Insulation resistance fault pre-diagnosis method, system and device of vehicle and medium

Abstract

The invention discloses a vehicle insulation resistor fault pre-diagnosis method, system and device and a medium. The method is applied to an Internet of Vehicles platform, a vehicle comprises a remote diagnosis box TBOX and a battery management system, and the method comprises the steps: receiving the operation data, sent by the remote diagnosis box TBOX, of a power battery monitored by the battery management system; obtaining the insulation resistance of the power battery and the change condition of the insulation resistance according to the operation data of the power battery; and when the insulation resistance is smaller than a preset value or the insulation resistance is predicted to have a fault risk according to the change condition of the insulation resistance, giving an alarm. With the adoption of the method and the device, before the power battery insulation fault of the vehicle occurs, the fault which is possibly to occur can be pre-judged, and a user can be prompted to overhaul, maintain and the like before the fault occurs, so that the fault occurrence probability is reduced, and the safety and the use experience of the vehicle are improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a method, system, device, and medium for pre-diagnosing insulation resistance faults in a vehicle. Background Art

[0002] In related technologies, electric vehicles typically have an alarm design for abnormal insulation resistance values ​​in their battery management systems. However, if the alarm is triggered when the insulation resistance is abnormal, the fault has already occurred, which can easily lead to secondary disasters such as accidental electric shock and spontaneous combustion of the power battery. In addition, the system will stop working after the fault occurs, causing vehicle travel interruption and user complaints. In other words, alarming after a fault occurs cannot effectively avoid the risks of sudden insulation failure, such as electric shock, short circuit, or fire. Moreover, if a sudden insulation failure causes the high-voltage system to be forced to shut down while the vehicle is driving, it will cause the vehicle to be unable to drive, resulting in user complaints and potentially higher maintenance costs. Summary of the Invention

[0003] Based on this, it is necessary to provide a vehicle insulation resistance fault pre-diagnosis method, system, equipment and medium to address the above technical problems. This method can predict possible failures before the vehicle's power battery insulation failure occurs, and can prompt users to perform inspections and maintenance before the failure occurs, thereby reducing the probability of failures and improving the safety and user experience of the vehicle.

[0004] In a first aspect, a vehicle insulation resistance fault pre-diagnosis method is provided, which is applied to a vehicle networking platform. The vehicle includes a remote diagnosis box TBOX and a battery management system. The vehicle insulation resistance fault pre-diagnosis method includes:

[0005] Receiving the operating data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX;

[0006] Obtaining the insulation resistance of the power battery and changes in the insulation resistance according to the operating data of the power battery;

[0007] When the insulation resistance is less than a preset value, or when it is predicted based on the change of the insulation resistance that there is a risk of insulation resistance failure, an alarm is issued.

[0008] In some examples, the operating data of the power battery monitored by the battery management system and sent by the remote diagnostic box TBOX and received by the Internet of Vehicles platform includes: a timestamp and a vehicle identification code added by the remote diagnostic box TBOX.

[0009] In some examples, obtaining the insulation resistance of the power battery and changes in the insulation resistance based on the operating data of the power battery includes:

[0010] Calculating the insulation resistance of the power battery according to the operating data of the power battery;

[0011] A linear fit is performed on the operating data of the power battery to obtain the change of the insulation resistance.

[0012] In some examples, when predicting, based on the change in the insulation resistance, that there is a risk of insulation resistance failure, issuing an alarm includes:

[0013] When one or more of the following conditions are met, the insulation resistance is predicted to have a fault risk and an alarm is issued:

[0014] The insulation resistance suddenly drops;

[0015] The continuous attenuation rate of the insulation resistance reaches a preset attenuation rate;

[0016] The oscillation amplitude of the insulation resistance exceeds the standard value;

[0017] The variance of the insulation resistance exceeds a predetermined percentile for vehicles of the same type.

[0018] In some examples, this also includes:

[0019] A regression model among the vehicle's ambient temperature value, ambient humidity value, and insulation resistance attenuation rate is established based on the vehicle identification code.

[0020] In some examples, after establishing a regression model between the vehicle's ambient temperature, ambient humidity, and resistance decay rate, the following steps are also included:

[0021] Based on the regression model, the relationship between the ambient temperature value, the ambient humidity value and the insulation resistance attenuation is statistically calculated;

[0022] Calculating the probability of insulation resistance degradation at various ambient temperature and humidity values ​​of the vehicle based on the relationship between the ambient temperature and humidity values ​​and insulation resistance degradation;

[0023] When the probability is greater than the preset probability, an early warning is issued.

[0024] In a second aspect, a vehicle insulation resistance fault pre-diagnosis system is provided, which is applied to a vehicle networking platform. The vehicle includes a remote diagnosis box TBOX and a battery management system. The vehicle insulation resistance fault pre-diagnosis system includes:

[0025] a receiving module, configured to receive the operating data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX;

[0026] a calculation module, configured to obtain the insulation resistance of the power battery and changes in the insulation resistance based on the operating data of the power battery;

[0027] The early warning module is used to issue an alarm when the insulation resistance is less than a preset value or when it is predicted based on the change of the insulation resistance that there is a risk of insulation resistance failure.

[0028] In a third aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the vehicle insulation resistance fault pre-diagnosis method of the first aspect and any possible implementation of the first aspect are implemented.

[0029] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the steps of the vehicle insulation resistance fault pre-diagnosis method of the above-mentioned first aspect and any possible implementation method of the first aspect are implemented.

[0030] In a fifth aspect, a computer program product is provided, on which a computer program is stored. When the program is executed by a processor, the steps of the vehicle insulation resistance fault pre-diagnosis method of the above-mentioned first aspect and any possible implementation of the first aspect are implemented.

[0031] By adopting the embodiments of the present application, the insulation resistance of the power battery and the changes in the insulation resistance can be determined based on the operating data of the power battery monitored by the battery management system sent by the vehicle's remote diagnostic box TBOX and received by the vehicle networking platform, and an alarm can be issued when the insulation resistance is less than a preset value, or when the insulation resistance is predicted to have a failure risk based on the changes in the insulation resistance. In this way, before the vehicle's power battery insulation failure occurs, a possible failure can be predicted, and the user can be prompted to perform inspection and maintenance before the failure occurs, thereby reducing the probability of failure and improving the safety and user experience of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Other features, objects and advantages of the present application will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0033] Figure 1 This is a flow chart of a vehicle insulation resistance fault pre-diagnosis method provided in an embodiment of the present application;

[0034] Figure 2 This is a structural block diagram of a vehicle insulation resistance fault pre-diagnosis system provided in an embodiment of the present application;

[0035] Figure 3This is a structural block diagram of the computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0036] The present application will be further described in detail below with reference to the embodiments and accompanying drawings. It should be understood that the specific embodiments described herein are intended only to illustrate the relevant application and are not intended to limit the application. It should also be noted that, for ease of description, only the portions relevant to the application are shown in the accompanying drawings.

[0037] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0038] The following describes in detail the insulation resistance fault pre-diagnosis method, system, device and medium for a vehicle according to an embodiment of the present application in conjunction with the accompanying drawings.

[0039] Figure 1 FIG. 1 is a flow chart of a method for pre-diagnosing insulation resistance faults of a vehicle according to an embodiment of the present application. Figure 1 As shown, the vehicle insulation resistance fault pre-diagnosis method according to an embodiment of the present application is applied to a vehicle networking platform. The vehicle includes a remote diagnosis box TBOX and a battery management system. The vehicle insulation resistance fault pre-diagnosis method includes the following steps:

[0040] S101: receiving the operating data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX.

[0041] In one embodiment of the present application, the operation data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX and received by the Internet of Vehicles platform includes: a timestamp and a vehicle identification code added by the remote diagnosis box TBOX.

[0042] Specifically, the remote diagnostic box TBOX is a controller inside the vehicle that can collect in-vehicle data, diagnose vehicle faults, and remotely upload the collected data and vehicle fault information to the Internet of Vehicles platform.

[0043] The battery management system (BMS) is the control module of the vehicle's power battery. It manages and controls the power battery system, can monitor the operating status of the power battery in real time, send the monitored power battery operating data to the CAN bus, and record fault information of the power battery system in real time.

[0044] The battery operating data includes, but is not limited to, the battery's positive and negative insulation values, system insulation values, electrical box positive and negative insulation values, electrical box system insulation values, ambient temperature, ambient humidity, battery temperature, and electrical box temperature. The above signals are periodically transmitted to the CAN bus, and a low insulation resistance alarm signal is sent to the CAN bus when the insulation resistance value falls below a threshold.

[0045] After the remote diagnostic box TBOX is powered on and initialized, it collects the operating data of the power battery, such as the positive insulation value, negative insulation value, system insulation value, battery box positive insulation value, battery box negative insulation value, battery box system insulation value, ambient temperature value, ambient humidity value, battery temperature value, battery box temperature value, etc., sent by the battery management system BMS on the CAN bus in real time, and reads the fault codes monitored by the battery management system in real time. The collected information is packaged, timestamp and vehicle identification code are added, and then transmitted to the Internet of Vehicles platform in real time.

[0046] Internet of Vehicles platform: collects data and fault information sent by the remote diagnostic box TBOX, processes and calculates the data in the subsequent process, and predicts insulation faults and risks.

[0047] S102: Obtaining the insulation resistance of the power battery and changes in the insulation resistance according to the operating data of the power battery.

[0048] In one embodiment of the present application, obtaining the insulation resistance of the power battery and the change in the insulation resistance based on the operating data of the power battery includes: calculating the insulation resistance of the power battery based on the operating data of the power battery; and performing linear fitting on the operating data of the power battery to obtain the change in the insulation resistance.

[0049] S103: When the insulation resistance is less than a preset value, or when it is predicted based on the change in the insulation resistance that there is a risk of insulation resistance failure, an alarm is issued.

[0050] In one embodiment of the present application, when it is predicted that there is a risk of failure in the insulation resistance based on the change of the insulation resistance, an alarm is issued, including: when one or more of the following is met, it is predicted that there is a risk of failure in the insulation resistance and an alarm is issued: the insulation resistance suddenly drops; the continuous attenuation rate of the insulation resistance reaches a preset attenuation rate; the oscillation amplitude of the insulation resistance exceeds the standard value; the variance of the insulation resistance exceeds the predetermined percentile of similar vehicles.

[0051] For example, the IoV platform receives real-time vehicle data from the vehicle's remote diagnostic box TBOX, such as the battery's positive insulation value, negative insulation value, system insulation value, battery box positive insulation value, battery box negative insulation value, battery box system insulation value, ambient temperature value, ambient humidity value, battery temperature value, battery box temperature value, and other power battery operating data. It performs linear fitting on the received data and issues a sudden drop in insulation resistance, for example, a drop of >30% in insulation resistance within a single day, or a continuous attenuation, for example, a continuous attenuation of insulation resistance if the attenuation rate of insulation resistance within a week is >5%, or an oscillation amplitude of insulation resistance exceeds the expected standard value, or the variance of insulation resistance exceeds the 95th percentile of similar vehicles, an early warning is issued.

[0052] In other words, if a sudden drop in insulation resistance is detected, or if the insulation resistance continues to decay, or if the insulation resistance oscillates widely, even if the insulation resistance is consistently within the standard range, it is still predicted that an insulation resistance problem may occur. This means that a potential insulation resistance failure can be predicted. Therefore, before a vehicle's power battery insulation failure occurs, an effective prediction of the impending failure is made, allowing inspection and maintenance to be performed before the failure occurs, thereby reducing the probability of failure and improving vehicle safety and user experience.

[0053] According to the vehicle insulation resistance fault pre-diagnosis method of the embodiment of the present application, the insulation resistance of the power battery and the change of the insulation resistance can be determined based on the operating data of the power battery monitored by the battery management system sent by the vehicle's remote diagnostic box TBOX and received by the vehicle networking platform, and an alarm can be issued when the insulation resistance is less than a preset value, or when it is predicted that there is a risk of insulation resistance failure based on the change of the insulation resistance. In this way, before the vehicle's power battery insulation failure occurs, a possible failure can be predicted, and the user can be prompted to perform inspection and maintenance before the failure occurs, thereby reducing the probability of failure and improving the safety and user experience of the vehicle.

[0054] In one embodiment of the present application, the method for pre-diagnosing insulation resistance faults in a vehicle further includes: the vehicle networking platform establishing a regression model between the vehicle's ambient temperature value, ambient humidity value, and insulation resistance decay rate based on the vehicle identification code. Furthermore, after establishing the regression model between the vehicle's ambient temperature value, ambient humidity value, and resistance decay rate, the method further includes: statistically calculating the relationship between the ambient temperature value, ambient humidity value, and insulation resistance decay based on the regression model; calculating the probability of insulation resistance decay occurring at various vehicle ambient temperatures and humidities based on the relationship between the ambient temperature value, ambient humidity value, and insulation resistance decay; and issuing a warning when the probability is greater than a preset probability. For example: The Internet of Vehicles platform establishes a regression model of the ambient temperature value-ambient humidity value-insulation resistance attenuation rate for all vehicles based on the vehicle identification code VIN, statistically calculates the relationship between ambient temperature, ambient humidity and insulation resistance attenuation, and calculates the probability of insulation resistance attenuation under various ambient temperature and ambient humidity conditions. For example: a warning is issued to vehicles with a probability of insulation resistance attenuation greater than 50%. In this way, before the vehicle's power battery insulation failure occurs, possible failures are predicted, thereby reducing the probability of failures.

[0055] Figure 2 FIG. 1 is a structural block diagram of a vehicle insulation resistance fault pre-diagnosis system according to an embodiment of the present application. Figure 2 As shown, the vehicle insulation resistance fault pre-diagnosis system according to an embodiment of the present application is applied to a vehicle networking platform. The vehicle includes a remote diagnosis box TBOX and a battery management system. The vehicle insulation resistance fault pre-diagnosis system includes: a receiving module 210, a calculation module 220 and an early warning module 230, wherein:

[0056] The receiving module 210 is configured to receive the operating data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX;

[0057] The calculation module 220 is used to obtain the insulation resistance of the power battery and the change of the insulation resistance according to the operating data of the power battery;

[0058] The early warning module 230 is configured to generate an alarm when the insulation resistance is less than a preset value, or when it is predicted based on the change of the insulation resistance that there is a risk of insulation resistance failure.

[0059] In one embodiment of the present application, the operation data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX and received by the Internet of Vehicles platform includes: a timestamp and a vehicle identification code added by the remote diagnosis box TBOX.

[0060] Specifically, the remote diagnostic box TBOX is a controller inside the vehicle that can collect in-vehicle data, diagnose vehicle faults, and remotely upload the collected data and vehicle fault information to the Internet of Vehicles platform.

[0061] The battery management system (BMS) is the control module of the vehicle's power battery. It manages and controls the power battery system, can monitor the operating status of the power battery in real time, send the monitored power battery operating data to the CAN bus, and record fault information of the power battery system in real time.

[0062] The battery operating data includes, but is not limited to, the battery's positive and negative insulation values, system insulation values, electrical box positive and negative insulation values, electrical box system insulation values, ambient temperature, ambient humidity, battery temperature, and electrical box temperature. The above signals are periodically transmitted to the CAN bus, and a low insulation resistance alarm signal is sent to the CAN bus when the insulation resistance value falls below a threshold.

[0063] After the remote diagnostic box TBOX is powered on and initialized, it collects the operating data of the power battery, such as the positive insulation value, negative insulation value, system insulation value, battery box positive insulation value, battery box negative insulation value, battery box system insulation value, ambient temperature value, ambient humidity value, battery temperature value, battery box temperature value, etc., sent by the battery management system BMS on the CAN bus in real time, and reads the fault codes monitored by the battery management system in real time. The collected information is packaged, timestamp and vehicle identification code are added, and then transmitted to the Internet of Vehicles platform in real time.

[0064] Internet of Vehicles platform: collects data and fault information sent by the remote diagnostic box TBOX, processes and calculates the data in the subsequent process, and predicts insulation faults and risks.

[0065] In one embodiment of the present application, obtaining the insulation resistance of the power battery and the change in the insulation resistance based on the operating data of the power battery includes: calculating the insulation resistance of the power battery based on the operating data of the power battery; and performing linear fitting on the operating data of the power battery to obtain the change in the insulation resistance.

[0066] In one embodiment of the present application, when it is predicted that there is a risk of failure in the insulation resistance based on the change of the insulation resistance, an alarm is issued, including: when one or more of the following is met, it is predicted that there is a risk of failure in the insulation resistance and an alarm is issued: the insulation resistance suddenly drops; the continuous attenuation rate of the insulation resistance reaches a preset attenuation rate; the oscillation amplitude of the insulation resistance exceeds the standard value; the variance of the insulation resistance exceeds the predetermined percentile of similar vehicles.

[0067] For example, the IoV platform receives real-time vehicle data from the vehicle's remote diagnostic box TBOX, such as the battery's positive insulation value, negative insulation value, system insulation value, battery box positive insulation value, battery box negative insulation value, battery box system insulation value, ambient temperature value, ambient humidity value, battery temperature value, battery box temperature value, and other power battery operating data. It performs linear fitting on the received data and issues a sudden drop in insulation resistance, for example, a drop of >30% in insulation resistance within a single day, or a continuous attenuation, for example, a continuous attenuation of insulation resistance if the attenuation rate of insulation resistance within a week is >5%, or an oscillation amplitude of insulation resistance exceeds the expected standard value, or the variance of insulation resistance exceeds the 95th percentile of similar vehicles, an early warning is issued.

[0068] In other words, if a sudden drop in insulation resistance is detected, or if the insulation resistance continues to decay, or if the insulation resistance oscillates widely, even if the insulation resistance is consistently within the standard range, it is still predicted that an insulation resistance problem may occur. This means that a potential insulation resistance failure can be predicted. Therefore, before a vehicle's power battery insulation failure occurs, an effective prediction of the impending failure is made, allowing inspection and maintenance to be performed before the failure occurs, thereby reducing the probability of failure and improving vehicle safety and user experience.

[0069] According to the vehicle insulation resistance fault pre-diagnosis system of the embodiment of the present application, the insulation resistance of the power battery and the change of the insulation resistance can be determined based on the operating data of the power battery monitored by the battery management system sent by the vehicle's remote diagnostic box TBOX and received by the vehicle networking platform, and an alarm can be issued when the insulation resistance is less than a preset value, or when it is predicted that there is a risk of insulation resistance failure based on the change of the insulation resistance. In this way, before the vehicle's power battery insulation failure occurs, a possible failure can be predicted, and the user can be prompted to perform inspection and maintenance before the failure occurs, thereby reducing the probability of failure and improving the safety and user experience of the vehicle.

[0070] In one embodiment of the present application, the vehicle networking platform further includes establishing a regression model between the vehicle's ambient temperature, ambient humidity, and insulation resistance decay rate based on the vehicle identification code. Furthermore, after establishing the regression model between the vehicle's ambient temperature, ambient humidity, and insulation resistance decay rate, the system further includes: calculating, based on the regression model, the relationship between the ambient temperature, ambient humidity, and insulation resistance decay; calculating, based on the relationship between the ambient temperature, ambient humidity, and insulation resistance decay, the probability of insulation resistance decay occurring at various vehicle ambient temperatures and ambient humidities; and issuing an early warning when the probability is greater than a preset probability. For example: The Internet of Vehicles platform establishes a regression model of the ambient temperature value-ambient humidity value-insulation resistance attenuation rate for all vehicles based on the vehicle identification code VIN, statistically calculates the relationship between ambient temperature, ambient humidity and insulation resistance attenuation, and calculates the probability of insulation resistance attenuation under various ambient temperature and ambient humidity conditions. For example: a warning is issued to vehicles with a probability of insulation resistance attenuation greater than 50%. In this way, before the vehicle's power battery insulation failure occurs, possible failures are predicted, thereby reducing the probability of failures.

[0071] The specific definitions of the vehicle insulation resistance fault pre-diagnosis system can be found in the definitions of the vehicle insulation resistance fault pre-diagnosis method described above and will not be repeated here. The various modules of the vehicle insulation resistance fault pre-diagnosis system described above can be implemented in whole or in part through software, hardware, or a combination thereof. Each of these modules can be embedded in or independent of a processor in a computer device in hardware form, or stored in the computer device's memory in software form, allowing the processor to call and execute the corresponding operations of each module.

[0072] In one embodiment, a computer device is provided. Figure 3 This is a block diagram of the computer device provided in the embodiment of the present application, refer to Figure 3 The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the embodiment of the vehicle insulation resistance fault pre-diagnosis method is implemented. For example, the following steps are performed: receiving the operating data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX;

[0073] Obtaining the insulation resistance of the power battery and changes in the insulation resistance according to the operating data of the power battery;

[0074] When the insulation resistance is less than a preset value, or when it is predicted based on the change of the insulation resistance that there is a risk of insulation resistance failure, an alarm is issued.

[0075] The present application also provides a computer-readable storage medium storing a computer program. When the processor executes the computer program, the method for pre-diagnosing insulation resistance faults in a vehicle described above is implemented. For example, the method includes: receiving the operating data of the power battery monitored by the battery management system and sent by the remote diagnostic box TBOX;

[0076] Obtaining the insulation resistance of the power battery and changes in the insulation resistance according to the operating data of the power battery;

[0077] When the insulation resistance is less than a preset value, or when it is predicted based on the change of the insulation resistance that there is a risk of insulation resistance failure, an alarm is issued.

[0078] The present application embodiment provides a computer program product, which includes instructions. When the instructions are executed, the method described in the embodiment of the present application is executed. For example, you can execute Figure 1 The various steps of the vehicle insulation resistance fault pre-diagnosis method shown, for example, are performed: receiving the operating data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX;

[0079] Obtaining the insulation resistance of the power battery and changes in the insulation resistance according to the operating data of the power battery;

[0080] When the insulation resistance is less than a preset value, or when it is predicted based on the change of the insulation resistance that there is a risk of insulation resistance failure, an alarm is issued.

[0081] Those skilled in the art will appreciate that all or part of the processes in the methods for implementing the above embodiments can be accomplished by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include processes of the embodiments of the above methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0082] The technical features of the above embodiments can be combined arbitrarily. In order 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.

[0083] The above embodiments merely illustrate 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 patent 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, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for pre-diagnosing insulation resistance faults of a vehicle, characterized in that: Applied to a vehicle networking platform, the vehicle includes a remote diagnostic box TBOX and a battery management system, and the method includes: Receiving the operating data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX; Obtaining the insulation resistance of the power battery and changes in the insulation resistance according to the operating data of the power battery; When the insulation resistance is less than a preset value, or when it is predicted based on the change of the insulation resistance that there is a risk of insulation resistance failure, an alarm is issued.

2. The vehicle insulation resistance fault pre-diagnosis method according to claim 1, characterized in that: The operating data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX and received by the Internet of Vehicles platform includes: a timestamp and a vehicle identification code added by the remote diagnosis box TBOX.

3. The vehicle insulation resistance fault pre-diagnosis method according to claim 1, characterized in that: Obtaining the insulation resistance of the power battery and changes in the insulation resistance according to the operating data of the power battery includes: Calculating the insulation resistance of the power battery according to the operating data of the power battery; A linear fit is performed on the operating data of the power battery to obtain the change of the insulation resistance.

4. The vehicle insulation resistance fault pre-diagnosis method according to claim 3, characterized in that: When the insulation resistance is predicted to have a fault risk based on the change in the insulation resistance, an alarm is issued, including: When one or more of the following conditions are met, the insulation resistance is predicted to have a fault risk and an alarm is issued: The insulation resistance suddenly drops; The continuous attenuation rate of the insulation resistance reaches a preset attenuation rate; The oscillation amplitude of the insulation resistance exceeds the standard value; The variance of the insulation resistance exceeds a predetermined percentile for vehicles of the same type.

5. The vehicle insulation resistance fault pre-diagnosis method according to claim 2, characterized in that: Also includes: A regression model among the vehicle's ambient temperature value, ambient humidity value, and insulation resistance attenuation rate is established based on the vehicle identification code.

6. The vehicle insulation resistance fault pre-diagnosis method according to claim 2, characterized in that: After establishing the regression model between the vehicle's ambient temperature, ambient humidity, and resistance attenuation rate, it also includes: Based on the regression model, the relationship between the ambient temperature value, the ambient humidity value and the insulation resistance attenuation is statistically calculated; Calculating the probability of insulation resistance degradation at various ambient temperature and humidity values ​​of the vehicle based on the relationship between the ambient temperature and humidity values ​​and insulation resistance degradation; When the probability is greater than the preset probability, an early warning is issued.

7. A vehicle insulation resistance fault pre-diagnosis system, characterized in that: Applied to the Internet of Vehicles platform, the vehicle includes a remote diagnostic box TBOX and a battery management system. The vehicle's insulation resistance fault pre-diagnosis system includes: a receiving module, configured to receive the operating data of the power battery monitored by the battery management system and sent by the remote diagnosis box TBOX; a calculation module, configured to obtain the insulation resistance of the power battery and changes in the insulation resistance based on the operating data of the power battery; The early warning module is used to issue an alarm when the insulation resistance is less than a preset value or when it is predicted based on the change of the insulation resistance that there is a risk of insulation resistance failure.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the vehicle insulation resistance fault pre-diagnosis method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium comprising a memory and a computer program stored in the memory and executable on a processor, characterized in that: When the program is executed by a processor, the vehicle insulation resistance fault pre-diagnosis method according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a memory and a computer program stored in the memory and executable on a processor, characterized in that: When the program is executed by a processor, the vehicle insulation resistance fault pre-diagnosis method according to any one of claims 1 to 6 is implemented.

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