Vehicle-mounted power battery fault diagnosis method and device

Abstract

The invention relates to a vehicle-mounted power battery fault diagnosis method and device. The method comprises the following steps: collecting relevant parameters of a battery in a preset period and cleaning the battery, wherein the relevant parameters of the battery at least comprise current; calculating an accumulated capacity based on a preset period and the battery related parameters; vehicle operation states are divided based on the current, wherein the vehicle operation states comprise a charging stage, a parking stage and a driving stage; performing fault diagnosis on the battery based on the charge consistency; the charging and discharging capacity of each vehicle in the running state is calculated according to the starting and ending periods of the running stage, the parking stage and the charging stage, and the capacity retention ratio of a battery is calculated; and performing fault diagnosis on the battery based on the capacity retention ratio and the charge consistency. By adopting the method, vehicle information can be acquired in real time, key indicators of battery performance changes can be accurately captured, various fault types can be identified, the whole vehicle can be monitored more comprehensively, and timeliness, comprehensiveness and effectiveness of fault diagnosis are ensured.

Description

Technical Field

[0001] The present application relates to the technical field of battery fault diagnosis, and in particular to a method and device for diagnosing vehicle-mounted power battery faults. Background Art

[0002] Lithium-ion batteries are widely used in electric vehicles due to their high energy density, lack of memory effect, excellent charge and discharge performance, and high durability. However, with the continued development of electric vehicles, battery safety incidents have become more frequent, causing significant financial losses and posing a serious threat to personal safety. Consequently, battery safety and durability have attracted increasing attention. To accurately assess the condition of in-vehicle batteries, metrics such as consistency and state of health (SOH) have been defined.

[0003] The consistency of power batteries is a key metric for evaluating the overall performance and stability of a battery pack. Automotive power batteries consist of dozens to thousands of cells connected in series or parallel. However, the total capacity of a battery pack depends on the lowest-capacity single cell in the actual lithium-ion battery pack. Inconsistencies in the initial conditions and operating conditions of individual cells can exacerbate battery pack inconsistencies, shortening service life and accelerating degradation of capacity and power performance. Therefore, power battery consistency can provide safety early warnings for electric vehicles, ensuring timely screening of defective cells and preventing thermal runaway accidents.

[0004] The state of health (SOH) of a power battery is an important indicator of battery durability and health. The ratio of a power battery's latest capacity to its initial capacity is often used to characterize its SOH. Therefore, achieving accurate and reliable battery SOH prediction is crucial for improving electric vehicle safety and alleviating public concerns about electric vehicle safety.

[0005] However, the current power battery fault diagnosis method needs to detect different battery parameters when detecting different battery indicators, and multiple battery indicators corresponding to power battery faults are abnormal. The existing power battery fault diagnosis cannot diagnose all types of faults of vehicle power batteries at one time. Summary of the Invention

[0006] 1. Problem to be solved Based on this, it is necessary to provide a vehicle-mounted power battery fault diagnosis method-level device that can diagnose various types of vehicle-mounted power battery faults at one time to address the above technical problems.

[0007] 2. Technical solution In a first aspect, the present application provides a method for diagnosing a vehicle-mounted power battery fault. The method comprises: Collecting battery-related parameters and performing cleaning within a preset period, wherein the battery-related parameters include at least current; Calculates cumulative capacity based on preset cycles and battery-related parameters; Classifying the vehicle operating state based on current, wherein the vehicle operating state includes a charging stage, a parking stage, and a driving stage; Battery fault diagnosis based on charge consistency; Calculate the charge and discharge capacity of each vehicle's operating state based on the start and end cycles of the driving phase, parking phase, and charging phase, and calculate the battery's capacity retention rate; Perform battery fault diagnosis based on capacity retention and charge consistency.

[0008] In one embodiment, dividing the vehicle operating range based on current includes: Comparing the collected current with a preset current threshold, and matching the preset vehicle operating state based on the comparison result; Obtain the current collected in different periods in chronological order; Comparing the vehicle operating status of different cycles with the vehicle operating status of the initial cycle in sequence; If they are not the same, the period from the initial period to the period when the vehicle operating status changes is set as the continuous period of the vehicle operating status of the initial period, the period when the vehicle operating status changes is set as the initial period, and the vehicle operating status outside the continuous period is compared with the initial period until all periods are within the continuous period of the vehicle operating status.

[0009] In one embodiment, calculating the capacity retention rate of the battery includes: Query the interval where charge consistency can be calculated and set it as the starting state for charging; Querying the interval where the maximum voltage is greater than the preset voltage and calculating the sum of the capacities from the charging start state to the interval where the maximum voltage is greater than the preset voltage; The battery capacity retention rate is calculated based on the preset rated capacity.

[0010] In one embodiment, diagnosing a battery fault based on charge consistency includes: Calculating state-of-charge consistency based on maximum state-of-charge and minimum state-of-charge; The formula is as follows: ; in, For state of charge consistency, is the maximum state of charge, is the minimum state of charge.

[0011] In one embodiment, diagnosing battery faults based on capacity retention and charge consistency includes: When the charge consistency is greater than 11%, the charge consistency fault is level one; When the charge consistency is greater than 6% and less than 11%, the charge consistency fault is level 2.

[0012] In one embodiment, diagnosing battery faults based on capacity retention and charge consistency includes: When the capacity retention rate is less than 80%, the capacity retention rate fault is level 1; When the capacity retention rate is ≥80% and <90%, the capacity retention rate fault is level 2.

[0013] In one embodiment, the fault information is stored in a preset fault information database, wherein the fault information database stores fault information of byte transmission failure; When network anomalies cause fault information to not be transmitted to the preset cloud platform; After the network is restored, the fault information is transmitted from the fault information database to the preset cloud platform.

[0014] In a second aspect, the present application also provides a vehicle-mounted power battery fault diagnosis device. The device includes: A data acquisition and cleaning module, configured to collect battery-related parameters and perform cleaning within a preset period, wherein the battery-related parameters include at least current; A cumulative capacity calculation module, used to calculate the cumulative capacity based on a preset cycle and battery-related parameters; A vehicle state classification module is used to classify the vehicle operation state based on the current, wherein the vehicle operation state includes a charging stage, a parking stage, and a driving stage; Charge consistency calculation module, used to diagnose battery faults based on charge consistency; The capacity retention rate calculation module is used to calculate the charge and discharge capacity of each vehicle operating state based on the start and end cycles of the driving phase, parking phase and charging phase, and calculate the capacity retention rate of the battery; The battery fault diagnosis module is used to diagnose battery faults based on capacity retention and charge consistency.

[0015] In a third aspect, the present application further provides a computer system. The computer system includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the following steps are performed: Collecting battery-related parameters and performing cleaning within a preset period, wherein the battery-related parameters include at least current; Calculates cumulative capacity based on preset cycles and battery-related parameters; Classifying the vehicle operating state based on current, wherein the vehicle operating state includes a charging stage, a parking stage, and a driving stage; Battery fault diagnosis based on charge consistency; Calculate the charge and discharge capacity of each vehicle's operating state based on the start and end cycles of the driving phase, parking phase, and charging phase, and calculate the battery's capacity retention rate; Perform battery fault diagnosis based on capacity retention and charge consistency.

[0016] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps: Collecting battery-related parameters and performing cleaning within a preset period, wherein the battery-related parameters include at least current; Calculates cumulative capacity based on preset cycles and battery-related parameters; Classifying the vehicle operating state based on current, wherein the vehicle operating state includes a charging stage, a parking stage, and a driving stage; Battery fault diagnosis based on charge consistency; Calculate the charge and discharge capacity of each vehicle's operating state based on the start and end cycles of the driving phase, parking phase, and charging phase, and calculate the battery's capacity retention rate; Perform battery fault diagnosis based on capacity retention and charge consistency.

[0017] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the following steps: Collecting battery-related parameters and performing cleaning within a preset period, wherein the battery-related parameters include at least current; Calculates cumulative capacity based on preset cycles and battery-related parameters; Classifying the vehicle operating state based on current, wherein the vehicle operating state includes a charging stage, a parking stage, and a driving stage; Battery fault diagnosis based on charge consistency; Calculate the charge and discharge capacity of each vehicle's operating state based on the start and end cycles of the driving phase, parking phase, and charging phase, and calculate the battery's capacity retention rate; Perform battery fault diagnosis based on capacity retention and charge consistency.

[0018] 3. Beneficial effects This application adopts the above method and, through advanced current monitoring technology, can obtain current information in the vehicle electrical system in real time, and use this data to quickly and accurately classify and divide the vehicle's operating status, providing strong support for daily vehicle maintenance, fault diagnosis, and performance optimization; Fault determination based on battery mechanisms can accurately capture key indicators of battery performance changes, enable rapid response and intervention, and provide accurate fault causes and locations, thereby ensuring timely and effective identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a flow chart of a method for diagnosing a vehicle power battery fault in one embodiment; Figure 2 A schematic diagram of determining a vehicle operating state in one embodiment; Figure 3 This is a structural block diagram of a vehicle-mounted power battery fault diagnosis device in one embodiment; Figure 4 FIG. 1 is a diagram showing the internal structure of a computer system in one embodiment. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0021] The vehicle-mounted power battery fault diagnosis method provided in the embodiment of the present application is as follows: Figure 1 As shown, the method includes the following steps: Step 202: Collect battery-related parameters and perform cleaning within a preset period.

[0022] The data is collected in real time, including total current, total voltage, cell voltage, time, and mileage information related to the power battery during vehicle operation. The data is collected at regular intervals and sorted in ascending order of time.

[0023] It is worth mentioning that the data is cleaned to remove abnormal values, invalid values, and outliers. This mainly removes data that is not a numeric type, data with a total current value greater than the first threshold, data with a total voltage value greater than the second threshold, and data with a single cell voltage of 0.

[0024] Step 204 : Calculate the cumulative capacity based on a preset period and battery-related parameters.

[0025] The data is calculated to determine the time interval between each acquisition time, and the cumulative capacity of the power battery is calculated based on this. The specific steps are as follows: the value of the time interval greater than the third threshold is set to 0; the time interval is multiplied by the total current to calculate the current capacity, and then added to the previous capacity to calculate the cumulative capacity.

[0026] It is worth mentioning that the data is calculated, and the time interval of each collection time is calculated. The time interval is the value obtained by subtracting the next time from the current time, and based on this, the cumulative capacity and cumulative energy of the power battery are calculated. The specific steps are as follows: Step 1: Change the values ​​of time intervals greater than 30s to 0.

[0027] Step 2: Multiply the time interval by the total current to calculate the current capacity, and then add it to the previous capacity to calculate the cumulative capacity.

[0028] ; in is the cumulative capacity, is the total current, is the time interval.

[0029] Step 206 : Classify the vehicle operating status based on the current.

[0030] Among them, the vehicle operating status includes the charging stage, the parking stage and the driving stage; the sliding window method is used to distinguish according to the current. When the absolute value of the current is less than the fourth threshold, it is the parking state; when the current value is greater than the fourth threshold, it is the driving state; when the opposite number of the current value is less than the fourth threshold, it is the charging state.

[0031] Step 208 : Perform fault diagnosis on the battery based on the charge consistency.

[0032] The state of charge consistency of the vehicle battery is calculated based on the cell voltage during the parking phase. The state of charge consistency is calculated by converting the extreme voltage in the cell voltage into the extreme state of charge.

[0033] Step 210 , calculating the charge and discharge capacity of each vehicle operating state based on the start and end cycles of the driving phase, the parking phase, and the charging phase, and calculating the capacity retention rate of the battery.

[0034] Among them, the charging and discharging capacity of each stage is calculated according to the start and end points of the driving stage, parking stage and charging stage. The charging and discharging capacity of each stage is calculated by subtracting the cumulative capacity at the start time of each stage from the cumulative capacity at the end time of each stage, and the capacity retention rate SOH of the vehicle battery is calculated based on this.

[0035] Step 212: Perform battery fault diagnosis based on capacity retention and charge consistency.

[0036] The above-mentioned on-board power battery fault diagnosis method uses advanced current monitoring technology to obtain real-time current information in the vehicle's electrical system. This data can be used to quickly and accurately classify and divide the vehicle's operating status, providing strong support for daily vehicle maintenance, fault diagnosis, and performance optimization. Fault determination based on battery mechanisms can accurately capture key indicators of battery performance changes, enable rapid response and intervention, and provide accurate fault causes and locations, thereby ensuring timely and effective identification.

[0037] In one embodiment, Figure 2 As shown in FIG, the vehicle operating state is divided into the following categories based on current: The current collected in different periods is acquired in chronological order; the collected current is compared with a preset current threshold, and the preset vehicle operating state is matched based on the comparison result; the current collected in different periods is acquired in chronological order; the vehicle operating state of different periods is compared with the vehicle operating state of the initial period in turn; if they are different, the period from the initial period to the change of the vehicle operating state is set as the continuous period of the vehicle operating state of the initial period, the period in which the vehicle operating state changes is set as the initial period, and the vehicle operating state outside the continuous period is compared with the initial period until all periods are within the continuous period of the vehicle operating state.

[0038] Among them, when the absolute value of the current is less than 3A, it is in the parking state, when the current value is greater than 3A, it is in the driving state, and when the current value is less than 3A, it is in the charging state. Figure 2 The specific division steps are as follows: Step 1: Initially, two pointers are included, and both the left pointer and the right pointer point to the first position of the current state.

[0039] Step 2: Move the right pointer backward and determine whether the current state is the same as the left pointer current state.

[0040] Step 3: If the left and right pointers indicate the same current state, the right pointer moves backward.

[0041] Step 4: If the current states indicated by the left and right pointers are different, the interval between the left pointer position and the right pointer position minus 1 is recorded as one interval, and the interval state is the state indicated by the left pointer. Finally, the left pointer position is moved to the current right pointer position.

[0042] Step 5: When the right pointer moves to the end, the interval between the current left and right pointer positions is recorded as the last interval, and the state at this stage is the state pointed to by the left pointer.

[0043] In this embodiment, by defining the left and right pointers, the vehicle operating status corresponding to the current of the current cycle is obtained respectively. When the vehicle operating status corresponding to the left and right pointers are the same, the right pointer points to the current of the next cycle and compares the vehicle operating status based on the current of the next cycle with the vehicle operating status of the current corresponding to the left pointer. Until the vehicle operating status of the two pointers is different, the continuous period of the vehicle operating status corresponding to the left pointer is from the initial period of the left pointer to the previous period of the right pointer. Continuous division can divide the vehicle operating status by current.

[0044] In one embodiment, Figure 4 As shown, calculating the battery capacity retention rate includes: Query the interval where charge consistency can be calculated and set it as the starting state of charging; query the interval where the maximum voltage is greater than the preset voltage and calculate the sum of the capacities from the starting state of charging to the interval where the maximum voltage is greater than the preset voltage; calculate the capacity retention rate of the battery based on the preset rated capacity.

[0045] The state of charge consistency of the vehicle battery is calculated based on the cell voltage during the parking phase. The state of charge consistency is calculated by converting the extreme voltage in the cell voltage into the extreme state of charge.

[0046] ; in, For state of charge consistency, is the maximum state of charge, is the minimum state of charge.

[0047] The vehicle's power battery fault is diagnosed based on the consistency of the state of charge. When diagnosing the state of charge consistency fault, the fault level is divided according to the size of the calculated consistency value. When >11%, it is level 1. When the incidence rate is >6% and ≤11%, it is Grade 2.

[0048] The charge and discharge capacity of each stage is calculated based on the start and end of the driving stage, parking stage, and charging stage. The charge and discharge capacity of each stage is calculated by subtracting the cumulative capacity at the start of each stage from the cumulative capacity at the end of each stage. Based on this, the capacity retention rate (SOH) of the vehicle battery is calculated. The calculation steps of the capacity retention rate (SOH) are as follows: Step 1: First find the interval where the consistency difference can be calculated, and use this interval as the starting state for charging.

[0049] Step 2: Find the interval with the highest voltage greater than 3.6V and add up all the capacities during that interval as the charging capacity. Step 3: Calculate SOH based on rated capacity.

[0050] ; in, is the rated capacity, is the capacity at the initial stage.

[0051] The vehicle's power battery fault diagnosis is then performed using the SOH. During the capacity retention rate SOH fault diagnosis, the fault level is classified based on the calculated SOH value. If it is <80%, it is classified as Level 1. If it is ≥80% and <90%, it is classified as Level 2.

[0052] It is worth mentioning that the fault information is stored in a preset fault information library, which stores fault information of byte transmission failure; when the network abnormality causes the fault information to not be transmitted to the preset cloud platform; after waiting for the network to recover, the fault information is transmitted from the fault information library to the preset cloud platform.

[0053] The vehicle's fault information is transmitted using bytes. When the fault information is transmitted, the data is first stored locally and then transmitted to the cloud platform via the network. If the network is abnormal, the local data is transmitted when the network is restored. Finally, an alarm is issued based on the fault type. When the fault type alarm is issued, the fault type and fault level must be distinguished using a status code. The specific distinction is as follows: The state of charge consistency value is 00000100 for a level 1 fault and 00001000 for a level 2 fault. The capacity retention rate value is 00000001 for a level 1 fault and 00000010 for a level 2 fault.

[0054] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0055] Based on the same inventive concept, embodiments of the present application also provide an on-vehicle power battery fault diagnosis device for implementing the above-mentioned on-vehicle power battery fault diagnosis method. The solution provided by this device is similar to the solution described in the above-mentioned method. Therefore, the specific limitations of one or more embodiments of the on-vehicle power battery fault diagnosis device provided below can be found in the above-mentioned limitations of the on-vehicle power battery fault diagnosis method and will not be repeated here.

[0056] In one embodiment, Figure 3 As shown, a vehicle-mounted power battery fault diagnosis device is provided, including: a data acquisition and cleaning module, a cumulative capacity calculation module, a vehicle state classification module, a charge consistency calculation module, a capacity retention rate calculation module, a capacity retention rate calculation module and a battery fault diagnosis module, wherein: A data acquisition and cleaning module, configured to collect battery-related parameters and perform cleaning within a preset period, wherein the battery-related parameters include at least current; A cumulative capacity calculation module, used to calculate the cumulative capacity based on a preset cycle and battery-related parameters; A vehicle state classification module is used to classify the vehicle operation state based on the current, wherein the vehicle operation state includes a charging stage, a parking stage, and a driving stage; Charge consistency calculation module, used to diagnose battery faults based on charge consistency; The capacity retention rate calculation module is used to calculate the charge and discharge capacity of each vehicle operating state based on the start and end cycles of the driving phase, parking phase and charging phase, and calculate the capacity retention rate of the battery; The battery fault diagnosis module is used to diagnose battery faults based on capacity retention and charge consistency.

[0057] In one embodiment, the vehicle state classification module is further used to compare the collected current with a preset current threshold, and match the preset vehicle operating state based on the comparison result; obtain the current collected in different periods in chronological order; and compare the vehicle operating states of different periods with the vehicle operating states of the initial period in turn; if they are different, setting the period from the initial period to the period in which the vehicle operating state changes as the continuous period of the vehicle operating state of the initial period, setting the period in which the vehicle operating state changes as the initial period, and comparing the vehicle operating states outside the continuous period with the initial period until all periods are within the continuous period of the vehicle operating state.

[0058] In one embodiment, the cumulative capacity calculation module is further used to query the interval in which the charge consistency can be calculated and set it as the charging start state; query the interval in which the maximum voltage is greater than the preset voltage and calculate the sum of the capacities from the charging start state to the interval in which the maximum voltage is greater than the preset voltage; and calculate the capacity retention rate of the battery based on the preset rated capacity.

[0059] In one embodiment, the charge consistency calculation module is further configured to perform battery fault diagnosis based on the charge consistency, including calculating the charge consistency based on the maximum state of charge and the minimum state of charge; the formula is as follows: ; in, For state of charge consistency, is the maximum state of charge, is the minimum state of charge.

[0060] In one embodiment, a battery fault diagnosis module stores fault information in a preset fault information library, wherein the fault information library stores fault information of byte transmission failure; when a network abnormality causes the fault information to not be transmitted to the preset cloud platform; after waiting for the network to recover, the fault information is transmitted from the fault information library to the preset cloud platform.

[0061] Each module in the above-mentioned vehicle power battery fault diagnosis device can be implemented in whole or in part through software, hardware, or a combination thereof. Each of the above modules can be embedded in or independent of the processor in the computer system in hardware form, or can be stored in the memory of the computer system in software form, so that the processor can call and execute the corresponding operations of each module.

[0062] In one embodiment, a computer system is provided. The computer system may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer system includes a processor, a memory and a network interface connected via a system bus. The processor of the computer system is used to provide computing and control capabilities. The memory of the computer system includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer system is used to store data. The network interface of the computer system is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for diagnosing vehicle power battery faults is implemented.

[0063] In one embodiment, a computer system is provided. The computer system may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown. The computer system includes a processor, memory, communication interface, display screen and input device connected via a system bus. The processor of the computer system is used to provide computing and control capabilities. The memory of the computer system includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The communication interface of the computer system is used to communicate with an external terminal in a wired or wireless manner. The wireless manner can be achieved through WIFI, mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for diagnosing vehicle power battery faults is implemented.

[0064] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer system to which the solution of the present application is applied. The specific computer system may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0065] In one embodiment, a computer system is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0066] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0067] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0068] It should be noted that the user information (including but not limited to user system information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0069] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.

[0070] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0071] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A vehicle-mounted power battery fault diagnosis method, characterized in that: The method comprises: Collecting battery-related parameters and performing cleaning within a preset period, wherein the battery-related parameters include at least current; Calculates cumulative capacity based on preset cycles and battery-related parameters; Classifying the vehicle operating state based on current, wherein the vehicle operating state includes a charging stage, a parking stage, and a driving stage; Battery fault diagnosis based on charge consistency; Calculate the charge and discharge capacity of each vehicle's operating state based on the start and end cycles of the driving phase, parking phase, and charging phase, and calculate the battery's capacity retention rate; Perform battery fault diagnosis based on capacity retention and charge consistency.

2. The vehicle-mounted power battery fault diagnosis method according to claim 1, characterized in that: The classification of the vehicle operating state based on the current includes: Comparing the collected current with a preset current threshold, and matching the preset vehicle operating state based on the comparison result; Obtain the current collected in different periods in chronological order; Comparing the vehicle operating status of different cycles with the vehicle operating status of the initial cycle in sequence; If they are not the same, the period from the initial period to the period when the vehicle operating status changes is set as the continuous period of the vehicle operating status of the initial period, the period when the vehicle operating status changes is set as the initial period, and the vehicle operating status outside the continuous period is compared with the initial period until all periods are within the continuous period of the vehicle operating status.

3. The vehicle-mounted power battery fault diagnosis method according to claim 1, characterized in that: Calculating the capacity retention rate of the battery includes: Query the interval for calculating battery charge consistency and set it as the charging start state; Querying the interval where the maximum voltage is greater than the preset voltage and calculating the sum of the capacities from the charging start state to the interval where the maximum voltage is greater than the preset voltage; The battery capacity retention rate is calculated based on the preset rated capacity.

4. The vehicle-mounted power battery fault diagnosis method according to claim 1, characterized in that: The battery fault diagnosis based on charge consistency includes: Calculating state-of-charge consistency based on maximum state-of-charge and minimum state-of-charge; The formula is as follows: ； in, For state of charge consistency, is the maximum state of charge, is the minimum state of charge.

5. The vehicle-mounted power battery fault diagnosis method according to claim 1, characterized in that: The battery fault diagnosis based on capacity retention rate and charge consistency includes: When the charge consistency is greater than 11%, the charge consistency fault is level one; When the charge consistency is greater than 6% and less than 11%, the charge consistency fault is level 2.

6. The vehicle-mounted power battery fault diagnosis method according to claim 1, characterized in that: The battery fault diagnosis based on capacity retention rate and charge consistency includes: When the capacity retention rate is less than 80%, the capacity retention rate fault is level 1; When the capacity retention rate is ≥80% and <90%, the capacity retention rate fault is level 2.

7. The vehicle-mounted power battery fault diagnosis method according to claim 1, characterized in that: The method further comprises: Storing the fault information in a preset fault information database, wherein the fault information database stores fault information of byte transmission failure; When network anomalies cause fault information to not be transmitted to the preset cloud platform; After the network is restored, the fault information is transmitted from the fault information database to the preset cloud platform.

8. A vehicle-mounted power battery fault diagnosis device, characterized in that: The device comprises: A data acquisition and cleaning module, configured to collect battery-related parameters and perform cleaning within a preset period, wherein the battery-related parameters include at least current; A cumulative capacity calculation module, used to calculate the cumulative capacity based on a preset cycle and battery-related parameters; A vehicle state classification module is used to classify the vehicle operation state based on the current, wherein the vehicle operation state includes a charging stage, a parking stage, and a driving stage; Charge consistency calculation module, used to diagnose battery faults based on charge consistency; The capacity retention rate calculation module is used to calculate the charge and discharge capacity of each vehicle operating state based on the start and end cycles of the driving phase, parking phase and charging phase, and calculate the capacity retention rate of the battery; The battery fault diagnosis module is used to diagnose battery faults based on capacity retention and charge consistency.

9. A computer system comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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