A vehicle fault diagnosis system, method and vehicle terminal

Abstract

The application relates to the technical field of fault diagnosis, and discloses a vehicle fault diagnosis system, a vehicle fault diagnosis method and a vehicle terminal. The vehicle fault diagnosis system comprises a vehicle terminal and an edge node. The vehicle terminal is used for collecting current vehicle data of the vehicle terminal in response to being connected to the edge node, and sending the current vehicle data to the edge node. The edge node is arranged in a target area. If the target area has the vehicle terminal, the edge node is used for connecting the vehicle terminal, performing fault diagnosis on the received current vehicle data, and obtaining a diagnosis result. The system is used for realizing vehicle fault diagnosis, reducing resource consumption in the fault diagnosis process, reducing transmission time delay and congestion, improving the timeliness of data processing, and avoiding losses caused by data delay.

Description

Technical Field

[0001] This application relates to the field of fault diagnosis technology, specifically to a vehicle fault diagnosis system, method, and vehicle terminal. Background Technology

[0002] With the continuous advancement of vehicle technology, especially the deep integration of electronic control systems and computer technology, modern vehicles have become highly integrated and complex. While significantly improving vehicle performance, this has also greatly increased the complexity and challenge of fault diagnosis. At the same time, consumers are placing higher demands on the richness of vehicle functionality and safety assurance. To meet these evolving consumer needs, fault diagnosis technology must develop in a more scientific and systematic direction to achieve rapid and accurate location and elimination of vehicle faults, ensuring stable vehicle performance and driving safety.

[0003] Some vehicle malfunctions still require diagnosis based on the experience of repair personnel. This demands a high level of expertise from the technicians, involves lengthy testing times, and can lead to inconsistent diagnostic results due to differences in individual experience. While existing solutions collect vehicle terminal data and upload it to the cloud for verification, these methods suffer from large data volumes, long transmission links to the cloud, resulting in long transmission times and low timeliness. Furthermore, they fail to consider the stability and timeliness of wireless transmission, and significant delays can cause substantial losses. Clearly, a new vehicle fault diagnosis method is urgently needed to address at least one of these problems.

[0004] It should be noted that the above content only provides background information related to this application and does not necessarily constitute prior art. Summary of the Invention

[0005] In view of the shortcomings of the prior art described above, this application provides a vehicle fault diagnosis system, method and vehicle terminal to diagnose and predict vehicle faults, reduce transmission delay and congestion in the fault diagnosis process, improve the timeliness of data processing and avoid losses caused by large delays.

[0006] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0007] According to one aspect of the embodiments of this application, a vehicle fault diagnosis system is provided, the vehicle fault diagnosis system including a vehicle terminal and an edge node; the vehicle terminal is configured to collect current vehicle data in response to connecting to the edge node, and send the current vehicle data to the edge node; the edge node is located in a target area, and the edge node is configured to connect to the vehicle terminal if a vehicle terminal exists in the target area, and perform fault diagnosis on the received current vehicle data to obtain a diagnosis result.

[0008] In one embodiment of this application, based on the foregoing scheme, the vehicle fault diagnosis system further includes a server, which is connected to the edge node. The server is used for at least one of the following: acquiring multiple historical vehicle data and fault results corresponding to each historical vehicle data; using each historical vehicle data as a vehicle data sample and labeling the vehicle data sample according to the fault results to obtain result sample labels corresponding to each vehicle data sample; training a model on the vehicle data samples with result sample labels to obtain a fault diagnosis model; receiving multiple sample vehicle data and fault data corresponding to each sample vehicle data uploaded by the edge node, using the sample vehicle data as optimized data samples and labeling the optimized data samples according to the fault data to obtain fault sample labels corresponding to each optimized data sample; optimizing the model on the optimized data samples with fault sample labels to send the optimized fault diagnosis model to the edge node according to a preset period; receiving current vehicle data uploaded by the edge node and generating visualization parameters based on the current vehicle data to visualize vehicle faults.

[0009] In one embodiment of this application, based on the foregoing scheme, the edge node is further configured to: if the edge node is connected to multiple vehicle terminals, determine the vehicle terminal corresponding to any diagnostic result as the target terminal; determine the fault importance corresponding to the diagnostic result based on the matching result between the diagnostic result and the preset result; if the fault importance includes important faults, send a prompt message to the vehicle terminals in the target area, the prompt message being generated based on the diagnostic result; if the fault importance includes ordinary faults, send the prompt message to the target terminal.

[0010] In one embodiment of this application, based on the foregoing scheme, the edge node sends the diagnostic result to the vehicle terminal in at least one of the following ways: if the fault importance level includes a critical fault, the edge node sends the diagnostic result to the vehicle terminal; if the fault importance level includes a common fault, the edge node sends the diagnostic result to the server, wherein the server is used to forward the diagnostic result to the vehicle terminal.

[0011] In one embodiment of this application, based on the foregoing scheme, if the number of edge nodes includes multiple nodes, the edge nodes connect to the vehicle terminal in the following manner: obtaining evaluation parameters, wherein the evaluation parameters include the relative distance between the vehicle terminal and each edge node, and the evaluation parameters also include the signal strength, computing power, and bandwidth of each edge node; calculating the comprehensive score of each edge node according to each evaluation parameter and its corresponding weight; and selecting the edge node with the highest comprehensive score as the target node, wherein the target node is used to connect to the vehicle terminal.

[0012] In one embodiment of this application, based on the foregoing scheme, the vehicle terminal connects to the edge node in at least one of the following ways: the vehicle terminal establishes a communication connection with the edge node through a PC5 interface; the vehicle terminal establishes a communication connection with the edge node through a Uu interface.

[0013] In one embodiment of this application, based on the aforementioned scheme, the edge node performs fault diagnosis on the received current vehicle data in any of the following ways to obtain a diagnosis result: performing fault diagnosis on the vehicle terminal based on the current vehicle data using a preset fault diagnosis model to obtain a diagnosis result, wherein the fault diagnosis model is obtained by training a model using vehicle data samples with result sample labels; and determining the diagnosis result based on the matching result between the current vehicle data and the preset vehicle data.

[0014] According to one aspect of the embodiments of this application, a vehicle fault diagnosis method is provided, applied to an edge node, the edge node being set in a target area, the vehicle fault diagnosis method comprising: acquiring current vehicle data of a vehicle terminal, wherein the vehicle terminal, in response to connecting to the edge node, collects the current vehicle data of the vehicle terminal and sends the current vehicle data to the edge node; if a vehicle terminal exists in the target area, the vehicle terminal is connected, and fault diagnosis is performed on the received current vehicle data to obtain a diagnosis result.

[0015] According to one aspect of the embodiments of this application, a vehicle fault diagnosis method is provided, applied to a vehicle terminal. The vehicle fault diagnosis method includes: in response to connecting to an edge node, collecting current vehicle data of the vehicle terminal and sending the current vehicle data to the edge node, wherein the edge node is set in a target area, and the edge node is used to connect to the vehicle terminal if there is a vehicle terminal in the target area, and to perform fault diagnosis on the received current vehicle data to obtain a diagnosis result.

[0016] According to one aspect of the embodiments of this application, a vehicle terminal is provided, the vehicle terminal comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the vehicle terminal enables the vehicle fault diagnosis method as described in the above embodiments.

[0017] The beneficial effects of this application are as follows: This application enables a vehicle terminal to connect to an edge node, collect current vehicle data, and send the current vehicle data to the edge node. If a vehicle terminal exists in the target area, the edge node located in the target area connects to the vehicle terminal and performs fault diagnosis on the received current vehicle data to obtain the diagnosis results. By using the edge node to perform fault diagnosis on the current vehicle data of the vehicle terminal, the amount of data processing on the server side is reduced, the consumption of computing resources and bandwidth resources is reduced, the transmission time is reduced, and the timeliness of data processing is improved, avoiding losses caused by large delays in data transmission and data processing. Furthermore, the edge node's fault diagnosis of the current vehicle data of the vehicle terminal includes diagnosing existing faults and predicting potential faults, which can improve security.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0020] Figure 1 This is a schematic diagram illustrating an exemplary system architecture as shown in an exemplary embodiment of this application;

[0021] Figure 2 This is a block diagram illustrating a vehicle fault diagnosis system as shown in an exemplary embodiment of this application;

[0022] Figure 3 This is a block diagram illustrating a vehicle fault diagnosis system, as shown in another exemplary embodiment of this application;

[0023] Figure 4 This is a schematic diagram illustrating data exchange of a vehicle fault diagnosis system, as shown in an exemplary embodiment of this application.

[0024] Figure 5 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0025] The embodiments of this application will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be understood that the preferred embodiments are only for illustrating this application and are not intended to limit the scope of protection of this application.

[0026] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. Therefore, the illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0027] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the present application. However, it will be apparent to those skilled in the art that embodiments of the present application may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the present application.

[0028] First, it's important to clarify that OTA (Over-The-Air) technology, also known as over-the-air, is a technology that enables remote management of mobile terminal devices and software via the air interface of mobile communications. Simply put, OTA technology allows users to wirelessly download and install new software, updates, or configuration files to their devices without connecting them to a computer or specific service station. In the automotive industry, OTA technology is widely used in electric vehicles and intelligent connected vehicles to enable remote upgrades and repairs of vehicle software. Through OTA technology, automakers can push new software versions, feature updates, security patches, or performance optimizations to vehicles in real time, thereby continuously improving vehicle performance, safety, and user experience.

[0029] A CAN message sequence refers to a series of CAN messages transmitted on the CAN bus. These messages are sent and received according to certain rules and order to achieve communication and data exchange between devices. The composition and order of the CAN message sequence depend on the specific communication protocol and application scenario. In CAN communication, each message contains certain information, such as an identifier (ID), a data field, and a control field. These messages are broadcast on the bus, and all devices connected to the bus can receive them. However, only devices interested in messages with a specific ID will further process these messages.

[0030] A CAN frame sequence refers to the sequence of CAN frames, the basic unit that constitutes a CAN message. A CAN frame is the smallest data unit in CAN communication, containing complete communication information such as identifiers, data, and control information. The composition and format of the CAN frame sequence are defined by the CAN protocol, ensuring correct communication between different devices.

[0031] The PC5 interface is an important communication interface in V2X (Vehicle to Everything) technology, primarily used for short-range direct communication between vehicles, people, and road infrastructure. The PC5 interface is used for direct communication between terminal devices in mobile communication systems, especially in vehicle-to-everything (V2X) scenarios, where vehicles can directly transmit and coordinate information with each other and with roadside units (RSUs).

[0032] The Uu interface plays a crucial role in communication systems, especially in mobile communication networks such as WCDMA (Wideband Code Division Multiple Access) and LTE (Long Term Evolution). The Uu interface is the communication interface between user equipment (UE, such as mobile phones, data cards, etc.) and radio network base stations (such as Node B in WCDMA, eNodeB in LTE). The Uu interface is responsible for data transmission and signaling interaction between the user equipment and the radio network, including various functions such as user data transmission, access control, handover management, and radio resource management.

[0033] Figure 1 This is a schematic diagram illustrating an exemplary system architecture as shown in an exemplary embodiment of this application.

[0034] Reference Figure 1 As shown, the system architecture may include a data acquisition device 101 and a computer device 102. The computer device 102 may be at least one of a desktop graphics processing unit (GPU) computer, a GPU computing cluster, or a neural network computer. The data acquisition device 101 is used to collect current vehicle data from the vehicle terminal. In this embodiment, after acquiring the data, the data acquisition device 101 provides it to the computer device 102 for processing. Those skilled in the art can use the computer device 102 to perform fault diagnosis on the vehicle terminal based on the current vehicle data and obtain diagnostic results. Specifically, fault diagnosis can be performed on the vehicle terminal based on the current vehicle data using a preset fault diagnosis model. The fault diagnosis model is obtained through model training using vehicle data samples with result sample labels; alternatively, the diagnostic result can be determined based on the matching results between the current vehicle data and preset vehicle data. It should be noted that the data acquisition device 101 and computer device 102 provided in this embodiment are merely examples and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0035] It should be noted that the vehicle fault diagnosis method provided in this application embodiment is generally executed by computer device 102, and correspondingly, the vehicle fault diagnosis system is generally set in computer device 102.

[0036] Figure 2 This is a block diagram illustrating a vehicle fault diagnosis system as shown in an exemplary embodiment of this application. The system can be applied to... Figure 1 The implementation environment shown is specifically configured in computer device 102. This system can also be applied to other exemplary implementation environments and specifically configured in other devices; this embodiment does not limit the implementation environment to which the system is applicable.

[0037] In one embodiment of this application, such as Figure 2As shown, this exemplary vehicle fault diagnosis system includes a vehicle terminal 210 and an edge node 220. The vehicle terminal 210 is configured to, in response to connecting to the edge node 220, collect current vehicle data and send the current vehicle data to the edge node 220. The edge node 220 is located in a target area and is configured to, if the vehicle terminal 210 is present in the target area, connect to the vehicle terminal 210 and perform fault diagnosis on the received current vehicle data to obtain a diagnosis result.

[0038] In this embodiment, after the vehicle terminal 210 collects the current vehicle data, it performs preprocessing such as data cleaning on the current vehicle data, packages the preprocessed current vehicle data, and uploads the packaged current vehicle data to the edge node 220. If the current vehicle data includes CAN messages, the current vehicle data is cleaned to remove outliers and noise, thereby ensuring the accuracy of the data; the CAN messages are packaged, and the packaged data is uploaded to the edge node 220.

[0039] In this embodiment, the vehicle terminal 210 collects current vehicle data and preprocesses, stores, and transmits this data. The current vehicle data includes, but is not limited to, at least one of the following: vehicle-side CAN (Controller Area Network), LIN (Local Interconnect Network), and ETH (Ethernet) controller data (including diagnostic messages and general application messages). The controller data includes operating status data of key components such as the vehicle control unit (VCU), battery management system (BMS), and motor control unit (MCU), such as vehicle speed, state of charge (SOC), battery status, engine speed, gear position, current, voltage, power mode, and fault data, as well as functional interaction signals such as seat adjustment, air conditioning temperature adjustment, assisted driving activation, and charging port activation. These signal lists are set during development according to preset filtering rules and can be updated via OTA (Over-The-Air). Since current mainstream electronic and electrical architectures involve more than one type of vehicle communication, it is necessary to package and process multiple signals. Taking CAN messages as an example, the current vehicle data is first preprocessed, that is, outliers and noise in the data are cleaned to ensure data accuracy. Then, multiple collected CAN messages plus timestamps are packaged into a CAN message sequence. Multiple CAN message sequences plus sampling time points are further packaged into a complete message encapsulation format and compressed. The vehicle terminal 210 waits for the packaged current vehicle data to be uploaded to the edge node 220 according to a preset period.

[0040] In this embodiment, considering the utilization rate of the equipment and the signal coverage, the roadside edge node, i.e., edge node 220, can be deployed in densely trafficked scenarios such as intersections and roundabouts of urban main roads, fixed on the crossarm of traffic lights, and responsible for receiving current vehicle data sent by vehicle terminals 210, and analyzing, processing, and uploading the data according to application requirements. It should be noted that the edge node setting position in this embodiment is only an example, and this application does not limit it, nor should it impose any restrictions on the function and scope of use of the embodiments of this application.

[0041] In this embodiment, after receiving the packaged file uploaded by the vehicle terminal 210, the edge node 220 needs to unpack the data packet. Taking the battery fault diagnosis model as an example, the unpacked data is filtered according to a preset filtering principle to obtain information such as cell voltage, temperature, and SOC (State of Charge, remaining battery power) required by the model. When the fault diagnosis model detects an abnormal trend or predicts a certain type of fault through the current vehicle data, it reminds the vehicle terminal and after-sales service to take necessary measures, and if necessary, alerts all vehicle terminals within the edge node range. The edge node 220 can perform real-time vehicle diagnosis, enabling timely and rapid diagnosis of vehicle status, greatly reducing the latency caused by data transmission speed and bandwidth limitations, and significantly alleviating the data processing pressure on the cloud.

[0042] In one embodiment of this application, the vehicle fault diagnosis system further includes a server 230 connected to an edge node 220. The server 230 is used for at least one of the following: acquiring multiple historical vehicle data and fault results corresponding to each historical vehicle data; using each historical vehicle data as a vehicle data sample and labeling the vehicle data samples according to the fault results to obtain result sample labels corresponding to each vehicle data sample; training a model on the vehicle data samples with result sample labels to obtain a fault diagnosis model; receiving multiple sample vehicle data and fault data corresponding to each sample vehicle data uploaded by the edge node 220; using the sample vehicle data as optimized data samples and labeling the optimized data samples according to the fault data to obtain fault sample labels corresponding to each optimized data sample; optimizing the model on the optimized data samples with fault sample labels to send the optimized fault diagnosis model to the edge node 220 according to a preset period; and receiving current vehicle data uploaded by the edge node 220 and generating visualization parameters based on the current vehicle data to visualize the vehicle fault.

[0043] In this embodiment, the cloud server 230 utilizes vehicle system and subsystem specifications, component mechanism models, component fault diagnosis strategies, and a large amount of historical fault data to establish an original fault diagnosis model. The system and subsystem specifications include composition, boundaries, functional allocation, and performance requirements; component mechanisms include power battery charging / discharging models, aging models, and thermal effect models; component fault diagnosis strategies are generally defined in the early stages of component development, including diagnostic enabling conditions, fault establishment conditions, fault manifestations, and maintenance suggestions; the historical fault database is accumulated from fault manifestation samples collected from past projects. The cloud server node is responsible for receiving historical vehicle data and corresponding fault results periodically reported by the edge node 220. Deep learning is used to train the original fault diagnosis model based on a large amount of vehicle operation data to obtain the fault diagnosis model, which undergoes regular version iterations and releases, and is fully pushed to the edge nodes to ensure that the edge node model is the latest version. By using vehicle functional specifications, component mechanism models, component fault diagnosis strategies, and historical fault data to build a database and model, and by regularly training the fault diagnosis model through deep learning, the identification, prediction, and location of problems become more accurate and rapid, providing good guidance for vehicle maintenance.

[0044] In this embodiment, the cloud database of the server 230 is responsible for storing the "pre-fault - fault" data. That is, the cloud database (server-side database) stores the acquired historical vehicle data and the fault results corresponding to each historical vehicle data, providing data support for model training. Based on the current vehicle data, visualization parameters are generated to visualize vehicle faults. These visualization methods include, but are not limited to, static charts such as tables, bar charts, line charts, and pie charts; dynamic charts that change over time; and dynamic visualizations such as animations and videos. For example, abnormal data in the current vehicle data can be compared with standard data in the form of a bar chart. Another example is the animation of the fault occurrence process: the server 230 combines the cloud vehicle model with the operational data in the current vehicle data, which can be used for a visual review of the entire fault scenario from "before the fault - during the fault - after the fault," providing guidance for model optimization.

[0045] It should be noted that the current vehicle data and other user data obtained in the embodiments of this application are all obtained with the user's consent, or actively submitted after the user's relevant instructions, or inevitably uploaded by the user when using the corresponding application through the client, webpage, etc. In the technical solutions disclosed in this application, the collection, storage, use, processing, transmission, provision, disclosure, and application of user personal information all comply with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and they do not violate public order and good morals.

[0046] In one embodiment of this application, the edge node 220 is further configured to: if the edge node 220 is connected to multiple vehicle terminals, determine the vehicle terminal corresponding to any diagnostic result as the target terminal; determine the fault importance corresponding to the diagnostic result based on the matching result between the diagnostic result and the preset result; if the fault importance includes important faults, send a prompt message to the vehicle terminals in the target area, and the prompt message is generated based on the diagnostic result; if the fault importance includes ordinary faults, send a prompt message to the target terminal.

[0047] In this embodiment, edge node 220 diagnoses vehicle pre-faults using a fault diagnosis model, that is, predicts the faults that will occur in the vehicle, identifies potential vehicle risks in advance, issues fault alarms, and sends safety control suggestions and maintenance suggestions to the vehicle terminal (i.e., the user) for prompting. The prompt information can include one or more of the following: text prompts, voice prompts, or alert sounds. For example, prompts can be displayed on the user interface or broadcast via a voice device. The prompt information can include diagnostic results, such as "Vehicle power will be interrupted in 15 minutes; please pull over immediately." When the diagnostic results include important faults (such as vehicle power interruption, thermal runaway, etc.), edge node 220 issues warnings to vehicle terminals (i.e., adjacent edge nodes and coverage areas) within the target area, providing prompts via text, voice, etc., to reduce the occurrence of safety accidents.

[0048] In one embodiment of this application, the edge node 220 notifies the vehicle terminal 210 through at least one of the following methods: determining the fault importance corresponding to the diagnostic result based on the matching result between the diagnostic result and the preset result; if the fault importance includes a critical fault, the edge node 220 sends the diagnostic result to the vehicle terminal 210; if the fault importance includes a common fault, the edge node 220 sends the diagnostic result to the server 230, wherein the server 230 is used to forward the diagnostic result to the vehicle terminal 210. Sending diagnostic results indicating a critical fault directly to the vehicle terminal 210 through the edge node 220 reduces the latency of fault result transmission, improves timeliness, and delivers the diagnostic result to the vehicle terminal 210 faster. Sending diagnostic results indicating a common fault indirectly to the vehicle terminal 210 through the server 230 avoids the vehicle terminal being outside the range of the edge node due to excessive vehicle speed, thus preventing the vehicle from receiving the diagnostic result.

[0049] In one embodiment of this application, if the number of edge nodes 220 includes multiple edge nodes, the edge nodes 220 connect to the vehicle terminal 210 in the following manner: obtaining evaluation parameters, wherein the evaluation parameters include the relative distance between the vehicle terminal 210 and each edge node 220, and the evaluation parameters also include the signal strength, computing power and bandwidth of each edge node 220; calculating the comprehensive score of each edge node 220 according to each evaluation parameter and the corresponding weight; and taking the edge node 220 with the highest comprehensive score as the target node, wherein the target node is used to connect to the vehicle terminal 210.

[0050] In this embodiment, the comprehensive score of each edge node 220 is calculated based on each evaluation parameter and its corresponding weight. Specifically, the comprehensive score of each edge node 220 is calculated based on the relative distance and distance weight, signal strength and signal weight, computing power and computing weight, and bandwidth and bandwidth weight.

[0051] In one embodiment of this application, the vehicle terminal 210 connects to the edge node 220 in at least one of the following ways: the vehicle terminal 210 establishes a communication connection with the edge node 220 through the PC5 interface; the vehicle terminal 210 establishes a communication connection with the edge node 220 through the Uu interface.

[0052] In this embodiment, the roadside edge nodes and the vehicle-mounted terminal (i.e., the vehicle terminal) adopt a short-range, low-latency, high-capacity, and highly reliable PC5 interface, while a Uu interface redundancy design ensures stable and reliable communication. The PC5 interface used by the edge nodes and the vehicle-mounted terminal, with its low latency, high capacity, and high reliability, can meet the needs of receiving and processing massive amounts of vehicle operation data.

[0053] In one embodiment of this application, the edge node 220 performs fault diagnosis on the received current vehicle data in any of the following ways to obtain a diagnosis result: performs fault diagnosis on the vehicle terminal 210 based on the current vehicle data using a preset fault diagnosis model to obtain a diagnosis result, wherein the fault diagnosis model is obtained by training the model using vehicle data samples with result sample labels; and determines the diagnosis result based on the matching result between the current vehicle data and the preset vehicle data.

[0054] In this embodiment, current vehicle data can be input into the fault diagnosis model to perform fault diagnosis on the vehicle terminal 210, thereby improving the accuracy of fault diagnosis. This approach has a wide range of applications and diagnostic targets. Alternatively, the diagnostic result can be determined based on the matching result between the current vehicle data and preset vehicle data. For example, matching the current battery temperature with a preset battery temperature; if the current battery temperature is higher than the preset battery temperature, the diagnostic result is that the current battery temperature is too high.

[0055] This application uses a fault diagnosis model deployed on the edge node 220 to perform real-time diagnosis of the vehicle terminal 210 based on the current vehicle data reported by the vehicle terminal 210. By using edge computing, the need for vehicle data to be uploaded to the cloud is no longer strong, and the latency caused by data transmission and bandwidth limitations is greatly reduced, thus alleviating the pressure on the cloud server.

[0056] Figure 3 This is a block diagram illustrating a vehicle fault diagnosis system, as shown in another exemplary embodiment of this application. (Refer to...) Figure 3 As shown, in an exemplary embodiment, the vehicle fault diagnosis system includes a vehicle terminal 210, an edge node 220, and a server 230. The vehicle terminal includes, but is not limited to, power domain, chassis domain, body domain, and intelligent driving domain. It collects current vehicle data from these domains and uploads at least one of the CAN, LIN, and ETH controller data to the edge node via a PC5 interface. This completes the data collection at the edge node. The edge node processes the current vehicle data according to application requirements, including data analysis and filtering based on preset principles. The processed data is input into the fault diagnosis model to obtain diagnostic results. Based on the diagnostic results, the system provides fault warnings or handling suggestions to the vehicle terminal and sends the diagnostic results, warnings, and handling suggestions back to the vehicle terminal. The edge node also uploads the processed data to the cloud for storage in the cloud's diagnostic database. The cloud's database uses the received data to train a fault diagnosis model and sends the model back to the edge node. The cloud also provides after-sales service and data display based on the current vehicle data. The specific implementation methods have been described in detail in the foregoing embodiments, and will not be repeated here.

[0057] Figure 4 This is a schematic diagram illustrating data exchange of a vehicle fault diagnosis system according to an exemplary embodiment of this application. The vehicle fault diagnosis method can be executed by a computing processing device, which may be... Figure 1 The computer device 102 shown is illustrated. (Refer to...) Figure 4As shown, in an exemplary embodiment, the vehicle terminal collects and stores the current vehicle data, and sends the current vehicle data to the edge node 220. According to a first preset period, multiple stored historical vehicle data and their corresponding fault results are sent to the edge node 220. The edge node 220 receives and forwards the multiple historical vehicle data and their corresponding fault results to the server 230. The server 230 performs model training based on the received multiple historical vehicle data and their corresponding fault results to obtain a fault diagnosis model, and sends the fault diagnosis model to the edge node 220. The edge node 220 receives the fault diagnosis model. The edge node 220 inputs the current vehicle data into the fault diagnosis model to obtain a diagnosis result, thereby performing fault diagnosis on the vehicle terminal 210. In this process, the edge node 220 also uploads the acquired sample vehicle data and the corresponding fault data of each sample vehicle data to the server 230 according to the second preset period, so that the server 230 can optimize the fault diagnosis model based on the multiple sample vehicle data and the corresponding fault data of each sample vehicle data, and distribute the optimized fault diagnosis model to the edge node 220 according to the third preset period, so that the fault diagnosis of the fault diagnosis model of the edge node 220 is more accurate.

[0058] This application enables vehicle terminals to connect to edge nodes, collect current vehicle data, and send this data to the edge nodes. If a vehicle terminal exists in the target area, the edge node located in that area connects to the vehicle terminal and performs fault diagnosis on the received current vehicle data, obtaining the diagnostic results. By using edge nodes to perform fault diagnosis on the current vehicle data, the amount of data processing on the server side is reduced, as are the consumption of computing and bandwidth resources. This also shortens transmission time and improves the timeliness of data processing, avoiding losses caused by significant delays in data transmission and processing. Furthermore, edge node fault diagnosis of the current vehicle data includes diagnosing existing faults and predicting potential faults, allowing for advance warning of possible faults and providing time for prevention, thus reducing the occurrence of safety accidents and improving safety. It also enhances the stability and timeliness of data transmission. Moreover, this application is scalable; it can be further developed on top of the vehicle fault diagnosis system to facilitate "vehicle-to-vehicle," "vehicle-to-device," and "device-to-device" analysis and suggestions on driving behavior, and optimization of vehicle energy management strategies.

[0059] In one embodiment of this application, a vehicle fault diagnosis method is applied to an edge node 220, which is located in a target area. The vehicle fault diagnosis method includes: acquiring current vehicle data of a vehicle terminal 210, wherein the vehicle terminal 210, in response to connecting to the edge node 220, collects the current vehicle data and sends the current vehicle data to the edge node 220; if a vehicle terminal 210 exists in the target area, the vehicle terminal 210 is connected, and fault diagnosis is performed on the received current vehicle data to obtain a diagnosis result.

[0060] In one embodiment of this application, a vehicle fault diagnosis method is applied to a vehicle terminal 210. The vehicle fault diagnosis method includes: in response to connecting to an edge node 220, collecting current vehicle data of the vehicle terminal 210, and sending the current vehicle data to the edge node 220. The edge node 220 is set in a target area. If the target area contains a vehicle terminal 210, the edge node 220 connects to the vehicle terminal 210 and performs fault diagnosis on the received current vehicle data to obtain a diagnosis result.

[0061] It should be noted that the vehicle fault diagnosis method provided in the above embodiments and the vehicle fault diagnosis system provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the vehicle fault diagnosis method provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the system can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.

[0062] Embodiments of this application also provide an electronic device, including: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the electronic device to implement the vehicle fault diagnosis methods provided in the various embodiments described above. The electronic device includes a vehicle terminal.

[0063] Figure 5 A schematic diagram of a computer system suitable for implementing the embodiments of this application is shown. It should be noted that... Figure 5 The computer system 500 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0064] like Figure 5As shown, the computer system 500 includes a Central Processing Unit (CPU) 501, which can perform various appropriate actions and processes, such as executing the methods provided in the various embodiments described above, based on a program stored in Read-Only Memory (ROM) 502 or a program loaded from Storage Unit 508 into Random Access Memory (RAM) 503. The RAM 503 also stores various programs and data required for system operation. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An Input / Output (I / O) interface 505 is also connected to the bus 504.

[0065] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. Removable media 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 510 as needed so that computer programs read from them can be installed into storage section 508 as needed.

[0066] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs various functions defined in the system of this application.

[0067] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0068] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0069] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0070] Another aspect of this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a computer's processor, causes the computer to perform the vehicle fault diagnosis method provided in the various embodiments described above. This computer-readable storage medium may be included in the electronic device described in the above embodiments, or it may exist independently and not assembled into the electronic device.

[0071] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0072] Another aspect of this application provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the vehicle fault diagnosis method provided in the various embodiments described above.

[0073] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0074] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0075] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A vehicle malfunction diagnosis system characterized by comprising: The vehicle fault diagnosis system comprises a vehicle terminal and an edge node; The vehicle terminal is configured to, in response to being connected to the edge node, collect current vehicle data of the vehicle terminal and send the current vehicle data to the edge node; The edge node is arranged in a target area, and is configured to, if there is a vehicle terminal in the target area, connect the vehicle terminal and perform fault diagnosis on the received current vehicle data to obtain a diagnosis result; If the number of edge nodes comprises a plurality of edge nodes, the edge nodes are connected to the vehicle terminal by the following method: An evaluation parameter is obtained, wherein the evaluation parameter comprises a relative distance between the vehicle terminal and each edge node, and the evaluation parameter further comprises a signal strength, a computing capability and a bandwidth of each edge node; A comprehensive score of each edge node is calculated according to each evaluation parameter and a corresponding weight; The edge node with the highest comprehensive score is taken as a target node, wherein the target node is configured to connect the vehicle terminal.

2. The vehicle malfunction diagnosis system according to claim 1, characterized by The vehicle fault diagnosis system further comprises a server end connected to the edge node, and the server end is configured to at least one of the following: A plurality of historical vehicle data and a fault result corresponding to each historical vehicle data are obtained; each historical vehicle data is taken as a vehicle data sample, and the vehicle data sample is labeled according to the fault result to obtain a result sample label corresponding to each vehicle data sample; a vehicle data sample with a result sample label is subjected to model training to obtain a fault diagnosis model; A plurality of sample vehicle data uploaded by the edge node and a fault data corresponding to each sample vehicle data are received, each sample vehicle data is taken as an optimization data sample, and the optimization data sample is labeled according to the fault data to obtain a fault sample label corresponding to each optimization data sample; an optimization data sample with a fault sample label is subjected to model optimization, and an optimized fault diagnosis model is sent to the edge node according to a preset period; Current vehicle data uploaded by the edge node is received, and a visual parameter is generated according to the current vehicle data to visually display a vehicle fault.

3. The vehicle malfunction diagnosis system according to claim 1, characterized by The edge node is further configured to: If the edge node is connected to a plurality of vehicle terminals, a vehicle terminal corresponding to any diagnosis result is determined as a target terminal; A fault importance degree corresponding to the diagnosis result is determined according to a matching result between the diagnosis result and a preset result; If the fault importance degree comprises an important fault, prompt information is sent to the vehicle terminal in the target area, and the prompt information is generated according to the diagnosis result; If the fault importance degree comprises an ordinary fault, the prompt information is sent to the target terminal.

4. The vehicle malfunction diagnosis system according to claim 3, characterized by The edge node sends the diagnosis result to the vehicle terminal by at least one of the following methods: If the fault importance degree comprises an important fault, the edge node sends the diagnosis result to the vehicle terminal; If the fault importance degree comprises a common fault, the edge node sends the diagnosis result to a server end, wherein the server end is configured to forward the diagnosis result to the vehicle terminal.

5. The vehicle malfunction diagnosis system according to any one of claims 1 to 4, characterized by, The vehicle terminal connects the edge node in at least one of the following ways: The vehicle terminal establishes a communication connection with the edge node through a PC5 interface. The vehicle terminal establishes a communication connection with the edge node through a Uu interface.

6. The vehicle malfunction diagnosis system according to any one of claims 1 to 4, characterized by, The edge node performs fault diagnosis on the received current vehicle data in any of the following ways to obtain a diagnosis result: A preset fault diagnosis model is used to perform fault diagnosis on the vehicle terminal according to the current vehicle data to obtain a diagnosis result, wherein the fault diagnosis model is obtained by model training using vehicle data samples with result sample labels. A diagnosis result is determined according to a matching result between the current vehicle data and preset vehicle data.

7. A vehicle failure diagnosis method characterized by comprising: The vehicle fault diagnosis method applied to an edge node, wherein the edge node is arranged in a target area, and the vehicle fault diagnosis method comprises: Obtaining current vehicle data of a vehicle terminal, wherein the vehicle terminal collects current vehicle data of the vehicle terminal and sends the current vehicle data to the edge node in response to being connected to the edge node; If the target area has a vehicle terminal, connecting the vehicle terminal and performing fault diagnosis on the received current vehicle data to obtain a diagnosis result; If the number of edge nodes comprises a plurality of edge nodes, the edge nodes connect the vehicle terminal in the following ways: Obtaining evaluation parameters, wherein the evaluation parameters comprise relative distances between the vehicle terminal and each edge node, and the evaluation parameters further comprise signal strengths, computing capabilities and bandwidths of each edge node; Calculating comprehensive scores of each edge node according to each evaluation parameter and a corresponding weight; Selecting an edge node with the highest comprehensive score as a target node, wherein the target node is used to connect the vehicle terminal.

8. A vehicle malfunction diagnosis method characterized by comprising: The vehicle fault diagnosis method applied to a vehicle terminal, wherein the vehicle fault diagnosis method comprises: Collecting current vehicle data of the vehicle terminal and sending the current vehicle data to an edge node in response to being connected to the edge node, wherein the edge node is arranged in a target area, and the edge node is configured to connect the vehicle terminal and perform fault diagnosis on the received current vehicle data to obtain a diagnosis result if the target area has a vehicle terminal; If the number of edge nodes comprises a plurality of edge nodes, the edge nodes connect the vehicle terminal in the following ways: Obtaining evaluation parameters, wherein the evaluation parameters comprise relative distances between the vehicle terminal and each edge node, and the evaluation parameters further comprise signal strengths, computing capabilities and bandwidths of each edge node; Calculating comprehensive scores of each edge node according to each evaluation parameter and a corresponding weight; Selecting an edge node with the highest comprehensive score as a target node, wherein the target node is used to connect the vehicle terminal.

9. A vehicle terminal, characterized by The vehicle terminal comprises: One or more processors; a storage device for storing one or more programs, which, when executed by the one or more processors, cause the vehicle terminal to implement the vehicle fault diagnosis method according to claim 8.

Images