A fuel cell vehicle fault monitoring method, system, server and medium

Abstract

The application discloses a kind of fuel cell vehicle fault monitoring method, system, server and medium.It includes the following steps: obtaining fault attribute information;According to the fault code in fault attribute information, call fault database, obtain the fault level corresponding to fault code;Fault database at least includes: fault code, and the fault index corresponding to fault code;Fault index includes: fault level and fault probability;When the fault level corresponding to fault code is greater than or equal to the first threshold value, obtain the fault probability corresponding to fault code;When the fault probability corresponding to fault code is greater than or equal to the second threshold value, obtain the fault influence factor;Fault code, the fault occurrence time corresponding to fault code and fault influence factor are added to fault information statistical database.Make that fault information statistical database has vehicle actual fault data, so as to be more accurately guided fault analysis result when subsequent in troubleshooting vehicle fault.

Description

TECHNICAL FIELD

[0001] The present application generally relates to the technical field of fuel cell vehicle, and particularly relates to a fuel cell vehicle fault monitoring method, system, server and medium. BACKGROUND

[0002] Fuel cell vehicles have become one of the important directions of sustainable development of future automobile industry due to their advantages of high efficiency, energy saving and zero emission, and are considered as an ideal way to solve the energy crisis and environmental pollution in the future. Countries are vigorously carrying out technical research and development and popularization of fuel cells, and have raised it to the height of national energy strategy. Moreover, key components such as stacks, compressors, DC / DC converters, hydrogen circulation devices, control systems and sensors of fuel cell systems have been localized.

[0003] However, the current fault determination method of fuel cell vehicles is to compare the historical data before the vehicle leaves the factory with the collected data. Since the historical data in the historical database is limited, it cannot be combined with the actual fault data of the vehicle for analysis, resulting in that the accuracy of fault troubleshooting results cannot be guaranteed. Therefore, we propose a fuel cell vehicle fault monitoring method, system, server and medium to solve the above problems. SUMMARY

[0004] In view of the above defects or deficiencies in the prior art, it is desirable to provide a fuel cell vehicle fault monitoring method, system, server and medium that can guarantee the accuracy of fault troubleshooting.

[0005] In a first aspect, the present application provides a fuel cell vehicle fault monitoring method, comprising the following steps:

[0006] Obtaining fault attribute information; the fault attribute information at least includes: fault code, and fault occurrence time corresponding to the fault code;

[0007] According to the fault code in the fault attribute information, a fault database is called to obtain the fault level corresponding to the fault code; the fault database at least includes: the fault code, and the fault index corresponding to the fault code; the fault index includes: fault level and fault probability;

[0008] When the fault level corresponding to the fault code is greater than or equal to a first threshold, the fault probability corresponding to the fault code is obtained;

[0009] When the fault probability corresponding to the fault code is greater than or equal to a second threshold, a fault influence factor is obtained;

[0010] add the fault code, the fault occurrence time corresponding to the fault code and the fault influence factor to a fault information statistical database to update the fault information statistical database; the fault information statistical database at least includes the fault code, the fault occurrence time corresponding to the fault code and the fault influence factor.

[0011] According to the technical scheme provided in the embodiment of the present application, the fault influence factor is obtained, and the method specifically comprises the following steps:

[0012] When the number of the fault occurrence times corresponding to the fault code in the fault information statistical database is greater than or equal to 1, the fault coefficient is calculated, and the fault influence factor is calculated according to the fault coefficient.

[0013] According to the technical scheme provided in the embodiment of the present application, the fault influence factor is calculated according to the fault coefficient, and the method specifically comprises the following steps:

[0014] The level database is called to find the fault coefficient range to which the fault coefficient belongs and the corresponding preset correction ratio; the level database includes the fault coefficient range and the preset correction ratio corresponding to the fault coefficient range.

[0015] The fault information statistical database is traversed to obtain a stored fault influence factor; the stored fault influence factor is the fault influence factor corresponding to the fault occurrence time closest to the fault occurrence time of the corresponding fault code and the same as the current fault code.

[0016] The fault influence factor is calculated according to the preset correction ratio and the stored fault influence factor.

[0017] According to the technical scheme provided in the embodiment of the present application, the fault database further includes an initial influence factor corresponding to the fault code.

[0018] The fault influence factor is obtained, and the method further comprises the following steps:

[0019] When the number of the fault occurrence times corresponding to the fault code in the fault information statistical database is less than 1, the fault database is called to obtain the initial influence factor corresponding to the fault code as the fault influence factor corresponding to the fault code at the current fault occurrence time.

[0020] According to the technical scheme provided in the embodiment of the present application, after it is judged that the fault probability corresponding to the fault code is greater than or equal to the second threshold value, before the fault influence factor is obtained, the method further comprises the following steps:

[0021] The environmental influence degree corresponding to the fault code is obtained.

[0022] When the environment influence degree is greater than or equal to the third threshold value, the fault influence factor is acquired.

[0023] According to the technical scheme provided in the embodiments of the present application, the fault coefficient is calculated according to the following formula:

[0024] ;

[0025] Wherein, Y is the fault coefficient, A is the fault value corresponding to the fault level, B is the fault probability, b is the fault probability factor corresponding to the fault probability, C is the environment influence degree, and c is the environment influence factor corresponding to the environment influence degree.

[0026] According to the technical scheme provided in the embodiments of the present application, the fault information statistical database is used to guide the vehicle related personnel to pre-analyze the vehicle fault.

[0027] In the second aspect, the present application provides a fuel cell vehicle fault monitoring system, which is realized based on the above-mentioned fuel cell vehicle fault monitoring method, and the fuel cell vehicle fault monitoring system comprises:

[0028] The data acquisition module is configured to acquire the fault attribute information.

[0029] The processing module is configured to call the fault database according to the fault code in the fault attribute information, to obtain the fault level corresponding to the fault code; and when the fault level corresponding to the fault code is greater than or equal to the first threshold value, the fault probability corresponding to the fault code is acquired.

[0030] When the fault probability corresponding to the fault code is greater than or equal to the second threshold value, the fault influence factor is acquired.

[0031] The fault code, the fault occurrence time corresponding to the fault code, and the fault influence factor are added to the fault information statistical database.

[0032] In the third aspect, the present application provides a server, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above-mentioned fuel cell vehicle fault monitoring method when executing the computer program.

[0033] In the fourth aspect, the present application provides a computer readable storage medium, which has a computer program, and the computer program implements the steps of the above-mentioned fuel cell vehicle fault monitoring method when executed by a processor.

[0034] In conclusion, the application discloses a specific process of a fuel cell vehicle fault monitoring method.

[0035] The application obtains the fault code of the vehicle, calls the fault level and the fault probability corresponding to the fault code in the fault database, obtains the fault influence factor when the fault level and the fault probability meet the requirements at the same time, and adds the fault code, the fault occurrence time corresponding to the fault code and the fault influence factor to the fault information statistical database, so that the vehicle actual fault data are possessed in the fault information statistical database, thereby more accurate fault analysis results can be obtained when the vehicle fault is investigated subsequently. BRIEF DESCRIPTION OF DRAWINGS

[0036] Other features, objects and advantages of the application will become more apparent from the following detailed description of non-restrictive embodiments made with reference to the drawings:

[0037] Figure 1 It is a flowchart of the fuel cell vehicle fault monitoring method.

[0038] Figure 2 It is a flowchart of the fuel cell vehicle fault monitoring system.

[0039] Figure 3 It is a principle block diagram of a server.

[0040] Reference signs in the drawings: 1, data acquisition module; 2, processing module;

[0041] 500, server; 501, CPU; 502, ROM; 503, RAM; 504, bus; 505, I / O interface; 506, input part; 507, output part; 508, storage part; 509, communication part; 510, driver; 511, detachable medium. DETAILED DESCRIPTION

[0042] The application will be further described in detail below with reference to the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the related application, and are not a limitation on the application. In addition, it should be noted that, for the convenience of description, only the parts related to the application are shown in the drawings.

[0043] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0044] Embodiment 1

[0045] Please refer to Figure 1 The first embodiment of the flowchart of the fuel cell vehicle fault monitoring method provided by the present application is shown, which includes the following steps:

[0046] S10, obtaining fault attribute information; the fault attribute information at least includes: fault code, and fault occurrence time corresponding to the fault code;

[0047] Taking the fuel cell system of the fuel cell vehicle as an example, it has basic fault information data before leaving the factory, as shown in Table 1, which includes fault code, fault category corresponding to the fault code and fault position; for example, the fault code is L3, and the corresponding fault category can be obtained as hydrogen leakage, and the fault position is hydrogen cylinder valve rupture. Here, the source of the fault code and the corresponding fault occurrence time, for example, is obtained on the instrument panel of the fuel cell vehicle.

[0048] Table 1 Basic fault information data

[0049]

[0050] S20, according to the fault code in the fault attribute information, calling the fault database to obtain the fault level corresponding to the fault code; the fault database at least includes: fault code, and fault index corresponding to the fault code; the fault index includes: fault level and fault probability;

[0051] Here, the fault level is divided according to the fault performance characteristics, and the fault performance characteristics include detection fault, warning fault and functional fault, and the corresponding levels are 1, 2 and 3 respectively.

[0052] The fault probability is to collect and record the fault data of the fuel cell vehicle in the test process, and to obtain the cumulative test time, the cumulative failure number in the time, and finally to obtain the failure probability corresponding to the fault by using the Duane model.

[0053] Wherein, the fault database is shown in Table 2;

[0054] Table 2 Fault database

[0055]

[0056] As can be seen from Table 2, the fault level corresponding to the fault code L3 is 3.

[0057] S30, when it is judged that the fault level corresponding to the fault code is greater than or equal to the first threshold value, obtaining the fault probability corresponding to the fault code; for example, the first threshold value is set to 1, and the fault probability corresponding to the fault code L3 is 0.19.

[0058] S40, when it is judged that the fault probability corresponding to the fault code is greater than or equal to the second threshold value, obtaining the fault influence factor; for example, the second threshold value is set to 0.01.

[0059] S50, adding the fault code, the fault occurrence time corresponding to the fault code and the fault influence factor to the fault information statistical database to update the fault information statistical database; the fault information statistical database at least includes: the fault code, and the fault occurrence time and the fault influence factor corresponding to the fault code.

[0060] Wherein, obtaining the fault influence factor, specifically comprising the following steps:

[0061] When it is judged that the number of fault occurrence times corresponding to the fault code in the fault information statistical database is greater than or equal to 1, calculating the fault coefficient, and calculating the fault influence factor according to the fault coefficient.

[0062] The fault coefficient is calculated according to the following formula:

[0063] ;

[0064] Wherein, Y is the fault coefficient, A is the fault value corresponding to the fault level, B is the fault probability, b is the fault probability factor corresponding to the fault probability, C is the environmental influence degree, and c is the environmental influence factor corresponding to the environmental influence degree.

[0065] It is set that the fault values corresponding to the fault levels 1, 2, 3 and 4 are 0.1, 0.2, 0.3 and 0.4 respectively; as shown in Table 3, Table 3 is the fault probability factor corresponding to the fault probability range and the environmental influence factor corresponding to the environmental influence degree, according to Table 2, the corresponding fault level, fault probability and environmental influence degree corresponding to the corresponding fault code can be obtained, taking the fault code L3 as an example, the fault value corresponding to the fault level 3 is 0.3, the fault probability factor corresponding to the fault probability 0.19 is 0.6, the environmental influence factor corresponding to the environmental influence degree 1.5 is 0.4, and the calculated fault coefficient is 1.014.

[0066] Table 3 factor database

[0067]

[0068] According to the fault coefficient, the fault influence factor is calculated, specifically comprising the following steps:

[0069] Call the level database to find the fault coefficient range to which the fault coefficient belongs and the corresponding preset correction ratio; the level database includes: a fault coefficient range, and a preset correction ratio corresponding to the fault coefficient range;

[0070] The level database is shown in Table 4.

[0071] Table 4 Level database

[0072]

[0073] The fault coefficient calculated through the above steps is 1.014, and the corresponding preset correction ratio is 1.1.

[0074] The fault information statistical database is shown in Table 5.

[0075] Table 5 Fault information statistical database

[0076]

[0077] Traverse the fault information statistical database to obtain the stored fault influence factor; wherein the stored fault influence factor is: the fault influence factor corresponding to the fault occurrence time closest to the current fault code and the fault occurrence time corresponding to the fault code.

[0078] According to the preset correction ratio and the stored fault influence factor, the fault influence factor of the current fault occurrence time is calculated.

[0079] The current fault occurrence time of the fault code L3 is 2023.03.26, as shown in Table 5, the fault occurrence time closest to the current fault occurrence time is 2023.02.10, and the corresponding fault influence factor is 0.86, that is, the stored fault influence factor; according to the product of 0.86 and 1.1, the fault influence factor of the fault code L3 at the current fault occurrence time is obtained, which is 0.946.

[0080] The fault database further includes: an initial influence factor corresponding to the fault code;

[0081] The fault influence factor further includes the following steps:

[0082] When it is judged that the number of fault occurrence times corresponding to the fault code in the fault information statistical database is less than 1, the fault database is called, as shown in Table 2, to obtain the initial influence factor corresponding to the fault code as the fault influence factor corresponding to the fault code at the current fault occurrence time.

[0083] Here, the fault influence factor refers to the severity of damage or consequences to the lives or property of personnel and property; the initial influence factor in Table 2 refers to the data entered before the vehicle is shipped.

[0084] Furthermore, after determining that the fault probability corresponding to the fault code is greater than or equal to the second threshold, but before obtaining the fault impact factor, the following steps are also included:

[0085] Obtain the environmental impact corresponding to the fault code;

[0086] Here, environmental impact is one of the failure indicators. Environmental impact refers to the degree of impact on the environment. Taking hydrogen leakage as an example, it is classified according to the concentration of hydrogen gas leaked or emitted as a result of the failure, as shown in Table 6.

[0087] Table 6 Hydrogen Leakage Levels

[0088]

[0089] Based on Table 6, we can match the corresponding environmental impact degree for each fault code in the fault database.

[0090] When the environmental impact is determined to be greater than or equal to the third threshold, the fault impact factor is obtained; for example, the third threshold is set to 1.

[0091] This invention calculates a fault coefficient based on whether both the fault level and probability meet the requirements (i.e., the fault's impact on the vehicle reaches a certain level of danger). The fault coefficient is then assigned to a specific range in the fault coefficient database, along with a preset correction ratio. This preset correction ratio is then used to calculate the fault influence factor for the current fault occurrence time, based on the fault code's corresponding fault occurrence time closest to the fault code's occurrence time. The fault occurrence time and influence factor are then stored in a fault information statistics database to update the database, ensuring it contains actual vehicle fault influence factors for more accurate fault diagnosis. Furthermore, the fault information statistics database can guide vehicle personnel in pre-analysis of vehicle faults. On one hand, the database provides advance warnings to drivers regarding vehicle inspection and maintenance based on the time intervals between adjacent fault occurrences corresponding to the same fault code. On the other hand, maintenance personnel can analyze the impact of the current fault location on the entire vehicle by examining a series of fault influence factors corresponding to the same fault code in the database.

[0092] Example 2

[0093] like Figure 2 As shown, a fuel cell vehicle fault monitoring system is implemented based on the fuel cell vehicle fault monitoring method described in Example 1. The fuel cell vehicle fault monitoring system includes:

[0094] Data acquisition module 1 is configured to acquire fault attribute information; the fault attribute information includes at least: fault code, and the fault occurrence time corresponding to the fault code;

[0095] Processing module 2 is configured to call the fault database based on the fault code in the fault attribute information to obtain the fault level corresponding to the fault code; the fault database includes at least: fault code, and fault index corresponding to the fault code; the fault index includes: fault level and fault probability;

[0096] When the fault level corresponding to the fault code is greater than or equal to the first threshold, obtain the fault probability corresponding to the fault code;

[0097] When the probability of a fault corresponding to a fault code is greater than or equal to the second threshold, the fault impact factor is obtained.

[0098] Add the fault code, the fault occurrence time corresponding to the fault code, and the fault impact factor to the fault information statistics database to update the fault information statistics database; the fault information statistics database shall include at least: fault code, and the fault occurrence time and fault impact factor corresponding to the fault code.

[0099] Among them, the data acquisition module 1 is, for example, a data acquisition instrument LC-DAQ810; the processing module 2 is, for example, a Core i9-9880XE processor.

[0100] Example 3

[0101] A server includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of a fuel cell vehicle fault monitoring method as described in the above embodiments.

[0102] In this embodiment, as Figure 3 As shown, the server 500 includes a CPU (Central Processing Unit) 501, which can perform various appropriate actions and processes based on programs stored in ROM (Read-Only Memory) 502 or programs loaded from storage into RAM (Random Access Memory) 503. RAM 503 also stores various programs and data required for system operation. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An I / O (Input / Output) interface 505 is also connected to the bus 504.

[0103] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive is also connected to I / O interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 510 as needed so that computer programs read from it can be installed into storage section 508 as needed.

[0104] In particular, according to embodiments of the present invention, the above-described reference process Figure 1 The described process can be implemented as a computer software program. For example, Embodiment 3 of the present invention includes a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by the CPU (Central Processing Unit) 501, it performs the functions defined in the system of the present invention.

[0105] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium, a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, RAM (random access memory), ROM (read-only memory), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0106] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0107] The units described in the embodiments of the present invention can be implemented in software or hardware, and can also be located in a processor. The names of these units do not necessarily limit the specific unit itself. The described units or modules can also be located in a processor.

[0108] Example 4

[0109] The present invention also provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable storage medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement a fuel cell vehicle fault monitoring method as described in the above embodiments.

[0110] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for fault monitoring in a fuel cell vehicle, characterized in that, Includes the following steps: Obtain fault attribute information; The fault attribute information includes at least: a fault code, and the fault occurrence time corresponding to the fault code; Based on the fault code in the fault attribute information, the fault database is invoked to obtain the fault level corresponding to the fault code; the fault database includes at least: the fault code, and the fault index corresponding to the fault code; the fault index includes: fault level and fault probability; When the fault level corresponding to the fault code is greater than or equal to the first threshold, the fault probability corresponding to the fault code is obtained; When the probability of a fault corresponding to the fault code is greater than or equal to a second threshold, a fault impact factor is obtained; the fault impact factor refers to the severity of the damage or consequences to human life or property. The fault code, the fault occurrence time corresponding to the fault code, and the fault impact factor are added to the fault information statistics database; the fault information statistics database includes at least: the fault code, and the fault occurrence time and fault impact factor corresponding to the fault code; To obtain the factors affecting the failure, the following steps are involved: If the number of occurrence times corresponding to the fault code in the fault information statistics database is greater than or equal to 1, calculate the fault coefficient, and calculate the fault impact factor based on the fault coefficient. The failure coefficient is calculated using the following formula: ； Where Y is the fault coefficient, A is the fault value corresponding to the fault level, B is the fault probability, b is the fault probability factor corresponding to the fault probability, C is the environmental impact degree, and c is the environmental impact factor corresponding to the environmental impact degree.

2. The method for fault monitoring of a fuel cell vehicle according to claim 1, characterized in that, The calculation of the fault impact factor based on the fault coefficient specifically includes the following steps: The system retrieves the fault coefficient range and the corresponding preset correction ratio from the fault coefficient database. The fault coefficient database includes: the fault coefficient range and the preset correction ratio corresponding to the fault coefficient range. Traverse the fault information statistics database to obtain the existing fault impact factors; the existing fault impact factors are: the fault impact factors that are the same as the current fault code and are closest to the fault occurrence time of the corresponding fault code. The fault impact factor is calculated based on the preset correction ratio and the existing fault impact factor.

3. The method for fault monitoring of a fuel cell vehicle according to claim 1, characterized in that, The fault database also includes: the initial impact factor corresponding to the fault code; Obtaining the failure impact factors also includes the following steps: If the number of fault occurrence times corresponding to the fault code in the fault information statistics database is less than 1, the fault database is called to obtain the initial influence factor corresponding to the fault code, which is used as the fault influence factor corresponding to the fault code at the current fault occurrence time.

4. The method for fault monitoring of a fuel cell vehicle according to claim 1, characterized in that, After determining that the fault probability corresponding to the fault code is greater than or equal to the second threshold, and before obtaining the fault impact factor, the following steps are also included: Obtain the environmental impact corresponding to the fault code; When the environmental impact is determined to be greater than or equal to the third threshold, the fault impact factor is obtained.

5. A method for fault monitoring of a fuel cell vehicle according to claim 1, characterized in that, The fault information statistics database is used to guide vehicle-related personnel in conducting pre-analysis of vehicle faults.

6. A fuel cell vehicle fault monitoring system, implemented based on the fuel cell vehicle fault monitoring method according to any one of claims 1 to 5, characterized in that, The fuel cell vehicle fault monitoring system includes: The data acquisition module is configured to obtain fault attribute information. The processing module is configured to call the fault database based on the fault code in the fault attribute information to obtain the fault level corresponding to the fault code; When the fault level corresponding to the fault code is greater than or equal to the first threshold, the fault probability corresponding to the fault code is obtained; When the probability of a fault corresponding to the fault code is greater than or equal to a second threshold, a fault impact factor is obtained; the fault impact factor refers to the severity of the damage or consequences to life or property. Add the fault code, the fault occurrence time corresponding to the fault code, and the fault impact factor to the fault information statistics database; The processing module is specifically used to determine that when the number of fault occurrence times corresponding to the fault code in the fault information statistics database is greater than or equal to 1, calculate the fault coefficient, and calculate the fault impact factor based on the fault coefficient. The failure coefficient is calculated using the following formula: ； Where Y is the fault coefficient, A is the fault value corresponding to the fault level, B is the fault probability, b is the fault probability factor corresponding to the fault probability, C is the environmental impact degree, and c is the environmental impact factor corresponding to the environmental impact degree.

7. A server, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of a fuel cell vehicle fault monitoring method as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of a fuel cell vehicle fault monitoring method as described in any one of claims 1 to 5.

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