Vehicle fault diagnosis method and device, electronic equipment and storage medium
By generating module identifiers and calling preset diagnostic interfaces to obtain diagnostic data, the problem of low fault diagnosis efficiency in traditional vehicle fault diagnosis methods is solved, and accurate identification and efficient diagnosis of sensor faults are achieved, improving the comprehensiveness and real-time performance of vehicle fault diagnosis.
Patent Information
- Application Number
- CN202511406197.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-29
- Publication Date
- 2025-11-21
AI Technical Summary
Traditional vehicle fault diagnosis methods rely on log-driven analysis, which leads to low fault investigation efficiency and insufficient fault location accuracy. They cannot keep track of the fault development dynamics in real time, and the massive amount of log information is complex and redundant, making it difficult to quickly filter out key fault information.
By generating module identifiers corresponding to the sensors and calling preset general diagnostic interfaces and preset dedicated diagnostic interfaces, diagnostic data reflecting the sensor's operating status can be obtained, fault analysis can be performed to determine the fault diagnosis results, thereby improving the accuracy and efficiency of diagnosis.
It achieves accurate identification and efficient diagnosis of sensor faults, reduces the complexity of interfacing different data processing modules with diagnostic modules, improves the comprehensiveness and adaptability of fault diagnosis, and ensures the real-time and reliability of vehicle fault diagnosis.
Smart Images
Figure CN120993891A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of autonomous driving technology, and in particular to a vehicle fault diagnosis method, device, electronic device, and storage medium. Background Technology
[0002] With the rapid iteration of automotive electronic intelligence, vehicles have evolved from simple mechanical carriers into intelligent terminals that rely on sensor networks to achieve environmental perception and intelligent operation. The widespread adoption of various sensors, such as LiDAR, millimeter-wave radar, and high-definition cameras, forms the core foundation for vehicles to perceive their surroundings, support intelligent driving functions, and make driving decisions. The stable operation of these sensors directly determines key performance indicators such as the accuracy of vehicle environmental perception and the reliability of intelligent driving functions. In this context, a malfunction in any vehicle sensor or its corresponding data processing module can lead to the failure of intelligent driving functions, abnormal powertrain systems, and even driving safety hazards. Therefore, accurate and efficient vehicle fault diagnosis is a crucial link in ensuring the safe and stable operation of vehicles and optimizing maintenance efficiency.
[0003] In the diagnostic module of the data abstraction and service platform, traditional fault testing mainly relies on log-driven analysis. This means that when a sensor or its corresponding data processing module malfunctions, developers can only try to identify fault-related traces and pinpoint the root cause by reviewing and analyzing log records. This method has significant drawbacks. Because sensors continuously collect massive amounts of data at high speeds, the resulting log information becomes complex and redundant. Effective fault clues are easily obscured by a large amount of irrelevant data, making it difficult for developers to quickly sift through the massive logs to extract key fault information. Furthermore, this method lacks real-time capability, relying solely on retrospective log analysis and failing to track the dynamic development of the fault in real time. This leads to low fault diagnosis efficiency and insufficient accuracy in fault location. Summary of the Invention
[0004] This disclosure provides a vehicle fault diagnosis method, device, electronic equipment, and storage medium to at least solve the problems of low fault diagnosis efficiency and insufficient fault location accuracy in related technologies.
[0005] According to a first aspect of the present disclosure, a vehicle fault diagnosis method is provided, comprising: In response to the first call request from the data processing modules corresponding to the multiple sensors in the target vehicle to the preset general diagnostic interface in the preset diagnostic module, a module identifier corresponding to the data processing module corresponding to the multiple sensors is generated, and the module identifier is sent to the corresponding data processing module; In response to a second call request from the target data processing module to any one of the at least one preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier, diagnostic data is obtained. The at least one preset dedicated diagnostic interface corresponds one-to-one with at least one preset dedicated diagnostic function. The target data processing module triggers the call request at different times for different preset dedicated diagnostic interfaces. The target data processing module is any one of the data processing modules corresponding to the plurality of sensors. The diagnostic data is data that can reflect the operating status of the target data processing module and / or the sensor corresponding to the target data processing module. Based on the diagnostic data, fault analysis is performed on the target data processing module and the corresponding sensor to determine the fault diagnosis result.
[0006] According to a second aspect of the present disclosure, a vehicle fault diagnosis device is provided, comprising: The module identifier generation module is used to generate module identifiers corresponding to the data processing modules corresponding to the multiple sensors in the target vehicle in response to the first call request of the preset general diagnostic interface in the preset diagnostic module, and send the module identifiers to the corresponding data processing modules. The diagnostic data acquisition module is used to respond to a second call request from the target data processing module to any one of the at least one preset dedicated diagnostic interfaces in the preset diagnostic modules based on a corresponding module identifier, and to obtain diagnostic data. The at least one preset dedicated diagnostic interface corresponds one-to-one with at least one preset dedicated diagnostic function. The target data processing module triggers the call request at different times for different preset dedicated diagnostic interfaces. The target data processing module is any one of the data processing modules corresponding to the plurality of sensors. The diagnostic data is data that can reflect the operating status of the target data processing module and / or the sensor corresponding to the target data processing module. The fault diagnosis result determination module is used to perform fault analysis on the target data processing module and the corresponding sensor based on the diagnostic data, and determine the fault diagnosis result.
[0007] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the method as described in any one of the first aspects above.
[0008] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided such that, when instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the method described in any of the first aspects of the present disclosure.
[0009] According to a fifth aspect of the present disclosure, a computer program product including instructions is provided that, when run on a computer, causes the computer to perform the method described in any of the first aspects of the present disclosure.
[0010] The technical solutions provided by the embodiments of this disclosure have at least the following beneficial effects: By responding to the first call requests from the data processing modules corresponding to multiple sensors in the target vehicle to the preset general diagnostic interfaces in the preset diagnostic module, a module identifier for each data processing module is generated and sent, enabling unique and accurate identification of each data processing module within the preset diagnostic module. Simultaneously, by responding to the second call requests from the target data processing module to any interface of at least one preset dedicated diagnostic interface in the preset diagnostic module based on the corresponding module identifier, and leveraging the one-to-one correspondence between preset dedicated diagnostic interfaces and preset dedicated diagnostic functions, and the different timing of call requests triggered by the target data processing module to different preset dedicated diagnostic interfaces, the system can target the target data processing module and its corresponding sensors at different operating stages. The system performs targeted fault analysis based on the status of the segment; by acquiring diagnostic data that reflects the operating status of the target data processing module and / or corresponding sensors, and based on this diagnostic data, it performs fault analysis on the target data processing module and corresponding sensors to determine the fault diagnosis results, thereby improving the accuracy and reliability of the fault diagnosis results; in addition, the setting of a preset universal diagnostic interface reduces the complexity of interfacing different data processing modules with the preset diagnostic module, improves the adaptability of the preset diagnostic module to the data processing modules corresponding to multiple sensors in the target vehicle, and the targeted design of the preset dedicated diagnostic interface ensures the professionalism and effectiveness of each diagnostic function, thereby improving the efficiency and comprehensiveness of the fault diagnosis of the target vehicle as a whole.
[0011] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description
[0012] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.
[0013] Figure 1 This is a flowchart illustrating a vehicle fault diagnosis method according to an exemplary embodiment; Figure 2 This is a schematic diagram illustrating a process of obtaining diagnostic data in response to a second call request from a target data processing module to any one of the preset dedicated diagnostic interfaces in at least one preset dedicated diagnostic interface in a preset diagnostic module based on a corresponding module identifier, according to an exemplary embodiment. Figure 3This is a schematic diagram illustrating another process of obtaining diagnostic data in response to a second call request from a target data processing module to any one of the preset dedicated diagnostic interfaces in a preset diagnostic module based on a corresponding module identifier, according to an exemplary embodiment. Figure 4 This is a schematic diagram illustrating another process of obtaining diagnostic data in response to a second call request from a target data processing module to any one of the preset dedicated diagnostic interfaces in a preset diagnostic module based on a corresponding module identifier, according to an exemplary embodiment. Figure 5 This is a schematic diagram illustrating a process, according to an exemplary embodiment, of updating a preset diagnostic module to a preset backup diagnostic module when the operation indication information indicates that the preset diagnostic module is malfunctioning, so as to continue fault analysis of the target data processing module and the corresponding sensor. Figure 6 This is a block diagram of a vehicle fault diagnosis device according to an exemplary embodiment; Figure 7 This is a block diagram illustrating an electronic device for vehicle fault diagnosis according to an exemplary embodiment. Detailed Implementation
[0014] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.
[0015] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar different contents and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.
[0016] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties.
[0017] Figure 1 This is a flowchart illustrating a vehicle fault diagnosis method according to an exemplary embodiment. This vehicle fault diagnosis method is applied to electronic devices such as servers. Figure 1 As shown, it includes the following steps: In step S101, in response to the first call request from the data processing modules corresponding to the multiple sensors in the target vehicle to the preset general diagnostic interface in the preset diagnostic module, a module identifier corresponding to the data processing module corresponding to the multiple sensors is generated, and the module identifier is sent to the corresponding data processing module.
[0018] In one specific embodiment, the sensor is a device on the target vehicle used to collect information about the internal and external environment or its own operating status. The data processing module is a corresponding module in the target vehicle for each sensor, used to receive and process the raw data collected by the corresponding sensor, and can also actively initiate a call request to the preset diagnostic module to participate in fault diagnosis. The preset diagnostic module is the module in the target vehicle responsible for fault diagnosis, used to receive call requests from each data processing module. The preset general diagnostic interface is a specific interface set in the preset diagnostic module; it does not have specific fault diagnosis functions, but is used to respond to the first call request from the data processing module, generate a unique module identifier for each data processing module and send it to the corresponding module, achieving unique identification of the data processing module within the preset diagnostic module.
[0019] In step S103, in response to the second call request from the target data processing module to any one of the preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier, diagnostic data is obtained.
[0020] In one specific embodiment, at least one preset dedicated diagnostic interface corresponds one-to-one with at least one preset dedicated diagnostic function. The timing of the triggering call request for different preset dedicated diagnostic interfaces by the target data processing module is different. The target data processing module is any data processing module among the data processing modules corresponding to multiple sensors. The diagnostic data is data that can reflect the operating status of the target data processing module and / or the sensor corresponding to the target data processing module.
[0021] In a specific embodiment, the preset dedicated diagnostic interface is an interface set in the preset diagnostic module that implements its respective specific diagnostic function. It is used by the target data processing module to initiate a second call request based on the corresponding module identifier to obtain diagnostic data.
[0022] In one specific embodiment, the second call request carries a module identifier so that any preset dedicated diagnostic interface can identify the specific data processing module that initiated the call.
[0023] In step S105, based on the diagnostic data, fault analysis is performed on the target data processing module and the corresponding sensor to determine the fault diagnosis result.
[0024] In one specific embodiment, the fault diagnosis results can indicate whether the current fault originates from an abnormality in the reception or processing of the target data processing module, an abnormality in the transmission of the corresponding sensor, or a problem with the transmission link between the target data processing module and the corresponding sensor.
[0025] In one specific embodiment, at least one preset dedicated diagnostic function includes a preset timeout diagnostic function, and at least one preset dedicated diagnostic interface includes a preset timeout diagnostic interface. When the second call request is a call request from the target data processing module to the preset timeout diagnostic interface, the second call request is triggered after the target data processing module receives the raw data. The raw data is the data sent from the corresponding sensor to the target data processing module. The second call request includes the first timeout diagnostic interface call request and the non-first timeout diagnostic interface call requests. The diagnostic data includes the cumulative number of timeouts in the target data processing module receiving the corresponding raw data within a first preset time period.
[0026] In a specific embodiment, such as Figure 2 As shown, in response to the second call request from the target data processing module to any one of the preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier, the diagnostic data obtained includes: In step S201, in response to the target data processing module's first timeout diagnosis interface call request to the preset timeout diagnosis interface based on the corresponding module identifier, the first call time corresponding to the first timeout diagnosis interface call request is obtained, and the first call time is used as the previous call time.
[0027] In one specific embodiment, the last call time is the time when the target data processing module last received the corresponding raw data.
[0028] In a specific embodiment, the above-mentioned response to the target data processing module's first timeout diagnosis interface call request to the preset timeout diagnosis interface based on the corresponding module identifier, obtaining the first call time corresponding to the first timeout diagnosis interface call request, and using the first call time as the previous call time may include: when the target data processing module initiates the first timeout diagnosis interface call request to the preset timeout diagnosis interface based on its own corresponding module identifier, the preset diagnosis module will respond to the request, obtain the time corresponding to this first call request as the first call time, and set the first call time as the previous call time required for subsequent timeout judgment.
[0029] In step S203, in response to the target data processing module's non-first timeout diagnosis interface call request to the preset timeout diagnosis interface based on the corresponding module identifier, the current call time corresponding to the non-first timeout diagnosis interface call request is obtained.
[0030] In a specific embodiment, the detailed process of obtaining the current call time corresponding to the non-first timeout diagnosis interface call request of the preset timeout diagnosis interface based on the corresponding module identifier by the target data processing module can be found in step S201 above. The process of obtaining the first call time corresponding to the first timeout diagnosis interface call request of the preset timeout diagnosis interface based on the corresponding module identifier by the target data processing module can be found in step S201 above. This will not be repeated here.
[0031] In one specific embodiment, the current call time is the time when the target data processing module receives the corresponding raw data this time.
[0032] In step S205, if the difference between the time interval between the current call time and the previous call time and the first preset transmission frequency is greater than a preset threshold, it is determined that the target data processing module has timed out of receiving data this time, and the preset timeout number is updated.
[0033] In one specific embodiment, the first preset transmission frequency is the time frequency at which the corresponding sensor sends corresponding raw data to the target data processing module. The preset threshold can be set according to the actual situation.
[0034] In one specific embodiment, the preset timeout number is initially zero.
[0035] In step S207, the current call time is updated to the previous call time.
[0036] In step S209, the steps of repeatedly responding to the non-first timeout diagnosis interface call request of the target data processing module based on the corresponding module identifier to the preset timeout diagnosis interface, obtaining the current call time corresponding to the non-first timeout diagnosis interface call request and updating the current call time to the previous call time are repeated.
[0037] In step S211, when the end time corresponding to the first preset time period is reached, the current preset timeout number is taken as the cumulative timeout number.
[0038] In the above embodiments, the timeout is determined by comparing the time interval between the current call time and the previous call time with the corresponding sensor's original data transmission frequency (first preset transmission frequency). This makes the timeout judgment match the actual data transmission pattern of the sensor, improves the ability of the preset diagnostic module to diagnose the timeliness of the target data processing module's receipt of original data, and further enhances the comprehensiveness and reliability of the preset diagnostic module's diagnosis of the target data processing module and the corresponding sensor's operating status.
[0039] In one specific embodiment, at least one preset dedicated diagnostic function includes a preset packet loss diagnostic function, and at least one preset dedicated diagnostic interface includes a preset packet loss diagnostic interface. When the second call request is a call request from the target data processing module to the preset packet loss diagnostic interface, the second call request is triggered after the target data processing module receives the raw data. The raw data is the data sent to the target data processing module by the corresponding sensor. The second call request includes an initial packet loss diagnostic interface call request and a non-initial packet loss diagnostic interface call request. The initial packet loss diagnostic interface call request carries an initial sequence number identifier, and the non-initial packet loss diagnostic interface call request carries a current sequence number identifier. The current sequence number identifier is the sequence number identifier corresponding to the corresponding raw data received by the target data processing module this time. The diagnostic data includes the cumulative number of packet losses received by the target data processing module for the corresponding raw data within a second preset time period.
[0040] For example, the initial sequence number can be set to 0. The value range of the above sequence number can be limited to 0-255, forming a complete sequence number cycle.
[0041] In a specific embodiment, when the second call request is a call request from the target data processing module to the preset packet loss diagnosis interface, the second call request also carries a preset maximum sequence number identifier, which, for example, can be 255. When a sequence number cycle ends (i.e., the sequence number identifier increments from 0 to 255) and the next sequence number cycle needs to be started, the preset maximum sequence number identifier will play its functional role; specifically, the preset maximum sequence number identifier is used to clarify the termination boundary of the current sequence number cycle and the start of the next current sequence number cycle, so as to ensure that if the sequence number identifier carried by the previous call request is 255 (i.e., the current cycle has ended), it can be determined that the sequence number identifier carried by the currently initiated call request should be 0.
[0042] In a specific embodiment, such as Figure 3 As shown, in response to the second call request from the target data processing module to any one of the preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier, the diagnostic data obtained includes: In step S301, in response to the target data processing module’s first packet loss diagnosis interface call request to the preset packet loss diagnosis interface based on the corresponding module identifier, the first sequence number identifier is used as the previous sequence number identifier.
[0043] In one specific embodiment, the previous sequence number identifier is the sequence number identifier corresponding to the original data previously received by the target data processing module.
[0044] In a specific embodiment, the above-mentioned response to the target data processing module's first packet loss diagnosis interface call request to the preset packet loss diagnosis interface based on the corresponding module identifier, using the first sequence number identifier as the previous sequence number identifier, may include: when the target data processing module initiates the first packet loss diagnosis interface call request to the preset packet loss diagnosis interface based on its own corresponding module identifier, the preset diagnosis module will respond to the request and set the first sequence number identifier carried in this call request as the previous sequence number identifier required for subsequent packet loss judgment.
[0045] In step S303, in response to the target data processing module's non-first packet loss diagnosis interface call request to the preset packet loss diagnosis interface based on the corresponding module identifier, if the previous sequence number identifier and the current sequence number identifier are not consecutive, it is determined that the target data processing module has lost packets in the received data, and the preset packet loss count is updated.
[0046] In one specific embodiment, the initial number of packet loss attempts is preset to zero.
[0047] In step S305, the current sequence number identifier is updated to the previous sequence number identifier.
[0048] In step S307, the non-first packet loss diagnosis interface call request from the target data processing module to the preset packet loss diagnosis interface based on the corresponding module identifier is repeatedly responded to. If the previous sequence number identifier and the current sequence number identifier are not consecutive, it is determined that the target data processing module has lost data, and the preset packet loss count is updated to the step of updating the current sequence number identifier to the previous sequence number identifier.
[0049] In step S309, when the end time corresponding to the second preset time period is reached, the current preset number of packet losses is taken as the cumulative number of packet losses.
[0050] In the above embodiments, by using the continuity check between the previous sequence number identifier and the current sequence number identifier, packet loss can be directly and accurately identified, which improves the diagnostic capability of the preset diagnostic module for the integrity of data reception of the data processing module, and further enhances the comprehensiveness and reliability of the preset diagnostic module for the operation status diagnosis of the target data processing module and the corresponding sensor.
[0051] In one specific embodiment, at least one preset dedicated diagnostic function includes a preset reception count diagnostic function, and at least one preset dedicated diagnostic interface includes a preset reception count statistics interface. When the second call request is a call request from the target data processing module to the preset reception count statistics interface, the second call request is triggered after the target data processing module receives the raw data. The raw data is the data sent by the corresponding sensor to the target data processing module, and the diagnostic data includes the cumulative number of times the target data processing module receives the corresponding raw data within a third preset time period.
[0052] In a specific embodiment, such as Figure 4 As shown, in response to the second call request from the target data processing module to any one of the preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier, the diagnostic data obtained includes: In step S401, in response to the second call request from the target data processing module to the preset reception count statistics interface based on the corresponding module identifier, the preset reception count is updated.
[0053] In one specific embodiment, the preset number of receptions is initially zero.
[0054] In step S403, the above steps of updating the preset number of receptions in response to the second call request from the target data processing module to the preset reception count statistics interface based on the corresponding module identifier are repeated.
[0055] In step S405, if the end time corresponding to the third preset time period is reached, the current preset number of receptions is taken as the cumulative number of receptions.
[0056] In the above embodiments, the target data processing module updates the preset number of receptions in real time based on the second call request initiated by the corresponding module identifier, providing a basis for judging the continuity and stability of data transmission between the target data processing module and the corresponding sensor, and further improving the comprehensiveness and reliability of the preset diagnostic module in diagnosing the operating status of the target data processing module and the corresponding sensor.
[0057] In one specific embodiment, at least one preset dedicated diagnostic function includes a preset latency statistics function, and at least one preset dedicated diagnostic interface includes a preset latency statistics interface. When the second call request is a call request from the target data processing module to the preset latency statistics interface, the second call request is triggered after the target data processing module sends the target data. The target data is the data processed by the target data processing module after processing the original data. The original data is the data sent to the target data processing module by the corresponding sensor. The second call request carries the data processing time, which is the time taken for the target data processing module to process the corresponding original data to obtain the corresponding target data and send the corresponding target data from the time it receives the corresponding original data. The diagnostic data includes the data processing and analysis data corresponding to the target data processing module within the fourth preset time period.
[0058] In a specific embodiment, the diagnostic data obtained in response to the second invocation request from the target data processing module to any one of the preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier includes: In response to the second call request from the target data processing module to the preset delay statistics interface based on the corresponding module identifier within the fourth preset time period, the data processing and analysis data is determined based on multiple data processing times within the fourth preset time period.
[0059] In one specific embodiment, the data processing and analysis data can characterize the data processing latency of the target data processing module within a fourth preset time period, reflecting the target data processing module's processing efficiency, latency stability, and the presence of abnormal latency, among other operational characteristics. For example, the data processing and analysis data may include at least one of the following: the average data processing time of the target data processing module within the fourth preset time period, the maximum and minimum values of the data processing time, and the fluctuation range of the data processing time.
[0060] In the above embodiments, the data processing and analysis data is determined based on multiple data processing times within the fourth preset time period. This can reflect the processing latency change trend and overall performance of the target data processing module within that time period, promptly identify abnormal latency situations in the data processing process, provide a basis for evaluating the operating efficiency of the target data processing module, and further improve the comprehensiveness and accuracy of the preset diagnostic module in diagnosing faults in the target data processing module and corresponding sensors.
[0061] In one specific embodiment, the diagnostic data includes the cumulative number of timeouts in the target data processing module receiving the corresponding raw data within a first preset time period, the cumulative number of packet losses in the target data processing module receiving the corresponding raw data within a second preset time period, the cumulative number of receptions in the target data processing module receiving the corresponding raw data within a third preset time period, and the data processing and analysis data corresponding to the target data processing module within a fourth preset time period.
[0062] In a specific embodiment, the above-mentioned fault analysis of the target data processing module and corresponding sensor based on diagnostic data, and the determination of the fault diagnosis results, include: Based on the correlation analysis of the cumulative timeouts, cumulative packet losses, cumulative receptions, and data processing analysis data, fault analysis is performed on the target data processing module and the corresponding sensors to determine the fault diagnosis results.
[0063] In a specific embodiment, after step S101, in response to the first call request from the data processing modules corresponding to the multiple sensors in the target vehicle to the preset general diagnostic interface in the preset diagnostic module, generating module identifiers corresponding to the data processing modules corresponding to the multiple sensors, and sending the module identifiers to the corresponding data processing modules, the method further includes: setting up a dedicated status detection unit for each data processing module that successfully calls the preset general diagnostic interface, so that the dedicated status detection unit can perform fault analysis on the data processing module and the corresponding sensor based on the correlation analysis of the cumulative timeouts, cumulative packet losss, cumulative receptions, and data processing analysis data of the corresponding data processing module, and determine the fault diagnosis result.
[0064] In a specific embodiment, based on the correlation analysis of the cumulative timeout count, cumulative packet loss count, cumulative reception count, and data processing analysis data, the fault analysis of the target data processing module and corresponding sensor to determine the fault diagnosis result may include: when performing fault analysis on the target data processing module and corresponding sensor, using the cumulative reception count as a reference, if the cumulative reception count is less than a preset reception count, analyzing whether frequent timeouts when the target data processing module receives raw data cause some data to fail to be received in time, thereby reducing the total reception count, by correlating with the cumulative timeout count; simultaneously correlating with the cumulative packet loss count to confirm whether... The insufficient number of receptions is caused by the direct loss of raw data during transmission. This clarifies whether the abnormal total number of receptions stems from timeouts, packet loss, or a combination of both. Further analysis of the coordinated changes in the cumulative number of timeouts and packet loss points pinpoints problems in the transmission link or the target data processing module itself. Simultaneously, cross-validation is performed using data processing analysis data to determine the impact of the target data processing module's processing status on the receiving stage or anomalies in the sensors and transmission link. Finally, through the correlation analysis of the above multi-dimensional data, the cause of the fault is determined to be an abnormality in the receiving or processing of the target data processing module, an abnormality in the transmission of the corresponding sensor, or a problem with the transmission link, thus forming a fault diagnosis result.
[0065] For example, based on the correlation analysis of the cumulative timeout count, cumulative packet loss count, cumulative reception count, and data processing analysis data, the above-mentioned fault analysis of the target data processing module and corresponding sensor to determine the fault diagnosis results may include: First, using the cumulative reception count as the basic reference for data transmission and reception, it is first determined whether it exceeds the preset reception count. If the cumulative reception count is less than the preset reception count, the cumulative timeout count is further correlated to investigate whether the frequent timeouts when the target data processing module receives raw data have caused some data to be not received in time, thus reducing the total reception. At the same time, the cumulative packet loss count is correlated to confirm whether the insufficient reception count is caused by data being directly lost during transmission. Next, the synergistic relationship between the cumulative timeout count and the cumulative packet loss count is analyzed. If both exceed the preset timeout count and the preset packet loss count, the transmission link between the target data processing module and the corresponding sensor is first investigated for problems such as signal instability and insufficient bandwidth. If only the cumulative timeout count exceeds the preset timeout count while the cumulative packet loss count is less than the preset packet loss count, the analysis focuses on the target data processing module itself. The system checks for issues such as delayed response at the receiving port or abnormal internal data buffering mechanisms that could lead to timeouts. Simultaneously, it cross-validates and deeply correlates the processed data with the three types of data mentioned above. For example, if the processed data indicates that the target data processing module's average processing time for raw data is too long, and the processing latency fluctuates significantly, and the cumulative timeout count exceeds the preset limit, it can be inferred that the root cause of the fault may lie in the target data processing module's insufficient processing capacity. This means the module cannot complete processing and transmission of the received raw data in a timely manner, indirectly causing timeouts in the receiving stage. If the processed data indicates that the target data processing module's latency for processing raw data is stable and its processing efficiency is normal, but the cumulative packet loss count exceeds the preset limit, the troubleshooting will shift to the corresponding sensor. This will determine whether there is a hardware fault at the sensor's transmitting end, an abnormal data transmission frequency, or a data loss in the transmission link. This process determines whether the fault originates from an abnormality in the target data processing module's reception or processing, or from an abnormality in the corresponding sensor's transmission or a problem in the transmission link, ultimately forming a fault diagnosis result.
[0066] In the above embodiments, by incorporating the cumulative number of timeouts, cumulative number of packet losses, cumulative number of receptions, and data processing and analysis data into the fault analysis and performing correlation analysis, the operating status of the target data processing module and the corresponding sensor can be comprehensively evaluated from multiple dimensions such as the timeliness, completeness, total amount of data reception, and processing latency characteristics, avoiding the one-sidedness caused by relying on a single diagnostic data. Furthermore, the correlation analysis of multi-dimensional data can effectively uncover the potential connections between different diagnostic data, thereby more accurately locating whether the root cause of the fault originates from the target data processing module or the corresponding sensor, significantly improving the accuracy and comprehensiveness of the fault diagnosis results.
[0067] In a specific embodiment, when it is confirmed that the number of data processing modules currently in a normal response state is less than the number of data processing modules initially registered (i.e., the number of data processing modules that successfully call the preset general diagnostic interface), it can be directly determined that the relevant system of the target vehicle has malfunctioned. The malfunction information is promptly transmitted through a preset warning signal so that relevant personnel can quickly detect it, thereby conducting investigation and handling, and preventing the malfunction from escalating further.
[0068] In a specific embodiment, such as Figure 5 As shown, the above method also includes: In step S501, based on the second preset transmission frequency, the operation indication information of the preset diagnostic module is sent to the preset monitoring system so that the preset monitoring system can determine the operation status of the preset diagnostic module.
[0069] In one specific embodiment, the operation indication information is used to indicate the operating status of the preset diagnostic module. For example, the operation indication information can be the heartbeat polling signal of the preset diagnostic module. Specifically, the heartbeat polling signal can start from 0, have a maximum value of 255, and be sent to the preset monitoring system every 100ms (i.e., the second preset transmission frequency can be 100ms).
[0070] In one specific embodiment, the preset monitoring system is used to receive operation instruction information sent by the preset diagnostic module in order to determine the operating status of the preset diagnostic module. For example, the preset monitoring system can be a software monitoring module deployed independently in the diagnostic system, or it can be a functional unit integrated into the overall control platform.
[0071] In step S503, if the operation indication information indicates that the preset diagnostic module is malfunctioning, the preset backup diagnostic module is updated to the preset diagnostic module so as to continue to perform fault analysis on the target data processing module and the corresponding sensor.
[0072] In one specific embodiment, the preset backup diagnostic module is a backup module configured in advance to deal with the failure of the preset diagnostic module. When the preset diagnostic module fails to work properly, it can take over the diagnostic work of the target data processing module and the corresponding sensor, thereby ensuring the normal operation of the fault analysis.
[0073] For example, when the operation indication information is a heartbeat polling signal of a preset diagnostic module, which starts from 0, has a maximum value of 255, and is sent to the preset monitoring system every 100ms (i.e., the second preset transmission frequency can be 100ms), the above-mentioned update of the preset backup diagnostic module to the preset diagnostic module to continue fault analysis of the target data processing module and the corresponding sensor when the operation indication information indicates that the preset diagnostic module is operating abnormally may include: if the interval between the release of the operation indication information exceeds 100ms, the signal value jumps or exceeds the range of 0-255, or no signal is received for several consecutive cycles, etc., which are inconsistent with the normal pattern (under normal circumstances, the operation indication information should strictly follow the pattern of being released once every 100ms, with the value starting from 0 and gradually increasing to 255 and then cyclically resetting to 0), then it is determined that the preset diagnostic module is operating abnormally, and the preset backup diagnostic module is immediately updated to the preset diagnostic module to continue fault analysis of the target data processing module and the corresponding sensor.
[0074] In the above embodiments, when the operation indication information indicates that the preset diagnostic module is malfunctioning, it is updated to the preset backup diagnostic module. This avoids the problem of fault analysis interruption caused by the malfunction of the preset diagnostic module, ensures the continuous development of fault analysis work for the target data processing module and the corresponding sensor, and improves the reliability and risk resistance of the entire fault diagnosis system.
[0075] Figure 6 This is a block diagram illustrating a vehicle fault diagnosis device according to an exemplary embodiment. (Refer to...) Figure 6 The device includes: The module identifier generation module 610 is used to generate module identifiers corresponding to the data processing modules of multiple sensors in the target vehicle in response to the first call request of the preset general diagnostic interface in the preset diagnostic module, and send the module identifiers to the corresponding data processing modules. The diagnostic data acquisition module 620 is used to respond to a second call request from the target data processing module to any one of the preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier, and to obtain diagnostic data. The at least one preset dedicated diagnostic interface corresponds one-to-one with at least one preset dedicated diagnostic function. The target data processing module triggers the call request at different times for different preset dedicated diagnostic interfaces. The target data processing module is any one of the data processing modules corresponding to multiple sensors. The diagnostic data is data that can reflect the operating status of the target data processing module and / or the sensor corresponding to the target data processing module. The fault diagnosis result determination module 630 is used to perform fault analysis on the target data processing module and the corresponding sensor based on diagnostic data, and determine the fault diagnosis result.
[0076] In an optional embodiment, the diagnostic data acquisition module 620 includes: The last call time determination unit is used to respond to the first timeout diagnosis interface call request of the target data processing module based on the corresponding module identifier to the preset timeout diagnosis interface, obtain the first call time corresponding to the first timeout diagnosis interface call request, and use the first call time as the last call time. The last call time is the time when the target data processing module last received the corresponding raw data. The current call time determination unit is used to respond to the non-first timeout diagnosis interface call request of the target data processing module to the preset timeout diagnosis interface based on the corresponding module identifier, and to obtain the current call time corresponding to the non-first timeout diagnosis interface call request. The current call time is the time when the target data processing module receives the corresponding raw data this time. The preset timeout update unit is used to determine that the target data processing module has timed out when the difference between the time interval between the current call time and the previous call time and the first preset transmission frequency is greater than a preset threshold, and to update the preset timeout count. The first preset transmission frequency is the time frequency at which the corresponding sensor sends the corresponding raw data to the target data processing module, and the preset timeout count is initially zero. The last call time update unit is used to update the current call time to the last call time; The first repeating unit is used to repeatedly respond to the non-first timeout diagnosis interface call request of the target data processing module based on the corresponding module identifier to the preset timeout diagnosis interface, and to obtain the current call time corresponding to the non-first timeout diagnosis interface call request up to the step of updating the current call time to the previous call time. The cumulative timeout determination unit is used to determine the current preset timeout count as the cumulative timeout count when the end time corresponding to the first preset time period is reached.
[0077] In an optional embodiment, the diagnostic data acquisition module 620 includes: The previous sequence number identifier determination unit is used to respond to the first packet loss diagnosis interface call request of the target data processing module to the preset packet loss diagnosis interface based on the corresponding module identifier, and to use the first sequence number identifier as the previous sequence number identifier. The previous sequence number identifier is the sequence number identifier corresponding to the original data previously received by the target data processing module. The preset packet loss count update unit is used to respond to the non-first packet loss diagnosis interface call request of the target data processing module to the preset packet loss diagnosis interface based on the corresponding module identifier. If the previous sequence number identifier and the current sequence number identifier are not consecutive, it determines that the data received by the target data processing module has been lost, and updates the preset packet loss count. The preset packet loss count is initially zero. The previous sequence number identifier update unit is used to update the current sequence number identifier to the previous sequence number identifier; The second repeating unit is used to repeatedly respond to the non-first packet loss diagnosis interface call request of the target data processing module to the preset packet loss diagnosis interface based on the corresponding module identifier. When the previous sequence number identifier and the current sequence number identifier are not continuous, it determines that the data received by the target data processing module has been lost, and updates the preset packet loss count to the step of updating the current sequence number identifier to the previous sequence number identifier. The cumulative packet loss count determination unit is used to determine the current preset packet loss count as the cumulative packet loss count when the end time corresponding to the second preset time period is reached.
[0078] In an optional embodiment, the diagnostic data acquisition module 620 includes: The preset reception count update unit is used to update the preset reception count in response to the second call request from the target data processing module to the preset reception count statistics interface based on the corresponding module identifier. The preset reception count is initially zero. The third repeating unit is used to repeatedly respond to the second call request from the target data processing module to the preset reception count statistics interface based on the corresponding module identifier, and update the preset reception count. The cumulative reception count determination unit is used to determine the current preset reception count as the cumulative reception count when the end time corresponding to the third preset time period is reached.
[0079] In an optional embodiment, the diagnostic data acquisition module 620 includes: The data processing and analysis data determination unit is used to respond to the second call request from the target data processing module to the preset delay statistics interface based on the corresponding module identifier within the fourth preset time period, and to determine the data processing and analysis data based on multiple data processing times within the fourth preset time period.
[0080] In an optional embodiment, the fault diagnosis result determination module 630 includes: The fault diagnosis result determination unit is used to perform fault analysis on the target data processing module and corresponding sensors based on the correlation analysis of the cumulative timeout count, cumulative packet loss count, cumulative reception count, and data processing analysis data, and to determine the fault diagnosis result.
[0081] In an optional embodiment, the above-described apparatus further includes: The operation indication information sending module is used to send operation indication information of the preset diagnostic module to the preset monitoring system based on the second preset sending frequency, so that the preset monitoring system can determine the operation status of the preset diagnostic module. The operation indication information is used to indicate the operation status of the preset diagnostic module. The preset diagnostic module update module is used to update the preset backup diagnostic module to the preset diagnostic module when the operation indication information indicates that the preset diagnostic module is malfunctioning, so as to continue to perform fault analysis on the target data processing module and the corresponding sensor.
[0082] Figure 7 This is a block diagram illustrating an electronic device for vehicle fault diagnosis according to an exemplary embodiment. The electronic device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown, the electronic device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a vehicle fault diagnosis method. The display screen can be a liquid crystal display (LCD) or an e-ink display. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.
[0083] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present disclosure and does not constitute a limitation on the electronic device to which the present disclosure is applied. A specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0084] In an exemplary embodiment, an electronic device is also provided, including: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the vehicle fault diagnosis method as described in the embodiments of this disclosure.
[0085] In an exemplary embodiment, a computer-readable storage medium is also provided, wherein when the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the vehicle fault diagnosis method of the present disclosure embodiments.
[0086] In an exemplary embodiment, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform the vehicle fault diagnosis method of the present disclosure embodiments.
[0087] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.
[0088] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.
[0089] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.
Claims
1. A vehicle fault diagnosis method, characterized in that, The method includes: In response to the first call request from the data processing modules corresponding to the multiple sensors in the target vehicle to the preset general diagnostic interface in the preset diagnostic module, a module identifier corresponding to the data processing module corresponding to the multiple sensors is generated, and the module identifier is sent to the corresponding data processing module; In response to a second call request from the target data processing module to any one of the at least one preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier, diagnostic data is obtained. The at least one preset dedicated diagnostic interface corresponds one-to-one with at least one preset dedicated diagnostic function. The target data processing module triggers the call request at different times for different preset dedicated diagnostic interfaces. The target data processing module is any one of the data processing modules corresponding to the plurality of sensors. The diagnostic data is data that can reflect the operating status of the target data processing module and / or the sensor corresponding to the target data processing module. Based on the diagnostic data, fault analysis is performed on the target data processing module and the corresponding sensor to determine the fault diagnosis result.
2. The method according to claim 1, characterized in that, The at least one preset dedicated diagnostic interface includes a preset timeout diagnostic interface. When the second call request is a call request from the target data processing module to the preset timeout diagnostic interface, the second call request is triggered after the target data processing module receives the raw data. The raw data is the data sent by the corresponding sensor to the target data processing module. The second call request includes a first timeout diagnostic interface call request and a non-first timeout diagnostic interface call request. The diagnostic data includes the cumulative number of timeouts in the target data processing module receiving the corresponding raw data within a first preset time period. The diagnostic data obtained in response to the target data processing module's second call request to any one of the preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier includes: In response to the target data processing module's first timeout diagnosis interface call request to the preset timeout diagnosis interface based on the corresponding module identifier, the first call time corresponding to the first timeout diagnosis interface call request is obtained, and the first call time is used as the previous call time, where the previous call time is the time when the target data processing module last received the corresponding original data; In response to the non-first timeout diagnosis interface call request of the target data processing module to the preset timeout diagnosis interface based on the corresponding module identifier, the current call time corresponding to the non-first timeout diagnosis interface call request is obtained, and the current call time is the time when the target data processing module receives the corresponding original data this time; If the difference between the time interval of the current call time and the time interval of the previous call time and the first preset transmission frequency is greater than a preset threshold, it is determined that the target data processing module has timed out of receiving data this time, and the preset timeout number is updated; the first preset transmission frequency is the time frequency at which the corresponding sensor sends the corresponding raw data to the target data processing module, and the preset timeout number is initially zero; Update the current call time to the previous call time; Repeat the steps from the non-first timeout diagnostic interface call request of the target data processing module based on the corresponding module identifier to the step of updating the current call time to the previous call time; If the end time corresponding to the first preset time period is reached, the current preset timeout number is taken as the cumulative timeout number.
3. The method according to claim 1, characterized in that, The at least one preset dedicated diagnostic interface includes a preset packet loss diagnostic interface. When the second call request is a call request from the target data processing module to the preset packet loss diagnostic interface, the second call request is triggered after the target data processing module receives the raw data. The raw data is the data sent to the target data processing module by the corresponding sensor. The second call request includes a first packet loss diagnostic interface call request and a non-first packet loss diagnostic interface call request. The first packet loss diagnostic interface call request carries a first sequence number identifier, and the non-first packet loss diagnostic interface call request carries a current sequence number identifier. The current sequence number identifier is the sequence number identifier corresponding to the raw data received by the target data processing module this time. The diagnostic data includes the cumulative number of packet losses received by the target data processing module for the corresponding raw data within a second preset time period. The diagnostic data obtained in response to the target data processing module's second call request to any one of the preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier includes: In response to the target data processing module's first packet loss diagnosis interface call request to the preset packet loss diagnosis interface based on the corresponding module identifier, the first sequence number identifier is used as the previous sequence number identifier, where the previous sequence number identifier is the sequence number identifier corresponding to the original data previously received by the target data processing module. In response to the non-first packet loss diagnosis interface call request of the target data processing module to the preset packet loss diagnosis interface based on the corresponding module identifier, if the previous sequence number identifier and the current sequence number identifier are not consecutive, it is determined that the target data processing module has received data loss, and the preset packet loss count is updated. The preset packet loss count is initially zero. Update the current sequence number identifier to the previous sequence number identifier; Repeat the non-first packet loss diagnosis interface call request of the target data processing module to the preset packet loss diagnosis interface based on the corresponding module identifier. If the previous sequence number identifier and the current sequence number identifier are not consecutive, determine that the target data processing module has lost data, and update the preset packet loss count to the step of updating the current sequence number identifier to the previous sequence number identifier. If the end time corresponding to the second preset time period is reached, the current preset number of packet losses will be used as the cumulative number of packet losses.
4. The method according to claim 1, characterized in that, The at least one preset dedicated diagnostic interface includes a preset reception count statistics interface. When the second call request is a call request from the target data processing module to the preset reception count statistics interface, the second call request is triggered after the target data processing module receives the raw data. The diagnostic data includes the cumulative number of times the target data processing module receives the corresponding raw data within a third preset time period. The raw data is the data sent to the target data processing module by the corresponding sensor. The diagnostic data obtained in response to the target data processing module's second call request to any one of the preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier includes: In response to the second call request from the target data processing module to the preset reception count statistics interface based on the corresponding module identifier, the preset reception count is updated, which is initially zero. Repeat the step of updating the preset reception count in response to the second call request from the target data processing module to the preset reception count statistics interface based on the corresponding module identifier; If the end time corresponding to the third preset time period is reached, the current preset number of receptions will be used as the cumulative number of receptions.
5. The method according to claim 1, characterized in that, The at least one preset dedicated diagnostic interface includes a preset latency statistics interface. When the second call request is a call request from the target data processing module to the preset latency statistics interface, the second call request is triggered after the target data processing module sends target data. The target data is the data processed by the target data processing module after processing the original data. The original data is the data sent to the target data processing module by the corresponding sensor. The second call request carries the data processing time, which is the time taken for the target data processing module to process the corresponding original data to obtain the corresponding target data and then send the corresponding target data. The diagnostic data includes the data processing and analysis data corresponding to the target data processing module within a fourth preset time period. The diagnostic data obtained in response to the target data processing module's second call request to any one of the preset dedicated diagnostic interfaces in the preset diagnostic module based on the corresponding module identifier includes: In response to the second call request from the target data processing module to the preset delay statistics interface based on the corresponding module identifier within the fourth preset time period, the data processing and analysis data is determined based on multiple data processing times within the fourth preset time period.
6. The method according to claim 1, characterized in that, The diagnostic data includes the cumulative number of timeouts when the target data processing module receives the corresponding raw data within a first preset time period, the cumulative number of packet losses when the target data processing module receives the corresponding raw data within a second preset time period, the cumulative number of receptions when the target data processing module receives the corresponding raw data within a third preset time period, and the data processing and analysis data corresponding to the target data processing module within a fourth preset time period. Based on the diagnostic data, fault analysis is performed on the target data processing module and the corresponding sensor to determine the fault diagnosis result, including: Based on the correlation analysis of the cumulative timeout count, the cumulative packet loss count, the cumulative reception count, and the data processing and analysis data, a fault analysis is performed on the target data processing module and the corresponding sensor to determine the fault diagnosis result.
7. The method according to claim 1, characterized in that, The method further includes: Based on a second preset transmission frequency, the operation indication information of the preset diagnostic module is sent to a preset monitoring system so that the preset monitoring system can determine the operation status of the preset diagnostic module. The operation indication information is used to indicate the operation status of the preset diagnostic module. If the operation indication information indicates that the preset diagnostic module is malfunctioning, the preset diagnostic module will be updated to a preset backup diagnostic module to continue fault analysis of the target data processing module and the corresponding sensor.
8. A vehicle fault diagnosis device, characterized in that, include: The module identifier generation module is used to generate module identifiers corresponding to the data processing modules corresponding to the multiple sensors in the target vehicle in response to the first call request of the preset general diagnostic interface in the preset diagnostic module, and send the module identifiers to the corresponding data processing modules. The diagnostic data acquisition module is used to respond to a second call request from the target data processing module to any one of the at least one preset dedicated diagnostic interfaces in the preset diagnostic modules based on a corresponding module identifier, and to obtain diagnostic data. The at least one preset dedicated diagnostic interface corresponds one-to-one with at least one preset dedicated diagnostic function. The target data processing module triggers the call request at different times for different preset dedicated diagnostic interfaces. The target data processing module is any one of the data processing modules corresponding to the plurality of sensors. The diagnostic data is data that can reflect the operating status of the target data processing module and / or the sensor corresponding to the target data processing module. The fault diagnosis result determination module is used to perform fault analysis on the target data processing module and the corresponding sensor based on the diagnostic data, and determine the fault diagnosis result.
9. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the vehicle fault diagnosis method as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is able to perform the vehicle fault diagnosis method as described in any one of claims 1 to 7.