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 charging process and belong to the field of fault diagnosis technology. The method includes: obtaining charging data from a single charging process, wherein the charging data includes sampling time, charging current, and voltages of at least two single cells; calculating the difference in open-circuit voltage of each single cell compared to the average battery at each data sampling point based on the charging current and the voltage of the single cells; calculating an 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 charging process based on the open-circuit voltage difference eigenvalue matrix. The method can perform real-time analysis of battery charging process data uploaded to the cloud to perform battery short-circuit fault diagnosis and warning.

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, methods that use single-cell voltage differentials for battery short-circuit fault diagnosis and early warning are susceptible to false alarms due to current, temperature, and sampling. To reduce false alarms, the early warning threshold is generally set high, and an early warning is only issued when the voltage differential caused by a single-cell short circuit is extremely large, resulting in delayed fault diagnosis. Furthermore, methods that use the chargeable capacity of a single cell for battery short-circuit fault diagnosis and early warning have strict data requirements and can only be analyzed after the charging process is completed, making real-time diagnosis and early warning impossible. 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 can perform real-time analysis of battery charging process data uploaded to the cloud to 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 charging process and includes:

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

[0006] Calculating, based on the charging 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 charging 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 charging current and the voltage of the single cell includes:

[0010] Calculate 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 according to the charging current, the voltage, and the preset internal resistance;

[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, calculating the first open-circuit voltage of the single battery at the data sampling point and the second open-circuit voltage of the average battery at the data sampling point based on the charging current, the voltage, and a preset internal resistance includes:

[0013] Identifying a charging current mutation point according to the mutation value of the charging current;

[0014] Calculating the preset internal resistance according to the charging current at the charging current mutation point and the voltage at the charging current mutation point;

[0015] 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 are calculated based on the charging current at the data sampling point, the voltage at the data sampling point and the preset internal resistance.

[0016] 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:

[0017] 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;

[0018] 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;

[0019] 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;

[0020] 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.

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

[0022] Obtain an open circuit voltage difference eigenvalue reference matrix;

[0023] 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.

[0024] 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:

[0025] 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;

[0026] 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;

[0027] First fault warning information is generated according to the first inspection result and the second inspection result.

[0028] 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 charging process according to the open circuit voltage difference eigenvalue matrix further includes:

[0029] Calculating an open circuit voltage difference eigenvalue long-term evolution matrix based on the open circuit voltage difference eigenvalue matrix;

[0030] 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;

[0031] The second fault warning information is generated according to the evolution speed.

[0032] 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 charging process and includes:

[0033] A first acquisition module is used to acquire charging data of a charging process, wherein the charging data includes a sampling time, a charging current, and voltages of at least two single cells;

[0034] A first calculation module is configured to calculate, based on the charging 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;

[0035] 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;

[0036] The fault warning information generation module is used to generate battery short circuit fault warning information during the charging process according to the open circuit voltage difference eigenvalue matrix.

[0037] 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.

[0038] 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.

[0039] 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 charging process. By acquiring charging data of a charging process, the charging data includes a sampling time, a charging current, and the voltage of at least two single cells, the charging data is sampled according to the sampling time to obtain at least two data sampling points, and 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 charging 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 charging process, thereby enabling real-time battery short-circuit fault diagnosis and warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] 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;

[0041] Figure 2 yes Figure 1 Flowchart of step S120 in FIG.

[0042] Figure 3 yes Figure 2 Flowchart of step S210 in FIG.

[0043] Figure 4 yes Figure 1 Flowchart of step S130 in FIG.

[0044] Figure 5 yes Figure 1 The first flow chart of step S140 in FIG.

[0045] Figure 6 yes Figure 5 Flowchart of step S520 in FIG.

[0046] Figure 7 yes Figure 1 A second flow chart of step S140 in FIG.

[0047] Figure 8 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;

[0048] Figure 9 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;

[0049] Figure 10 This is a module structure diagram of a device for generating battery short circuit fault warning information provided by an embodiment of the present disclosure;

[0050] Figure 11 It is a schematic diagram of the hardware structure of the computer device provided in the embodiment of the present disclosure. DETAILED DESCRIPTION

[0051] 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.

[0052] 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.

[0053] 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.

[0054] Currently, short-circuit fault diagnosis and early warning methods based on battery charging 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 available charge capacity of individual cells for fault diagnosis and early warning. This involves using battery charging data to calculate the amount of charge that can still be charged into each cell after the battery system is fully charged, to determine whether a fault has occurred. If the available charge capacity of a particular cell exceeds a preset threshold, or if the rate of change in the available charge capacity over several charging cycles exceeds a preset threshold, an early warning is issued for that cell. However, methods using cell voltage differentials for fault early warning are significantly affected by charging current, temperature, and sampling time, making them prone to false alarms. Furthermore, to minimize false alarms, the threshold is typically set high, so a short circuit fault is only considered and an early warning is issued when the voltage differential is very large, resulting in a certain delay in fault identification. The method of using the rechargeable capacity to conduct fault warning judgment can only calculate the rechargeable capacity after the battery system is fully charged, and the charging data requirements are relatively strict. In actual practice, it is impossible for the charging data of each charging process to meet the calculation requirements. Moreover, this method can only perform fault analysis at the end of charging, and cannot perform fault diagnosis and warning in real time. The timeliness of short-circuit fault diagnosis is not strong.

[0055] 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 can diagnose battery short-circuit faults through the open-circuit voltage difference values ​​of single cells, and can perform short-circuit fault analysis and warning in real time.

[0056] 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.

[0057] 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.

[0058] S110, acquiring charging data of a charging process, the charging data including sampling time, charging current, and voltages of at least two single cells;

[0059] 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 charging current and the voltage of the single cell;

[0060] 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;

[0061] S140 , generating battery short circuit fault warning information during the charging process according to the open circuit voltage difference eigenvalue matrix.

[0062] In step S110, the charging data may be charging data from 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 charging data for a single charging process refers to a complete parking charging process from the start to the end of charging. The charging data for a single charging process includes the sampling time, charging current, and the voltages of at least two cells. The charging current and the voltages of each cell vary with charging time.

[0063] In step S120, charging data is first sampled according to the sampling time to obtain at least two data sampling points. Then, based on the charging current and the voltage of the individual cells, the difference in open circuit voltage 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 open circuit voltage difference of each individual cell compared to the average cell at each data sampling point, the open circuit voltage difference between the individual cells in series can be identified in real time.

[0064] In step S130 and step S140, the open circuit voltage difference value of the single cell is used to approximately characterize 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 charging data uploaded to the cloud can be analyzed in real time, which has a strong timeliness and can detect problems as early as possible, avoiding the cloud being unable to use charging 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 resource requirements. SOC (State of Charge) refers to the state of charge, which represents the ratio of the remaining capacity of the battery to the capacity of the battery when it is fully charged, and its value range is [0, 1]. When the SOC value is 0, it means that the battery is fully discharged. When the SOC value is 1, it means that the battery is fully charged.

[0065] In some embodiments, as Figure 2 As shown, step S120 specifically includes the following steps:

[0066] S210, calculating a first open circuit voltage of a single cell at a data sampling point and a second open circuit voltage of an average cell at the data sampling point based on the charging current, voltage, and a preset internal resistance;

[0067] 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.

[0068] In step S210, a Rint equivalent circuit model based on a lithium-ion battery is established according to the charging current, voltage, and preset internal resistance to calculate the first open circuit voltage of the single battery at the data sampling point and the second open circuit voltage of the average battery at the data sampling point.

[0069] 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.

[0070] In some embodiments, as Figure 3 As shown, step S210 specifically includes the following steps:

[0071] S310, identifying a charging current mutation point according to a mutation value of the charging current;

[0072] S320, calculating a preset internal resistance based on the charging current and the voltage at the charging current mutation point;

[0073] S330 , 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 according to the charging current at the data sampling point, the voltage at the data sampling point, and a preset internal resistance.

[0074] In step S310, the charging current mutation point of this charging process is identified based on the mutation value of the charging current of this charging process. The mutation value of the charging current is the difference between the charging current at a data sampling point and the charging current at the previous data sampling point. If the mutation value is greater than or equal to a preset reference value, then the data sampling point is the charging current mutation point. It should be noted that those skilled in the art can set the reference value according to actual needs, for example, the reference value is 10. If the data sampling point is the kth data sampling point, the charging current is I k The last data sampling point is the k-1th data sampling point, and the charging current is I k-1 . If |I k -I k-1 |≥10,k≥2, then the kth data sampling point is the current mutation point.

[0075] In step S320, the charging current mutation point is the kth data sampling point, and the charging current at the charging current mutation point is I k , the voltage of the i-th single cell at the charging current mutation point is V k,i , where i≥2. The charging current at the last data sampling point is I k-1 , the voltage of the i-th single cell at the last data sampling point is V k-1,i According to the charging current I at the charging current mutation point k , the voltage V at the charging current mutation point k,i , the charging current I at the previous data sampling point k-1 , the voltage V at the previous data sampling point k-1,i , calculate the internal resistance R of the single cell at the current mutation point k,i The calculation method is shown in formula (1):

[0076] R k,i =|V k,i -V k-1,i | / |I k -I k-1 | (1)

[0077] It should be noted that the embodiments of the present disclosure do not further limit the specific values ​​of k and i.

[0078] Usually, there are multiple current mutation points in a charging process, and the internal resistance of a single battery can be calculated at each current mutation point. The internal resistance of a single battery, such as the i-th single battery, at each current mutation point is regarded as a set and expressed as {R k,i}, where i is a fixed value. The average or median of the internal resistance of the single cell calculated at all current mutation points is used as the internal resistance of the single cell during the current charging process. That is, the average or median of the internal resistance of a single cell at all current mutation points is used as the preset internal resistance, and the preset internal resistance is stored. For each single cell, the average or median of the internal resistance of the single cell calculated at each current mutation point is used as the preset internal resistance of each single cell.

[0079] It should be noted that if no current mutation point is identified during this charging process, the internal resistance of the single cell in the previous charging process will be used as the internal resistance of this charging process, that is, the preset internal resistance of the single cell in the previous charging process will be used as the preset internal resistance of the single cell in this charging process.

[0080] It should be noted that if no valid preset internal resistance of the single battery is calculated during the first charging process, the preset internal resistance of each single battery is set to an initial value set manually in advance, such as 0.5 mΩ.

[0081] In step S330, a Rint equivalent circuit model based on the lithium-ion battery is established based on the charging current at the data sampling point, the voltage at the data sampling point, and the preset internal resistance, and the first open-circuit voltage and the second open-circuit voltage are calculated based on the equivalent circuit model. The Rint equivalent circuit model equates the battery to a series connection of an ideal voltage source Uoc and a resistor R, with the current represented by I and the external voltage represented by V. The Rint equivalent circuit model is shown in formula (2):

[0082] Uoc=V+IR (2)

[0083] Among them, the ideal voltage source is the open circuit voltage of the battery.

[0084] Let the preset internal resistance be represented by R i , according to the charging current I at the data sampling point k , the voltage of the single cell at the data sampling point V k,i And the preset internal resistance R i A first Rint equivalent circuit model is established, and the first open circuit voltage of the single cell at the data sampling point is calculated based on the first Rint equivalent circuit model. The calculation method of the first open circuit voltage is shown in formula (3):

[0085] OCV k,i =V k,i +I k R i (3)

[0086] Let the preset internal resistance of all single cells be expressed as {R i}, according to the preset internal resistance {R i}Calculate the average battery internal resistance R ave , that is, all single cells have a preset internal resistance {R i The average or median value of the average battery internal resistance R ave According to the voltage V of all single cells at a certain data sampling point, such as the kth data sampling point k,i , calculate the average battery voltage V at the data sampling point k,ave , where k is a fixed value, that is, the average or median value of the voltage of all single cells at the data sampling point is taken as the voltage V of the average cell at the data sampling point k,ave According to the charging current I at the data sampling point k , the average battery voltage V at the data sampling point k,ave , average battery internal resistance R ave A second Rint equivalent circuit model is established, and the second open circuit voltage of the average battery at the data sampling point is calculated based on the second Rint equivalent circuit model. The calculation method of the second open circuit voltage is shown in formula (4):

[0087] OCV k,ave =V k,ave +I k R ave (4)

[0088] In some embodiments, as Figure 4 As shown, step S130 specifically includes the following steps:

[0089] S410, dividing the operating voltage range of the single battery into at least two sub-ranges, where the operating voltage range is a range from a discharge cut-off voltage to a charge cut-off voltage;

[0090] S420, 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;

[0091] S430, 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;

[0092] S440 , calculating an open circuit voltage difference eigenvalue matrix based on the open circuit voltage difference eigenvalues ​​of the single battery cells in the subintervals.

[0093] In step S410, 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.

[0094] In step S420, 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 charging medium voltage, that is, in the order of the used voltage intervals. 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.

[0095] In step S430, 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 for the cell in the subinterval is calculated. This average open circuit voltage difference value is used as the open circuit voltage difference characteristic value for the cell in the subinterval. At all data sampling points within each subinterval, the average open circuit voltage difference values ​​corresponding to the individual cells are calculated to calculate the open circuit voltage difference characteristic value for each cell in each subinterval.

[0096] In step S440, 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 charging process, the row of the matrix corresponding to that voltage subrange is left blank.

[0097] In some embodiments, as Figure 5 As shown, step S140 specifically includes the following steps:

[0098] S510, obtaining an open circuit voltage difference eigenvalue reference matrix;

[0099] S520 , 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.

[0100] In step S510, the open circuit voltage difference eigenvalue reference matrix for the current charging process is calculated based on the open circuit voltage difference eigenvalue matrix for the previous charging process. That is, all non-null elements in the open circuit voltage difference eigenvalue matrix for the previous charging process are used to replace the elements of 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 charging process is stored for use in updating the open circuit voltage difference eigenvalue reference matrix for the next charging process. The open circuit voltage difference eigenvalue matrix for the current charging process is stored by clearing the open circuit voltage difference eigenvalue matrix for the previous charging process.

[0101] It should be noted that no battery short-circuit fault warning analysis is performed during the first charging process. Only the open-circuit voltage difference eigenvalue matrix of this charging process is stored and used as the reference matrix for the open-circuit voltage difference eigenvalues ​​of the subsequent charging process. Warning judgment is required for the second charging process and subsequent charging processes, except for the first charging process.

[0102] In step S520, 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.

[0103] In some embodiments, as Figure 6 As shown, the battery short circuit fault warning information includes the first fault warning information, and step S520 specifically includes the following steps:

[0104] S610, 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;

[0105] S620, 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;

[0106] S630: Generate first fault warning information according to the first inspection result and the second inspection result.

[0107] In step S610 , 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.

[0108] In step S620, 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.

[0109] In step S630, 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 charging 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 severe short circuit in the battery. In this case, a warning is issued for the battery cell corresponding to the column of the open-circuit voltage difference eigenvalue matrix where the element is located. The first fault warning message is identified as warning_flag1.

[0110] It should be noted that if a single battery cell displays warning_flag1 during M1 consecutive charging cycles, 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. Using the first fault alarm information from multiple consecutive charging processes to determine a valid warning can reduce false alarms.

[0111] In some embodiments, as Figure 7 As shown, the battery short circuit fault warning information includes the second fault warning information, and step S140 specifically includes the following steps:

[0112] S710, calculating an open circuit voltage difference eigenvalue long-term evolution matrix based on the open circuit voltage difference eigenvalue matrix;

[0113] S720, 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;

[0114] S730: Generate second fault warning information according to the evolution speed.

[0115] In step S710, 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 charging 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 charging process is stored in a time series. This high-end voltage subrange refers to the interval whose endpoint value is close to the charging cutoff voltage.

[0116] In step S720, when the number of rows of 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 row elements and the corresponding time series of the corresponding column in the long-term evolution matrix of the open-circuit voltage difference eigenvalues ​​of each single cell are obtained, and the linear least squares algorithm is used to fit the last N row 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 value of the single cell in N consecutive charging processes and the corresponding start time of the N charging processes.

[0117] 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 S720 to S730 are not performed.

[0118] In step S730, a second fault warning message is generated based on the evolution rate of the open-circuit voltage difference values ​​during multiple consecutive charging 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.

[0119] It should be noted that if a single battery cell displays warning_flag2 during M2 consecutive charging cycles, 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 charging processes to determine a valid warning can reduce false alarms.

[0120] In some embodiments, as Figure 8 As shown, in the actual battery short circuit fault analysis and warning process, the battery short circuit fault warning information generation method includes but is not limited to steps S8010 to S8100.

[0121] S8010, determining whether the vehicle is in the parking charging process, if the determination result is yes, executing steps S8020 to S8100, if the determination result is no, continuing to execute step S8010;

[0122] S8020, identifying a complete parking charging process data segment;

[0123] S8030, calculating, based on the parking charging process data segment, a difference in open circuit voltage of each single battery compared to an average battery at each data sampling point;

[0124] S8040, calculating an open circuit voltage difference eigenvalue matrix of the current charging process based on the open circuit voltage difference value of each single battery;

[0125] S8050, calling the open circuit voltage difference eigenvalue reference matrix;

[0126] 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;

[0127] S8070, updating the open circuit voltage difference eigenvalue reference matrix according to the open circuit voltage difference eigenvalue matrix of the current charging process;

[0128] S8080, after step S8040, updating the open circuit voltage difference eigenvalue long-term evolution matrix according to the open circuit voltage difference eigenvalue matrix;

[0129] S8090: Provides battery micro-short circuit fault warning based on the long-term evolution matrix of open-circuit voltage difference eigenvalues;

[0130] S8100, identify the next parking charging process.

[0131] In some embodiments, as Figure 9 As shown, in real life, the method for generating battery short circuit fault warning information includes but is not limited to steps S9010 to S9140.

[0132] S9010, determining whether the vehicle is in the parking charging process, if the determination result is yes, executing steps S9020 to S9140, if the determination result is no, continuing to execute step S9010;

[0133] S9020, identifying a complete parking charging process data segment;

[0134] S9030, determining whether there is a current mutation point that meets the memory calculation condition during the current charging process; if the determination result is yes, executing step S9050; if the determination result is no, executing step S9040;

[0135] S9040: Recall the single cell internal resistance and average battery internal resistance calculated during the previous charging process and use them in subsequent calculations.

[0136] S9050: Calculate the internal resistance of the single battery and the average internal resistance of the battery during the current charging process and store them;

[0137] S9060, calculating the difference in open circuit voltage between the single cell and the average cell;

[0138] S9070, calculating an open circuit voltage difference eigenvalue matrix of the current charging process based on the open circuit voltage difference values;

[0139] S9080, calling the open circuit voltage difference eigenvalue reference matrix;

[0140] S9090: Determine a serious battery short circuit fault based on the open circuit voltage difference eigenvalue matrix and the open circuit voltage difference eigenvalue reference matrix and provide a warning message;

[0141] S9100, updating an open circuit voltage difference eigenvalue reference matrix according to the open circuit voltage difference eigenvalue matrix;

[0142] S9110, after step S9060, determining whether the current charging process satisfies the open circuit voltage difference eigenvalue long-term evolution matrix update condition; if the determination result is yes, executing S9120; if the determination result is no, executing S9150;

[0143] S9120, updating the open circuit voltage difference eigenvalue long-term evolution matrix according to the open circuit voltage difference eigenvalue matrix;

[0144] S9130, 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 S9140; if the determination result is no, executing S9150;

[0145] S9140, based on the long-term evolution matrix of the open-circuit voltage difference eigenvalues, provides battery micro-short circuit fault warning;

[0146] S9150, identifying the next parking charging process.

[0147] By providing battery short-circuit fault warnings based on parking and charging 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 shown 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.

[0148] The method for generating battery short-circuit fault warning information proposed in the embodiments of the present disclosure obtains charging data of a charging process, where the charging data includes a sampling time, a charging current, and the voltages of at least two single cells. The charging 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 charging 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 charging process. This method 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 charging 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 problem of a high false alarm rate caused by the influence of charging current, temperature, and sampling when currently performing short-circuit fault diagnosis on the cloud using voltage difference.

[0149] The present disclosure also provides a device for generating battery short circuit fault warning information, which is applied to the charging process, such as Figure 10As shown, the above-mentioned battery short circuit fault warning information generation method can be implemented. The device includes: a first acquisition module 1010, a first calculation module 1020, a second calculation module 1030 and a fault warning information generation module 1040, wherein the first acquisition module 1010 is used to obtain charging data of a charging process, and the charging data includes sampling time, charging current and voltage of at least two single cells; the first calculation module 1020 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 charging current and the voltage of the single cell; the second calculation module 1030 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 1040 is used to generate battery short circuit fault warning information during the charging 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.

[0150] 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 charging data of a single charging process. The charging data includes a sampling time, a charging current, and the voltages of at least two single cells. The charging 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 battery at each data sampling point is calculated based on the charging 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 charging process. The battery short-circuit fault diagnosis and warning can be performed in real time. This not only solves the problem that the cloud cannot directly identify the SOC difference between each single cell using charging 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 charging current, temperature, and sampling when currently performing short-circuit fault diagnosis on the cloud using voltage difference.

[0151] The present disclosure also provides a computer device, including:

[0152] at least one processor, and

[0153] a memory communicatively connected to at least one processor; wherein,

[0154] 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.

[0155] The following combination Figure 11 The hardware structure of the computer device is described in detail. The computer device includes: a processor 1110 , a memory 1120 , an input / output interface 1130 , a communication interface 1140 , and a bus 1150 .

[0156] The processor 1110 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.

[0157] The memory 1120 can be implemented in the form of ROM (Read Only Memory), static storage device, dynamic storage device, or RAM (Random Access Memory). The memory 1120 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 1120 and is called by the processor 1110 to execute the battery short circuit fault warning information generation method of the embodiment of the present disclosure;

[0158] Input / output interface 1130, used to implement information input and output;

[0159] Communication interface 1140, 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

[0160] bus 1150 , which transmits information between various components of the device (e.g., processor 1110 , memory 1120 , input / output interface 1130 , and communication interface 1140 );

[0161] The processor 1110 , the memory 1120 , the input / output interface 1130 , and the communication interface 1140 are communicatively connected to each other within the device via a bus 1150 .

[0162] 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.

[0163] 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.

[0164] 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.

[0165] It will be understood by those skilled in the art that Figures 1 to 9 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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 charging process, characterized in that: include: Acquire charging data of a charging process, wherein the charging data includes sampling time, charging current, and voltages of at least two single cells; Calculating, based on the charging 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 charging 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 single cell 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 battery at each data sampling point; calculating an open circuit voltage difference eigenvalue of the single cell in the sub-range based on an open circuit voltage difference value of the single 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 single cell in the sub-range; Generating battery short circuit fault warning information during charging 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 the generating of the battery short circuit fault warning information during the charging process according to the open circuit voltage difference eigenvalue matrix further 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 charging current and the voltage of the single cell includes: Calculate 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 according to the charging current, the voltage, and the preset internal resistance; 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 step of calculating the first open circuit voltage of the single battery at the data sampling point and the second open circuit voltage of the average battery at the data sampling point based on the charging current, the voltage, and a preset internal resistance includes: Identifying a charging current mutation point according to the mutation value of the charging current; Calculating the preset internal resistance according to the charging current at the charging current mutation point and the voltage at the charging current mutation point; 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 are calculated based on the charging current at the data sampling point, the voltage at the data sampling point and the preset internal resistance.

4. A battery short circuit fault warning information generation device, applied to the charging process, characterized in that: include: A first acquisition module is used to acquire charging data of a charging process, wherein the charging data includes a sampling time, a charging current, and voltages of at least two single cells; A first calculation module is configured to calculate, based on the charging 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; 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 generating module, configured to generate battery short circuit fault warning information during charging 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 single cell 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 battery at each data sampling point; calculating an open circuit voltage difference eigenvalue of the single cell in the sub-range based on an open circuit voltage difference value of the single 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 single cell in the sub-range; Generating battery short circuit fault warning information during charging 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 the generating of the battery short circuit fault warning information during the charging process according to the open circuit voltage difference eigenvalue matrix further 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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