Vehicle fault diagnosis method and device, vehicle and storage medium

Abstract

The invention relates to the technical field of fault diagnosis, in particular to a vehicle fault diagnosis method and device, a vehicle and a storage medium, and the method is applied to a vehicle-mounted server, and comprises the steps: obtaining the device information and operation state data of a target vehicle; traversing the running state data of the vehicle, and judging whether the running state data is within a preset range based on the vehicle condition detection model to obtain first diagnosis information; the device type is identified based on the device information of the vehicle, a diagnosis mode corresponding to the device type is determined, the diagnosis mode comprises at least one of frequency detection, process detection and window detection, and second diagnosis information is obtained; and obtaining a fault diagnosis result of the target vehicle according to the first diagnosis information and the second diagnosis information. The system can diagnose and analyze the collected data in real time at the vehicle end, and monitor the running state of the vehicle end in an omnibearing manner.

Description

Technical Field

[0001] The present invention relates to the technical field of fault diagnosis, and in particular to a vehicle fault diagnosis method, device, vehicle and storage medium. Background Art

[0002] At present, the main form of vehicle-side status detection is that the vehicle-side equipment collects raw data and sends the data to the cloud server, where the data is processed to achieve vehicle-side fault diagnosis, such as the fault diagnosis method, device, communication equipment, readable storage medium and vehicle disclosed in CN117409499A. This solution proposes that the vehicle-side sends data to the cloud server. After receiving the vehicle-side data, the cloud server performs fault diagnosis on the vehicle-side data to generate fault diagnosis data, and sends the fault diagnosis data to the digital twin module for visual display of the vehicle-side data. Another example is a method, system, electronic device and program product for cloud diagnosis of vehicle PHM based on historical data disclosed in CN115755833A. This solution proposes that the vehicle-side data acquisition system collects raw data from each key system and component, and uploads the raw data to the cloud diagnosis platform. The cloud diagnosis platform then calls the diagnosis model library to analyze the vehicle-side data and gives an analysis report. The above-mentioned related technical solutions all emphasize that the vehicle-side only collects and uploads raw data, and the platform analyzes and displays the data.

[0003] In summary, the existing technology has the following problems: 1. Relying on the cloud to process data, when the connection with the platform is interrupted due to poor network, it is impossible to reliably and effectively analyze the data in real time. 2. Relying only on raw data, it is impossible to monitor the operating logic of the vehicle-side functions and achieve full monitoring of the vehicle-side operating status. 3. There is no corresponding treatment measure to recover after the fault is detected. Summary of the invention

[0004] The purpose of the present invention is to provide a vehicle fault diagnosis method, device, vehicle and storage medium, which can diagnose and analyze collected data in real time on the vehicle side and monitor the operating status of the vehicle side in all directions.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides a vehicle fault diagnosis method, which is applied to a vehicle-mounted server and includes: Obtain device information and operating status data of the target vehicle; Traversing the running status data of the vehicle, determining whether the running status data is within a preset range based on a vehicle condition detection model, and obtaining first diagnostic information; Identifying a device type based on the device information of the vehicle, determining a diagnostic method corresponding to the device type, the diagnostic method including at least one of frequency detection, process detection, and window detection, and obtaining second diagnostic information; A fault diagnosis result of the target vehicle is obtained according to the first diagnostic information and the second diagnostic information.

[0006] Further, the frequency detection includes: setting a first preset checkpoint at the business logic completion node, collecting and obtaining the number of reports of the first preset checkpoint within a preset time period; if the number of reports is within a preset number range, the frequency detection is determined to be qualified, otherwise the frequency detection is determined to be unqualified.

[0007] And / or, the process detection includes: setting a plurality of second preset checkpoints corresponding to a plurality of execution nodes of the business logic, collecting and obtaining a reporting order of the plurality of second preset checkpoints when the business logic is executed; if the reporting order is the same as the preset order, determining that the process detection is qualified, otherwise determining that the process detection is unqualified; And / or, the window detection includes: setting a first preset checkpoint at the business logic completion node, setting a third preset checkpoint at the business logic start node, and collecting and obtaining the reporting time difference between the first preset checkpoint and the third preset checkpoint after the business logic is completed; if the time difference is within the preset time range, the window detection is determined to be qualified, otherwise the window detection is determined to be unqualified.

[0008] Furthermore, when at least one of frequency detection, process detection and window detection is used to detect vehicle components, if any one of the frequency detection, process detection and window detection fails, the second diagnostic information is that a fault exists, otherwise the second diagnostic information is that a fault does not exist.

[0009] Further, obtaining a fault diagnosis result of the target vehicle according to the first diagnostic information and the second diagnostic information includes: If both the first diagnostic information and the second diagnostic information indicate that there is no fault, it is determined that there is no fault in the target vehicle; If the first diagnostic information and / or the second diagnostic information indicates that a fault exists, it is determined that a fault exists in the target vehicle.

[0010] Further, in response to a fault in the target vehicle, the fault information is transmitted to a fault recovery module, and a fault recovery action is performed.

[0011] Furthermore, after obtaining the fault diagnosis result of the target vehicle, it also includes: transmitting the fault diagnosis result of the target vehicle to a cloud server, and sending the fault diagnosis result of the target vehicle to a preset terminal through the cloud server for visual display.

[0012] Furthermore, the operating status data of the target vehicle includes vehicle software operating status information, vehicle system operating status information and vehicle hardware operating status information.

[0013] In a second aspect, the present invention provides a vehicle fault diagnosis device, the device comprising: An acquisition module, used to acquire device information and operating status data of a target vehicle; A first diagnostic module, used to traverse the running status data of the vehicle, determine whether the running status data is within a preset range based on the vehicle condition detection model, and obtain first diagnostic information; A second diagnostic module, identifying a device type based on the device information of the vehicle, determining a diagnostic method corresponding to the device type, wherein the diagnostic method includes at least one of frequency detection, process detection, and window detection, and obtaining second diagnostic information; An output module is used to obtain a fault diagnosis result of the target vehicle according to the first diagnostic information and the second diagnostic information.

[0014] In a third aspect, the present invention provides a vehicle, comprising the above-mentioned vehicle fault diagnosis device.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium having computer-readable instructions stored thereon, which, when executed by a processor of a computer, enables the computer to execute the above-mentioned vehicle fault diagnosis method.

[0016] The present invention has the following unexpected beneficial effects: 1. The vehicle fault diagnosis method of the present invention is applied to the vehicle-mounted server, so that the collected data can be reliably and real-timely diagnosed and analyzed on the vehicle side to obtain the diagnosis and analysis results, thus avoiding the problem of untimely vehicle fault diagnosis caused by poor network connection between the vehicle side and the cloud server in the prior art.

[0017] 2. The present invention performs multiple diagnoses on the collected data. On the one hand, the vehicle's operating status data is traversed, and based on the vehicle condition detection model, it is determined whether the operating status data is within a preset range to obtain the first diagnostic information, that is, the collected operating status data itself is diagnosed and analyzed to obtain the fault analysis result. On the other hand, the device type is identified based on the vehicle's device information, and the diagnostic method corresponding to the device type is determined. The diagnostic method includes at least one of frequency detection, process detection and window detection to obtain the second diagnostic information. By using a variety of diagnostic methods in combination, the vehicle-side operating status can be monitored in all directions, making the vehicle fault diagnosis more comprehensive and avoiding missed faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0019] Figure 1 A schematic flow chart of the vehicle fault diagnosis method in an embodiment of the present invention is shown.

[0020] Figure 2 The flowchart of the frequency detection in the embodiment of the present invention is shown.

[0021] Figure 3 A schematic diagram of the process flow of the process detection described in the embodiment of the present invention is shown.

[0022] Figure 4 A schematic diagram of the process of window detection in an embodiment of the present invention is shown.

[0023] Figure 5 A schematic diagram of the structure of the vehicle fault diagnosis method in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0024] The following will describe the embodiments of the present invention with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention, not for limiting the scope of protection of the present invention.

[0025] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention. The drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0026] In one embodiment, see Figure 1 As shown, the present invention provides a vehicle fault diagnosis method, which is applied to a vehicle-mounted server and includes: Obtain the device information and operating status data of the target vehicle. Through vehicle-mounted sensors or other data acquisition equipment, collect various key data of the vehicle in real time or regularly, including but not limited to engine speed, oil pressure, water temperature, vehicle speed, etc., as well as basic information such as the model and specifications of each device of the vehicle (such as sensors, actuators, etc.).

[0027] Traverse the vehicle's operating status data, determine whether the operating status data is within a preset range based on the vehicle condition detection model, and obtain the first diagnostic information. Through the preset vehicle condition detection model, analyze the collected operating status data one by one to determine whether the data is within the normal working range. This step can quickly identify abnormal conditions in vehicle operation, such as engine overheating, low oil pressure, etc., thereby generating the first diagnostic information.

[0028] Based on the vehicle's device information, the device type is identified, and a diagnostic method corresponding to the device type is determined, wherein the diagnostic method includes at least one of frequency detection, process detection, and window detection, to obtain second diagnostic information. Based on the device information, the system can identify the specific device type and select the most appropriate diagnostic method accordingly. Different devices may require different detection methods, such as frequency detection, process detection, or window detection, to ensure the pertinence and accuracy of the diagnosis.

[0029] The fault diagnosis result of the target vehicle is obtained according to the first diagnostic information and the second diagnostic information. By combining the first diagnostic information (based on the judgment of the running status data) and the second diagnostic information (based on the result of the diagnostic method of the device type), the system can more comprehensively evaluate the fault condition of the vehicle and give an accurate fault diagnosis result, thereby improving the accuracy and reliability of fault diagnosis.

[0030] The vehicle fault diagnosis method of the present invention combines the vehicle's operating status data and device information, diagnoses the vehicle from multiple dimensions, and improves the comprehensiveness of the diagnosis. The appropriate diagnostic method is selected according to the device type, making the diagnostic process more accurate and efficient. By collecting data in real time or regularly, vehicle faults can be discovered and handled in a timely manner to avoid the expansion of faults and more serious consequences. By using the vehicle condition detection model and the selection mechanism of the diagnostic method, the intelligent and automated fault diagnosis is realized, reducing the burden of manual diagnosis.

[0031] The vehicle fault diagnosis method described in the present invention is applied to the vehicle-mounted server, so that the collected data can be reliably and real-timely diagnosed and analyzed on the vehicle side to obtain the diagnosis and analysis results, thus avoiding the problem of untimely vehicle fault diagnosis caused by poor network connection between the vehicle side and the cloud server in the prior art.

[0032] The present invention performs multiple diagnoses on the collected data. On the one hand, it traverses the vehicle's operating status data, and determines whether the operating status data is within a preset range based on the vehicle condition detection model to obtain the first diagnostic information, that is, the collected operating status data itself is diagnosed and analyzed to obtain the fault analysis result. On the other hand, the device type is identified based on the vehicle's device information, and the diagnostic method corresponding to the device type is determined. The diagnostic method includes at least one of frequency detection, process detection and window detection to obtain the second diagnostic information. By using a variety of diagnostic methods in combination, the vehicle-side operating status can be monitored in all directions, making the vehicle fault diagnosis more comprehensive and avoiding missed faults.

[0033] In a preferred embodiment, frequency detection, process detection or window detection is realized by configuring checkpoints at preset node positions of business logic. A checkpoint is a set of IDs. When running business logic, the ID value can be reported to the checkpoint processing module through the interface. The checkpoint processing module needs to pre-configure the expected reporting logic of the checkpoint ID value, and compare the actual reported checkpoint logic with the preset logic during operation. If it does not match the preset logic, it is judged as a fault and the fault is reported to the fault recovery module. The fault recovery module needs to set corresponding fault recovery measures in advance according to each checkpoint reporting logic defined in the checkpoint processing module. When the checkpoint processing module reports the fault logic to the fault recovery module, the corresponding recovery measures can be executed. The vehicle end will also upload the detection information and recovery operation records to the platform for visual display and recording.

[0034] In a preferred embodiment, the frequency detection is mainly used to monitor whether a certain function on the vehicle side is running too frequently or too infrequently. Running a certain function or business logic too often or too infrequently poses a risk to the stability of the vehicle. Therefore, it is necessary to detect whether the vehicle side is running normally from the dimension of the number of function runs. For details, see Figure 2 As shown, the frequency detection includes: setting a first preset checkpoint at the business logic completion node, collecting and obtaining the number of reports of the first preset checkpoint within a preset time period; if the number of reports is within the preset number range, the frequency detection is determined to be qualified, otherwise the frequency detection is determined to be unqualified. For example, when the vehicle-side device is without a network, the number of network searches allowed within 10 minutes is set to 3 to 5 times, and if the number of network searches is not within the range, the network search is terminated.

[0035] Frequency detection is used to monitor whether a function on the vehicle side is running too much or too little. Running a function too much or too little may affect the stability of the system. For example, when the vehicle-side device is set to search the network continuously without a network, or when the system restarts due to an error, too frequent network searches or restarts will affect the normal use of the vehicle-side device. The current solution does not provide a universal monitoring method for the running frequency of the software function itself. Frequency detection provides a universal monitoring method for different functions, which improves the robustness of the system while reducing the amount of development.

[0036] In a preferred embodiment, the process detection is mainly used to determine whether the function logic of the controller is normal or to check whether the information interaction process between modules with information interaction is in line with expectations. Various working conditions may occur during the operation of the vehicle-side system, which may cause a certain function to not operate according to the original design logic. This monitoring method can identify this situation and handle it. For details, see Figure 3 As shown, the process detection includes: setting a number of second preset checkpoints corresponding to a number of execution nodes of the business logic, and collecting and obtaining the reporting order of the number of second preset checkpoints when the business logic is executed; if the reporting order is the same as the preset order, the process detection is determined to be qualified, otherwise the process detection is determined to be unqualified.

[0037] Process detection is mainly used to determine whether the function logic of the controller is normal or to check whether the information interaction process between modules with information interaction is in line with expectations. For example, the vehicle has bcall and ecall functions, which involve signal interaction between the vehicle controller and the vehicle computer, as well as complex business logic such as dialing, calling back, and signal transmission inside the vehicle controller. In the current solution, the controller and the vehicle computer mainly rely on heartbeat interaction to ensure that the other party works normally, and the specific interaction logic is not monitored. At the same time, there is no global supervision of the complex business logic inside the vehicle controller. If a problem occurs in one of the links and the dial fails, it will take more time to troubleshoot the problem. In this case, process detection can monitor the different steps of the function implementation, and compare the monitoring results with the preset expected results. If the match is successful, the function is normal; if the match fails, the function is abnormal, and the problem can be quickly located according to which step fails, and the repair logic for the problem can be triggered.

[0038] In a preferred embodiment, the window detection is used to detect whether a certain function of the vehicle end is completed within the specified time. When a certain function, i.e., the business logic, is completed within the time limit or has not been completed, it may affect the normal operation of other functions. Therefore, when a certain function is not completed within the specified time, the problem needs to be handled. For details, see Figure 4As shown, the window detection includes: setting a first preset checkpoint at the business logic completion node, setting a third preset checkpoint at the business logic start node, and collecting and obtaining the reporting time difference between the first preset checkpoint and the third preset checkpoint after the business logic is completed; if the time difference is within the preset time range, the window detection is determined to be qualified, otherwise the window detection is determined to be unqualified.

[0039] Window detection mainly tests whether a certain function on the vehicle side is completed within the specified time, such as the time calibration function on the vehicle side. Currently, many functions on the vehicle side depend on the current time, such as the appointment function, log recording, etc. If the vehicle side fails to calibrate the time for a long time, it will affect the normal use of other functions. For example, if the vehicle side cannot log in to the cloud platform for a long time, it will also affect the normal use of remote control, signal upload and other functions. In most current solutions, the completion time of a certain function is not monitored. Often, other related functions are started before a function is completed, which will cause the function to fail. For example: if the vehicle-side time calibration is not completed within a certain period of time, and the appointment function is triggered at this time, the appointment function will fail. To solve the above problems, window detection will calculate and judge the start and end time of specific functions. If a function is completed overtime or has not been completed, the preset recovery operation will be triggered to enhance the robustness of the system.

[0040] In a preferred embodiment, when at least one of frequency detection, process detection and window detection is used to detect vehicle components, if any one of the frequency detection, process detection and window detection fails, the second diagnostic information is that there is a fault, that is, if any detection method reveals that there is a potential problem with the component or does not meet the expected behavior, then the second diagnostic information is determined to be "there is a fault". This "one-vote veto" logic ensures the strictness and reliability of fault detection and avoids the possibility of missing faults due to the limitations of a single detection method. On the contrary, if all the detection methods used (any one of frequency detection, process detection and window detection) are qualified, that is, no abnormality or unexpected behavior is detected, then the second diagnostic information is determined to be "no fault", indicating that the component is healthy and working normally under the current detection conditions.

[0041] The present invention improves the sensitivity of identifying vehicle device faults by combining multiple detection methods, which helps to find potential problems early. And because of the "one-vote veto" logic, the accuracy and reliability of fault judgment are ensured, and the risk of misdiagnosis or missed diagnosis is reduced. At the same time, according to the characteristics of specific devices and detection requirements, suitable detection methods or combinations can be flexibly selected to improve detection efficiency and pertinence.

[0042] In a preferred embodiment, obtaining the fault diagnosis result of the target vehicle based on the first diagnostic information and the second diagnostic information includes: if the first diagnostic information and the second diagnostic information both indicate that there is no fault, then determining that the target vehicle has no fault; if the first diagnostic information and / or the second diagnostic information indicates that there is a fault, then determining that the target vehicle has a fault.

[0043] After determining that the target vehicle has a fault, the system can further combine the first diagnostic information and the second diagnostic information to locate the specific location and cause of the fault, which helps maintenance personnel find the problem more quickly and take appropriate maintenance measures to restore the normal operation of the vehicle.

[0044] In a preferred embodiment, in response to a fault in the target vehicle, fault information is transmitted to a fault recovery module, and a fault recovery action is performed.

[0045] The fault recovery module usually contains a series of preset fault handling strategies and recovery procedures, and can automatically select corresponding recovery measures according to different fault types. For example, for some simple faults, such as sensor failure or loose connection lines, the fault recovery module may directly recover by resetting the device, reconnecting the lines, etc.; while for more complex faults, such as engine failure or transmission system failure, it may be necessary to call professional maintenance programs or guide users to designated maintenance sites for processing.

[0046] Fault recovery actions are specific measures taken by the fault recovery module based on fault information and analysis results. These measures may include but are not limited to: 1) Automatic repair: For certain faults that can be automatically repaired, such as software errors or configuration errors, the fault recovery module can directly perform repair operations to restore the normal working state of the device. 2) Prompt the user: For faults that require user participation to solve, such as replacing parts or adjusting settings, the fault recovery module will send clear prompts to the user to guide the user to follow the instructions. 3) Contact maintenance personnel: For faults that cannot be automatically repaired and are difficult for users to solve by themselves, the fault recovery module will provide contact information or guide users to designated maintenance sites to obtain professional maintenance services.

[0047] Through this preferred implementation, the system can respond quickly and perform effective fault recovery actions when a fault occurs in the target vehicle, thereby ensuring the safety and reliability of the vehicle and improving user satisfaction and trust. For example, the fault recovery module is configured in advance to restart the CPU when the CPU load is too high, and the normal value of the CPU load rate is set to 80% in the vehicle condition detection module. When the CPU load rate is detected to be higher than 80% during actual operation, it is determined that a fault exists and reported to the fault recovery module to restart the CPU.

[0048] In a preferred embodiment, after obtaining the fault diagnosis result of the target vehicle, it also includes: transmitting the fault diagnosis result of the target vehicle to a cloud server, and sending the fault diagnosis result of the target vehicle to a preset terminal through the cloud server for visual display, providing users with a more convenient, intuitive and efficient fault handling experience.

[0049] The cloud server provides powerful data storage and management capabilities, which can save the vehicle's fault diagnosis results and other related information for a long time. This not only helps with subsequent fault analysis and vehicle maintenance, but also provides valuable data support for vehicle performance evaluation and improvement.

[0050] Through the cloud server, users can access the vehicle's fault diagnosis results anytime and anywhere, without having to go to the vehicle's location in person or rely on local devices. At the same time, the cloud server also supports multi-user sharing and collaboration, making it easier for maintenance teams, technicians and car owners to share fault information and solve problems together. In addition, cloud servers usually use advanced data encryption and security protection technologies to ensure the security and privacy protection of vehicle fault diagnosis results and other sensitive information during transmission and storage.

[0051] Visual display converts complex fault diagnosis results into intuitive charts, images or animations, making it easier for users to understand information such as the nature, location and severity of the fault. This helps users make decisions faster and take appropriate measures. In addition, through visual display on preset terminals (such as smartphones, tablets or computers, etc.), users can view the fault diagnosis results of the vehicle anytime and anywhere without relying on specific equipment or environment. This convenience greatly improves the user experience and satisfaction. In addition, the visual display not only provides intuitive fault information, but also provides relevant suggestions or solutions based on user needs. For example, the system can recommend suitable maintenance sites, parts or maintenance measures based on the fault diagnosis results to help users resume normal use of the vehicle faster.

[0052] In a preferred embodiment, the target vehicle's operating status data includes vehicle software operating status information, vehicle system operating status information, and vehicle hardware operating status information. The vehicle software operating status information includes memory usage, CPU load rate, and application monitoring status; the vehicle system operating status information includes operating system memory monitoring information, operating system CPU monitoring information, and operating system process number monitoring information; and the vehicle hardware operating status information includes controller temperature and power-on status.

[0053] In one embodiment, the present invention provides a vehicle fault diagnosis device, see Figure 5As shown, the device 10 includes an acquisition module 11, a first diagnostic module 12, a second diagnostic module 13 and an output module 14. The acquisition module 11 is used to acquire the device information and operating status data of the target vehicle. The first diagnostic module 12 is used to traverse the operating status data of the vehicle, determine whether the operating status data is within a preset range based on a vehicle condition detection model, and obtain first diagnostic information. The second diagnostic module 13 identifies the device type based on the device information of the vehicle, determines the diagnostic method corresponding to the device type, and the diagnostic method includes at least one of frequency detection, process detection and window detection to obtain second diagnostic information. The output module 14 is used to obtain the fault diagnosis result of the target vehicle based on the first diagnostic information and the second diagnostic information.

[0054] In one embodiment, the present invention provides a vehicle, comprising the above-mentioned vehicle fault diagnosis device.

[0055] In one embodiment, the present invention provides a computer-readable storage medium having computer-readable instructions stored thereon. When the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the above-mentioned vehicle fault diagnosis method.

[0056] The above embodiments are only preferred embodiments for fully illustrating the present invention, and the protection scope of the present invention is not limited thereto. Any equivalent substitution or change made by a person skilled in the art based on the present invention is within the protection scope of the present invention.

Claims

1. A vehicle fault diagnosis method, characterized in that: Applied to a vehicle-mounted server, the method comprises: Obtain device information and operating status data of the target vehicle; Traversing the running status data of the vehicle, determining whether the running status data is within a preset range based on a vehicle condition detection model, and obtaining first diagnostic information; Identifying a device type based on the device information of the vehicle, determining a diagnostic method corresponding to the device type, the diagnostic method including at least one of frequency detection, process detection, and window detection, and obtaining second diagnostic information; A fault diagnosis result of the target vehicle is obtained according to the first diagnostic information and the second diagnostic information.

2. The vehicle fault diagnosis method according to claim 1, characterized in that: The frequency detection includes: setting a first preset checkpoint at the business logic completion node, collecting and obtaining the number of reports of the first preset checkpoint within a preset time period; if the number of reports is within a preset number range, determining that the frequency detection is qualified, otherwise determining that the frequency detection is unqualified; And / or, the process detection includes: setting a plurality of second preset checkpoints corresponding to a plurality of execution nodes of the business logic, collecting and obtaining a reporting order of the plurality of second preset checkpoints when the business logic is executed; if the reporting order is the same as the preset order, determining that the process detection is qualified, otherwise determining that the process detection is unqualified; And / or, the window detection includes: setting a first preset checkpoint at the business logic completion node, setting a third preset checkpoint at the business logic start node, and collecting and obtaining the reporting time difference between the first preset checkpoint and the third preset checkpoint after the business logic is completed; if the time difference is within the preset time range, the window detection is determined to be qualified, otherwise the window detection is determined to be unqualified.

3. The vehicle fault diagnosis method according to claim 1, characterized in that: When at least one of frequency detection, process detection and window detection is used to detect vehicle components, if any one of the frequency detection, process detection and window detection fails, the second diagnostic information is that a fault exists, otherwise the second diagnostic information is that a fault does not exist.

4. The vehicle fault diagnosis method according to any one of claims 1 to 3, characterized in that: Acquiring a fault diagnosis result of the target vehicle according to the first diagnostic information and the second diagnostic information includes: If both the first diagnostic information and the second diagnostic information indicate that there is no fault, it is determined that there is no fault in the target vehicle; If the first diagnostic information and / or the second diagnostic information indicates that a fault exists, it is determined that a fault exists in the target vehicle.

5. The vehicle fault diagnosis method according to claim 4, characterized in that: In response to a fault in the target vehicle, the fault information is transmitted to the fault recovery module and a fault recovery action is performed.

6. The vehicle fault diagnosis method according to claim 1, characterized in that: After obtaining the fault diagnosis result of the target vehicle, it also includes: transmitting the fault diagnosis result of the target vehicle to a cloud server, and sending the fault diagnosis result of the target vehicle to a preset terminal through the cloud server for visual display.

7. The vehicle fault diagnosis method according to claim 1, characterized in that: The operating status data of the target vehicle includes vehicle software operating status information, vehicle system operating status information and vehicle hardware operating status information.

8. A vehicle fault diagnosis device, characterized in that: include: An acquisition module, used to acquire device information and operating status data of a target vehicle; A first diagnostic module, used to traverse the running status data of the vehicle, determine whether the running status data is within a preset range based on the vehicle condition detection model, and obtain first diagnostic information; A second diagnostic module, identifying a device type based on the device information of the vehicle, determining a diagnostic method corresponding to the device type, wherein the diagnostic method includes at least one of frequency detection, process detection, and window detection, and obtaining second diagnostic information; An output module is used to obtain a fault diagnosis result of the target vehicle according to the first diagnostic information and the second diagnostic information.

9. A vehicle, characterized in that: It comprises the vehicle fault diagnosis device as claimed in claim 8.

10. A computer-readable storage medium, characterized in that: Computer-readable instructions are stored thereon, and when the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the vehicle fault diagnosis method as claimed in any one of claims 1 to 7.

Images