cells, or directly identify the SOC difference between each cell and the average cell. If the SOC difference or the rate of change over time exceeds a preset threshold, an early warning is issued for that cell. SOC (State of Charge) refers to the state of charge, representing the ratio of a battery's remaining capacity to its fully charged capacity. Its value range is [0, 1]. An SOC value of 0 indicates a fully discharged battery. An SOC value of 1 indicates a fully charged battery. However, the method of using the voltage difference of each cell for fault warning is greatly affected by the charging current, temperature, and sampling time, and is prone to false alarms. In order to reduce false alarms, the threshold is generally set high. Only when the voltage difference is very large will the battery be considered to have a short circuit fault and a warning be issued, resulting in a certain delay in fault identification. The method of using the SOC value of each cell for fault warning requires knowing the OCV-SOC curve of each cell, and has high requirements for the sampling synchronization and acquisition frequency of data such as the voltage and discharge current of each cell, that is, higher than the GB-32960 standard of uploading one data every 10 seconds. The calculation is more complex and requires high computing resources. In addition, the change in the SOC difference between each cell is affected by the consistency of the cell capacity, which may cause false alarms.

[0051] Based on this, the main purpose of the embodiments of the present disclosure is to propose a method and device, equipment, and medium for generating battery short-circuit fault warning information, which is applied to the discharge process, and the battery short-circuit fault is diagnosed by the open-circuit voltage difference value of each single battery during the discharge process, so as to perform battery short-circuit fault analysis and warning in real time.

[0052] The battery short circuit fault warning information generation method, device, equipment, and medium provided in the embodiments of the present disclosure are specifically described through the following embodiments. First, the battery short circuit fault warning information generation method in the embodiments of the present disclosure is described.

[0053] Reference Figure 1 According to the first aspect of the embodiments of the present disclosure, the method for generating battery short circuit fault warning information includes but is not limited to steps S110 to S140.

[0054] S110, obtaining discharge data of a discharge process, where the discharge data includes sampling time, discharge current, and voltages of at least two single cells;

[0055] S120, calculating the difference in open circuit voltage of each single cell compared to the average cell at each data sampling point based on the discharge current and the voltage of the single cell;

[0056] S130, calculating an open circuit voltage difference eigenvalue matrix based on the open circuit voltage difference value of each single cell at each data sampling point;

[0057] S140 , generating battery short circuit fault warning information during the discharge process according to the open circuit voltage difference eigenvalue matrix.

[0058] In step S110, the discharge data may be the discharge data of the vehicle's battery system, which includes multiple series-connected cells, uploaded to the cloud platform in accordance with the GB32960 standard. The GB32960 standard is the technical specification for electric vehicle remote service and management systems. The discharge data for a single discharge process refers to the complete discharge data from the end of one parking charge to the start of the next parking charge. The discharge data for a single discharge process includes the sampling time, discharge current, and the voltages of at least two cells. The discharge current and voltage both vary with discharge time.

[0059] In step S120, discharge data is first sampled according to the sampling time to obtain at least two data sampling points. Then, based on the discharge current and the voltage of the individual cells, the difference in open circuit voltage (OCV) between the individual cells and the average cell at the data sampling points is calculated. The average cell is a collective representation of multiple individual cells; the open circuit voltage difference (dOCV) is the difference between the open circuit voltage of the individual cells and the average cell; and the open circuit voltage (OCV) is the terminal voltage of the cell in the open circuit state. By calculating the difference in open circuit voltage of each individual cell at each data sampling point compared to the average cell, the open circuit voltage difference between the individual cells in series can be identified in real time.

[0060] In step S130 and step S140, the open circuit voltage difference value of the single cell is used to approximately represent the SOC difference value of the single cell, eliminating the influence of current and temperature. The single cell with a sharp increase in open circuit voltage difference and a slow increase in open circuit voltage difference can be identified in time and an early warning can be issued. All discharge data uploaded to the cloud can be analyzed in real time, which has strong timeliness and can discover problems as early as possible. It solves the problem that the cloud cannot use discharge data to directly identify the SOC difference between each single cell, and does not require the support of the battery OCV-SOC curve, reducing the calculation complexity and the demand for computing resources.

[0061] In some embodiments, as Figure 2 As shown, step S120 specifically includes the following steps:

[0062] S210, calculating a first open circuit voltage of a single cell at the data sampling point and a second open circuit voltage of an average cell at the data sampling point based on the discharge current and the voltage at the data sampling point;

[0063] S220 , calculating an open circuit voltage difference value of the single battery at the data sampling point based on the first open circuit voltage and the second open circuit voltage.

[0064] In step S210, the discharge current at each data sampling point in the current discharge process is obtained to generate a discharge current sequence {I k}, obtain the voltage of each single cell at each data sampling point during this discharge process to generate the voltage sequence of the single cell {V k,i}, where k≤m,i≤n, m is the number of sampling points, n is the number of single cells in the battery system, V k,i Represents the voltage of the ith single cell at the kth data sampling point. According to the voltage sequence {V k,i}, calculate the average battery voltage at each data sampling point during this discharge process. For example, according to the voltage sequence {V k,i}, where k = j, the average value or median of the voltage sequence is taken as the voltage V of the average battery at the jth data sampling point j,ave According to the average battery voltage at each data sampling point, the average battery voltage sequence {V k,ave It should be noted that the embodiments of the present disclosure do not limit the specific values ​​of m and n, and those skilled in the art can set the number of single cells in the battery system, i.e., m, and the sampling time according to actual needs.

[0065] Let the internal resistance of the single cell at the data sampling point be expressed as R k,i , according to the discharge current I at the data sampling point k, the voltage of the single cell at the data sampling point V k,i , the internal resistance R of the single battery at the data sampling point k,i , to establish the first Rint equivalent circuit model, namely OCV k,i =V k,i +I k R k,i Based on the first Rint equivalent circuit model, the first open circuit voltage and the internal resistance of the single cell are calculated using the extended Kalman filter (EKF) or the recursive least squares method, that is, the single cell voltage sequence {V k,i} and the discharge current sequence {I k} is input and the open circuit voltage OCV of each single cell at each data sampling point is calculated and output k,i And the internal resistance R of each single cell at each data sampling point k,i .

[0066] Let the average internal resistance of the battery at the data sampling point be expressed as R k,ave , according to the discharge current I at the data sampling point k , average battery voltage V at the data sampling point k,ave , the average battery internal resistance R at the data sampling point k,ave , to establish the second Rint equivalent circuit model, namely OCV k,ave =V k,ave +I k R k,ave Based on the second Rint equivalent circuit model, the second open circuit voltage and the average battery internal resistance are calculated using the extended Kalman filter (EKF) or the recursive least squares method, that is, the average battery voltage sequence {V k,ave} and the discharge current sequence {I k} is input and the open circuit voltage OCV of each average battery at each data sampling point is calculated and output k,ave And the internal resistance R of each average battery at each data sampling point k,ave .

[0067] In step S220 , the difference between the first open circuit voltage of the single cell at the data sampling point and the second open circuit voltage of the average cell at the data sampling point is used as the open circuit voltage difference value of the single cell at the data sampling point.

[0068] In some embodiments, as Figure 3 As shown, step S130 specifically includes the following steps:

[0069] S310, dividing a use voltage range of a cell voltage into at least two sub-ranges, where the use voltage range is a range from a discharge cut-off voltage to a charge cut-off voltage;

[0070] S320, classifying each data sampling point into a plurality of sub-intervals according to an average open circuit voltage value of the battery at each data sampling point;

[0071] S330, calculating an open circuit voltage difference characteristic value of the single cell in the subinterval according to the open circuit voltage difference value of the single cell at the data sampling point in the subinterval;

[0072] S340 , calculating an open circuit voltage difference eigenvalue matrix based on the open circuit voltage difference eigenvalues ​​of the single cells in the subintervals.

[0073] In step S310, the operating voltage range of the single battery is from the discharge cut-off voltage to the charge cut-off voltage specified by the battery manufacturer, and the operating voltage range is divided into a plurality of sub-ranges at equal intervals.

[0074] In step S320, the data sampling points are classified into the subintervals according to the subintervals in which the average battery open circuit voltage values ​​at the data sampling points are located, until all the data sampling points are classified into the correct subintervals. According to which voltage subinterval the average battery open circuit voltage values ​​at each data sampling point are located, the data sampling point is also located in this subinterval. For example, let the number of subintervals be n, and the subintervals are numbered from 1 to n in the order from the discharge cut-off voltage to the charge cut-off voltage, that is, in the order of the voltage ranges used. If the average battery open circuit voltage value OCV at the kth data sampling point is k,ave If it is in the 4th subinterval, the kth data sampling point is classified into the 4th subinterval.

[0075] In step S330, based on the open circuit voltage difference values ​​of a cell at the data sampling points within the same subinterval, an average open circuit voltage difference value of the cell in the subinterval is calculated. This average open circuit voltage difference value is used as the open circuit voltage difference characteristic value of the cell in the subinterval. At all data sampling points within each subinterval, the average open circuit voltage difference values ​​corresponding to each cell are calculated to calculate the open circuit voltage difference characteristic value for each cell in each subinterval.

[0076] In step S340, the open-circuit voltage difference eigenvalues ​​for each battery cell in each subrange are stored in a matrix to generate an open-circuit voltage difference eigenvalue matrix. Each row of the matrix represents a voltage subrange, and each column represents a battery cell. Thus, an element in the matrix represents the open-circuit voltage difference eigenvalue for a particular battery cell in a particular voltage subrange. If no data sampling point falls within a particular voltage subrange during the current discharge process, the row of the matrix corresponding to that voltage subrange is left blank.

[0077] In some embodiments, as Figure 4 As shown, step S140 specifically includes the following steps:

[0078] S410, obtaining an open circuit voltage difference eigenvalue reference matrix;

[0079] S420 , generating battery short circuit fault warning information according to the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix.

[0080] In step S410, the open circuit voltage difference eigenvalue reference matrix for the current discharge process is calculated based on the open circuit voltage difference eigenvalue matrix for the previous discharge process. That is, all non-null elements in the open circuit voltage difference eigenvalue matrix for the previous discharge process replace the original open circuit voltage difference eigenvalue reference matrix to update the open circuit voltage difference eigenvalue reference matrix. The open circuit voltage difference eigenvalue matrix for the current discharge process is stored for use in updating the open circuit voltage difference eigenvalue reference matrix for the next discharge process. The open circuit voltage difference eigenvalue matrix for the current discharge process is stored by clearing the open circuit voltage difference eigenvalue matrix for the previous discharge process.

[0081] It should be noted that no battery short-circuit fault warning analysis is performed during the first discharge process. Only the open-circuit voltage difference eigenvalue matrix of this discharge process is stored and used as the reference matrix for the open-circuit voltage difference eigenvalues ​​of the subsequent discharge process. Warning judgment is required for the second discharge process and subsequent discharge processes, except for the first discharge process.

[0082] In step S420, each element of the open circuit voltage difference eigenvalue matrix is ​​compared with the corresponding element of the open circuit voltage difference eigenvalue reference matrix, and battery short circuit fault warning information is generated according to the comparison result.

[0083] In some embodiments, as Figure 5 As shown, the battery short circuit fault warning information includes the first fault warning information, and step S420 specifically includes the following steps:

[0084] S510, obtaining a first test result based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix; the first test result includes that none of the elements at the corresponding positions are null values;

[0085] S520, obtaining a second test result based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix; the second test result includes that the element difference at the corresponding position is less than a preset threshold;

[0086] S530: Generate first fault warning information according to the first inspection result and the second inspection result.

[0087] In step S510 , if there is an element in the open circuit voltage difference eigenvalue matrix that is not a null value, and an element in the same position in the open circuit voltage difference eigenvalue reference matrix is ​​also not a null value, the first check result is successful.

[0088] In step S520, if the first test result is successful, the difference between the elements involved in the open circuit voltage difference eigenvalue matrix and the corresponding elements involved in the open circuit voltage difference eigenvalue reference matrix is ​​calculated. If the difference is less than a preset threshold, the second test result is successful.

[0089] In step S530, a first fault warning message is generated based on the first and second test results. Specifically, the first fault warning message is generated based on the sudden change in the open-circuit voltage difference eigenvalues ​​between two consecutive discharge processes. If both the first and second test results are successful, the first fault warning message is generated. The first fault warning message indicates a serious short circuit in the battery. In this case, the cell corresponding to the column of the open-circuit voltage difference eigenvalue matrix in which the element is located issues a warning. The first fault warning message is identified as warning_flag1.

[0090] It should be noted that if a single cell displays warning_flag1 during M1 consecutive discharges, it is considered a valid warning. Where M1 ≥ 1, the present disclosure does not limit the value of M1; those skilled in the art can set it based on actual needs. Determining a valid warning based on the first fault warning information from multiple consecutive discharges can reduce false alarms.

[0091] In some embodiments, as Figure 6 As shown, the battery short circuit fault warning information includes the second fault warning information, and step S140 specifically includes the following steps:

[0092] S610, calculating an open circuit voltage difference eigenvalue long-term evolution matrix based on the open circuit voltage difference eigenvalue matrix;

[0093] S620, calculating the evolution rate of the open circuit voltage difference eigenvalues ​​of the single battery cells based on the long-term evolution matrix of the open circuit voltage difference eigenvalues;

[0094] S630: Generate second fault warning information according to the evolution speed.

[0095] In step S610, a high-end voltage subrange is randomly selected and fixed. If the element in the row corresponding to this subrange in the open-circuit voltage difference eigenvalue matrix during the current discharge process is not null, the value of this row element is added to the latest row of the open-circuit voltage difference eigenvalue long-term evolution matrix, and the start time of this discharge process is stored in a time series. This high-end voltage subrange refers to the interval whose endpoint value is close to the discharge cutoff voltage.

[0096] In step S620, when the number of rows in the long-term evolution matrix of the open-circuit voltage difference eigenvalues ​​is greater than a preset reference value N of the number of rows, the last N rows of elements and the corresponding time series of the corresponding columns in the long-term evolution matrix of the open-circuit voltage difference eigenvalues ​​of each single cell are obtained, and a linear least squares algorithm is performed on the last N rows of elements and the time series to obtain the evolution rate of the open-circuit voltage difference value of the single cell over time. That is, the evolution rate of the single cell is calculated based on the open-circuit voltage difference values ​​of the single cell in N consecutive discharge processes and the corresponding start times of the N discharge processes.

[0097] It should be noted that when the number of rows of the long-term evolution matrix of the open circuit voltage difference eigenvalues ​​is less than or equal to a preset row number reference value N, steps S610 to S630 are not performed.

[0098] In step S630, a second fault warning message is generated based on the evolution rate of the open-circuit voltage difference values ​​during multiple consecutive discharge processes. If the evolution rate exceeds a preset evolution rate threshold, the second fault warning message is generated. The second fault warning message indicates that a micro-short circuit fault has occurred in the battery, and a warning is issued for the battery. The second fault warning message is identified as warning_flag2.

[0099] It should be noted that if a single cell displays warning_flag2 during M2 consecutive discharges, it is considered a valid warning. Where M2 ≥ 1, the present disclosure does not limit the value of M2; those skilled in the art can set it based on actual needs. Using the second fault alarm information from multiple consecutive discharges to determine a valid warning can reduce false alarms.

[0100] In some embodiments, as Figure 7 As shown, in real life, the method for generating battery short circuit fault warning information includes but is not limited to steps S7010 to S7100.

[0101] S7010, determining whether the vehicle is in the driving discharge process, if the determination result is yes, executing steps S7020 to S7100, if the determination result is no, continuing to execute step S7010;

[0102] S7020, identifying a complete driving discharge process data segment;

[0103] S7030, calculating the difference in open circuit voltage of each single battery compared to the average battery at each data sampling point based on the driving discharge process data segment;

[0104] S7040, calculating an open circuit voltage difference eigenvalue matrix of the current discharge process based on the open circuit voltage difference value of each single battery;

[0105] S7050, calling the open circuit voltage difference eigenvalue reference matrix;

[0106] S7060: Perform a battery severe short circuit fault warning based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix;

[0107] S7070, updating the open circuit voltage difference eigenvalue reference matrix according to the open circuit voltage difference eigenvalue matrix of the current discharge process;

[0108] S7080, after S7040, updating the open circuit voltage difference eigenvalue long-term evolution matrix according to the open circuit voltage difference eigenvalue matrix;

[0109] S7090: Provides battery micro-short circuit fault warning based on the long-term evolution matrix of open-circuit voltage difference eigenvalues;

[0110] S7100, identify the next driving discharge process.

[0111] In some embodiments, as Figure 8 As shown, in real life, the method for generating battery short circuit fault warning information includes but is not limited to steps S8010 to S8120.

[0112] S8010, determining whether the vehicle is in the driving discharge process, if the determination result is yes, executing steps S8020 to S8120, if the determination result is no, continuing to execute step S8010;

[0113] S8020, identifying a complete driving discharge process data segment;

[0114] S8030, calculating the difference in open circuit voltage between the single cell and the average cell during the current discharge process;

[0115] S8040, calculating an open circuit voltage difference eigenvalue matrix of the current discharge process based on the open circuit voltage difference value;

[0116] S8050, calling the open circuit voltage difference eigenvalue reference matrix;

[0117] S8060: Perform a battery severe short circuit fault warning based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix;

[0118] S8070, updating the open circuit voltage difference eigenvalue reference matrix according to the open circuit voltage difference eigenvalue matrix;

[0119] S8080, after step S8030, determining whether the current discharge process satisfies the open circuit voltage difference eigenvalue long-term evolution matrix update condition; if the determination result is yes, executing S8090; if the determination result is no, executing S8120;

[0120] S8090, updating the open circuit voltage difference eigenvalue long-term evolution matrix according to the open circuit voltage difference eigenvalue matrix;

[0121] S8100, determining whether the number of rows of the long-term evolution matrix of the open circuit voltage difference eigenvalues ​​meets the early warning analysis condition; if the determination result is yes, executing S8110; if the determination result is no, executing S8120;

[0122] S8110, based on the long-term evolution matrix of the open circuit voltage difference eigenvalues, provides battery micro-short circuit fault warning;

[0123] S8120, identifying the next driving discharge process.

[0124] By providing a battery short-circuit fault warning based on driving discharge data, it is possible to promptly detect whether any single cell in the vehicle's power battery system has experienced a significant, abnormal drop in voltage compared to the rest of the cells, thereby promptly identifying whether any single cell has experienced a severe short-circuit fault and accurately locating the faulty battery. It can also detect whether any single cell's voltage has experienced a long-term, slow decrease compared to the rest of the cells, thereby promptly identifying whether any single cell has experienced a micro-short circuit or high self-discharge fault and accurately locating the faulty battery. By identifying single cell short-circuit faults and issuing safety warnings, it can guide manufacturers to replace faulty batteries as soon as possible, preventing thermal runaway accidents in new energy vehicles and improving vehicle safety.

[0125] The method for generating battery short-circuit fault warning information proposed in the embodiments of the present disclosure is applied to a discharge process. Discharge data of a discharge process is obtained, where the discharge data includes a sampling time, a discharge current, and the voltages of at least two single cells. The discharge data is sampled according to the sampling time to obtain at least two data sampling points. The open-circuit voltage difference value of each single cell compared to the average cell at each data sampling point is calculated based on the discharge current and the voltage of the single cell. An open-circuit voltage difference eigenvalue matrix is ​​calculated based on the open-circuit voltage difference value. The open-circuit voltage difference eigenvalue matrix is ​​used to generate battery short-circuit fault warning information during the discharge process. This method enables real-time battery short-circuit fault diagnosis and warning. This method not only solves the problem that the cloud cannot directly identify the SOC difference between each single cell using discharge process data, but also does not require the support of the battery OCV-SOC curve, reducing computational complexity and resource requirements. It also solves the high false alarm rate caused by the influence of discharge current, temperature, and sampling when currently performing short-circuit fault diagnosis on the cloud using voltage difference.

[0126] The embodiment of the present disclosure also provides a battery short circuit fault warning information generation device, which is applied to the discharge process, such as Figure 9 As shown, the above-mentioned battery short circuit fault warning information generation method can be implemented. The device includes: a first acquisition module 910, a first calculation module 920, a second calculation module 930 and a fault warning information generation module 940, wherein the first acquisition module 910 is used to obtain discharge data of a discharge process, and the discharge data includes sampling time, discharge current and voltage of at least two single cells; the first calculation module 920 is used to calculate the open circuit voltage difference value of each single cell compared with the average cell at each data sampling point based on the discharge current and the voltage of the single cell; the second calculation module 930 is used to calculate the open circuit voltage difference eigenvalue matrix based on the open circuit voltage difference value of each single cell at each data sampling point; the fault warning information generation module 940 is used to generate battery short circuit fault warning information during the discharge process based on the open circuit voltage difference eigenvalue matrix. The battery short circuit fault warning information generation device of the disclosed embodiment is used to execute the battery short circuit fault warning information generation method of the above-mentioned embodiment. Its specific processing process is the same as that of the battery short circuit fault warning information generation method of the above-mentioned embodiment, and will not be repeated here.

[0127] The battery short-circuit fault warning information generation device proposed in the embodiments of the present disclosure, by implementing the above-mentioned battery short-circuit fault warning information generation method, can obtain discharge data of a discharge process. The discharge data includes a sampling time, a discharge current, and the voltages of at least two single cells. The discharge data is sampled according to the sampling time to obtain at least two data sampling points. The open-circuit voltage difference value of each single cell compared to the average cell at each data sampling point is calculated based on the discharge current and the voltage of the single cell. An open-circuit voltage difference eigenvalue matrix is ​​calculated based on the open-circuit voltage difference value. The open-circuit voltage difference eigenvalue matrix is ​​used to generate battery short-circuit fault warning information during the discharge process. This enables real-time battery short-circuit fault diagnosis and warning. This not only solves the problem that the cloud cannot directly identify the SOC difference between each single cell using discharge process data, but also does not require the support of the battery OCV-SOC curve, reducing computational complexity and resource requirements. It also solves the high false alarm rate caused by the influence of discharge current, temperature, and sampling when currently performing short-circuit fault diagnosis on the cloud using voltage difference.

[0128] The present disclosure also provides a computer device, including:

[0129] at least one processor, and

[0130] a memory communicatively connected to at least one processor; wherein,

[0131] The memory stores instructions, which are executed by at least one processor so that the at least one processor implements a method as described in any one of the embodiments of the first aspect of the present application when executing the instructions.

[0132] The following combination Figure 10 The hardware structure of the computer device is described in detail. The computer device includes: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040 and a bus 1050.

[0133] The processor 1010 may be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute relevant programs to implement the technical solutions provided by the embodiments of the present disclosure.

[0134] The memory 1020 can be implemented in the form of ROM (Read Only Memory), static storage device, dynamic storage device, or RAM (Random Access Memory). The memory 1020 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1020 and is called by the processor 1010 to execute the battery short circuit fault warning information generation method of the embodiment of the present disclosure;

[0135] Input / output interface 1030, used to implement information input and output;

[0136] Communication interface 1040, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.); and

[0137] bus 1050 , which transmits information between various components of the device (e.g., processor 1010 , memory 1020 , input / output interface 1030 , and communication interface 1040 );

[0138] The processor 1010 , the memory 1020 , the input / output interface 1030 , and the communication interface 1040 are connected to each other in communication within the device via a bus 1050 .

[0139] An embodiment of the present disclosure further provides a storage medium, which is a computer-readable storage medium and stores computer-executable instructions. The computer-executable instructions are used to enable a computer to execute the battery short circuit fault warning information generation method of the embodiment of the present disclosure.

[0140] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0141] The embodiments described in the embodiments of the present disclosure are intended to more clearly illustrate the technical solutions of the embodiments of the present disclosure and do not constitute a limitation on the technical solutions provided by the embodiments of the present disclosure. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present disclosure are also applicable to similar technical problems.

[0142] It will be understood by those skilled in the art that Figures 1 to 8 The technical solutions shown in the figures do not constitute a limitation on the embodiments of the present disclosure, and may include more or fewer steps than those shown in the figures, or a combination of certain steps, or different steps.

[0143] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0144] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0145] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0146] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0147] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0148] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0149] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0150] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0151] The preferred embodiments of the present disclosure are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present disclosure. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present disclosure should be within the scope of the present disclosure.

Claims

1. A method for generating battery short circuit fault warning information, applied to the discharge process, characterized in that: include: Acquire discharge data of a discharge process, wherein the discharge data includes sampling time, discharge current, and voltages of at least two single cells; Calculating, based on the discharge current and the voltage of the single battery, a difference in open circuit voltage of each single battery compared to an average battery at each data sampling point; Calculating an open circuit voltage difference eigenvalue matrix according to the open circuit voltage difference value of each of the single cells at each of the data sampling points; generating battery short circuit fault warning information during the discharge process according to the open circuit voltage difference eigenvalue matrix; The step of calculating an open circuit voltage difference eigenvalue matrix based on the open circuit voltage difference value of each single cell at each data sampling point includes: Dividing the operating voltage range of the cell voltage into at least two sub-ranges, the operating voltage range being a range from a discharge cut-off voltage to a charge cut-off voltage; classifying each data sampling point into a plurality of sub-ranges based on an average open circuit voltage value of the cell at each data sampling point; calculating an open circuit voltage difference eigenvalue of the cell in the sub-range based on an open circuit voltage difference value of the cell at the data sampling point in the sub-range; and calculating an open circuit voltage difference eigenvalue matrix based on the open circuit voltage difference eigenvalue of the cell in the sub-range; Generating battery short circuit fault warning information during the discharge process according to the open circuit voltage difference eigenvalue matrix includes: Obtaining an open circuit voltage difference eigenvalue reference matrix; generating the battery short circuit fault warning information according to the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix; The battery short circuit fault warning information includes first fault warning information, and generating the battery short circuit fault warning information according to the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix includes: Obtaining a first test result based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix; the first test result includes that none of the elements at the corresponding positions are null values; obtaining a second test result based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix; the second test result includes that the difference between the elements at the corresponding positions is less than a preset threshold; and generating first fault warning information based on the first test result and the second test result; The battery short circuit fault warning information includes second fault warning information, and generating the battery short circuit fault warning information during the discharge process according to the open circuit voltage difference eigenvalue matrix includes: Based on the open circuit voltage difference eigenvalue matrix, a long-term evolution matrix of the open circuit voltage difference eigenvalues ​​is calculated; based on the long-term evolution matrix of the open circuit voltage difference eigenvalues, an evolution speed of the open circuit voltage difference eigenvalues ​​of the single battery cells is calculated; and based on the evolution speed, the second fault warning information is generated.

2. The method according to claim 1, characterized in that Calculating the difference in open circuit voltage of each single cell compared to an average cell at each data sampling point based on the discharge current and the voltage of the single cell includes: Calculating a first open-circuit voltage of the single cell at the data sampling point and a second open-circuit voltage of the average cell at the data sampling point according to the discharge current at the data sampling point and the voltage at the data sampling point; The open circuit voltage difference value of the single battery at the data sampling point is calculated according to the first open circuit voltage and the second open circuit voltage.

3. The method according to claim 2, characterized in that The first open-circuit voltage and the second open-circuit voltage are calculated using extended Kalman filtering or recursive least squares method.

4. A fault warning information generating device, applied to the discharge process, characterized in that: include: A first acquisition module is used to acquire discharge data of a discharge process, wherein the discharge data includes sampling time, discharge current, and voltages of at least two single cells; A first calculation module is configured to calculate, based on the discharge current and the voltage of the single battery, a difference in open circuit voltage between each single battery and an average battery at each data sampling point; A second calculation module is configured to calculate an open circuit voltage difference eigenvalue matrix according to the open circuit voltage difference value of each single cell at each data sampling point; A fault warning information generation module, configured to generate battery short circuit fault warning information during discharge according to the open circuit voltage difference eigenvalue matrix; The step of calculating an open circuit voltage difference eigenvalue matrix based on the open circuit voltage difference value of each single cell at each data sampling point includes: Dividing the operating voltage range of the cell voltage into at least two sub-ranges, the operating voltage range being a range from a discharge cut-off voltage to a charge cut-off voltage; classifying each data sampling point into a plurality of sub-ranges based on an average open circuit voltage value of the cell at each data sampling point; calculating an open circuit voltage difference eigenvalue of the cell in the sub-range based on an open circuit voltage difference value of the cell at the data sampling point in the sub-range; and calculating an open circuit voltage difference eigenvalue matrix based on the open circuit voltage difference eigenvalue of the cell in the sub-range; Generating battery short circuit fault warning information during the discharge process according to the open circuit voltage difference eigenvalue matrix includes: Obtaining an open circuit voltage difference eigenvalue reference matrix; generating the battery short circuit fault warning information according to the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix; The battery short circuit fault warning information includes first fault warning information, and generating the battery short circuit fault warning information according to the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix includes: Obtaining a first test result based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix; the first test result includes that none of the elements at the corresponding positions are null values; obtaining a second test result based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix; the second test result includes that the difference between the elements at the corresponding positions is less than a preset threshold; and generating first fault warning information based on the first test result and the second test result; The battery short circuit fault warning information includes second fault warning information, and generating the battery short circuit fault warning information during the discharge process according to the open circuit voltage difference eigenvalue matrix includes: Based on the open circuit voltage difference eigenvalue matrix, a long-term evolution matrix of the open circuit voltage difference eigenvalues ​​is calculated; based on the long-term evolution matrix of the open circuit voltage difference eigenvalues, an evolution speed of the open circuit voltage difference eigenvalues ​​of the single battery cells is calculated; and based on the evolution speed, the second fault warning information is generated.

5. A computer device, characterized in that: The computer device includes a memory and a processor, wherein the memory stores a program, and when the program is executed by the processor, the processor is configured to perform: The method according to any one of claims 1 to 3.

6. A storage medium, wherein the storage medium is a computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program. When the computer program is executed by a computer, the computer is configured to: The method according to any one of claims 1 to 3.

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