Diagnostic repair method, system, electronic device and storage medium for a vehicle

Abstract

The application provides a vehicle diagnosis repair method and system, an electronic device and a storage medium, applied to the field of vehicle remote control, the method comprises the following steps: in response to a vehicle failure, sending fault information to the cloud diagnosis unit through the vehicle end; based on the fault information, the cloud diagnosis unit performs remote fault diagnosis on the vehicle; sending the fault diagnosis result to the cloud diagnosis model, determining the software upgrade package corresponding to the fault diagnosis result, and sending the software upgrade package to the vehicle end through over-the-air technology; repairing the vehicle fault through the software upgrade package; and updating the software of the vehicle end to realize fault repair. Compared with offline repair by technicians, the method of the application realizes remote fault repair of the vehicle, improves the vehicle fault repair efficiency, and improves the convenience of users using the vehicle.

Description

Technical Field

[0001] This application relates to the field of vehicle fault diagnosis technology, and in particular to a vehicle diagnosis and repair method, system, electronic device and storage medium. Background Technology

[0002] Currently, when a vehicle malfunctions, specific diagnostic equipment is typically used for on-site diagnosis and troubleshooting. After identifying the faulty component, the user needs to take the vehicle to a designated repair shop for repair, which is inconvenient. Furthermore, due to the surge in the number of vehicles on the market, traditional troubleshooting methods cannot meet the future demand for vehicle fault diagnosis, resulting in low repair efficiency. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a vehicle diagnostic and repair method, system, electronic device and storage medium to solve the problem of low efficiency in existing vehicle fault repair.

[0004] The first aspect of this application provides a vehicle diagnostic and repair method, applied to a vehicle diagnostic and repair system, the system including a cloud diagnostic unit and a cloud diagnostic model, the method comprising:

[0005] In response to a vehicle malfunction, fault information is sent from the vehicle to the cloud diagnostic unit.

[0006] Based on the fault information, the vehicle is remotely diagnosed through the cloud diagnostic unit, and the fault diagnosis results are sent to the cloud diagnostic model.

[0007] The cloud diagnostic model determines the software upgrade package corresponding to the fault diagnosis result and sends the software upgrade package to the vehicle to repair the fault.

[0008] Optionally, the remote fault diagnosis of the vehicle through the cloud diagnostic unit includes:

[0009] The cloud diagnostic unit determines the configuration information corresponding to the fault information and sends the configuration information to the vehicle.

[0010] The current status information of the vehicle-side device corresponding to the fault information is determined by the vehicle-side device, the current status information is compared with the configuration information, and the fault diagnosis result is generated based on the comparison result.

[0011] Optionally, the system further includes a service unit; the method further includes:

[0012] The service unit sends an inquiry to the vehicle to ask whether the fault has been resolved.

[0013] In response to the service unit receiving feedback information corresponding to the query information, the feedback information is sent to the cloud diagnostic unit;

[0014] The cloud diagnostic unit sends the feedback information to the cloud diagnostic model to update the cloud diagnostic model based on the feedback information.

[0015] Optionally, the cloud diagnostic model includes a first event library; updating the cloud diagnostic model based on the feedback information includes:

[0016] The feedback information, the fault diagnosis results, and the software upgrade package corresponding to the fault diagnosis results are stored in the first event database;

[0017] The historical data in the first event database is corrected based on the feedback information, the fault diagnosis results, and the software upgrade package corresponding to the fault diagnosis results.

[0018] Optionally, the cloud diagnostic model further includes a second event library; the method further includes:

[0019] In response to the feedback information being valid feedback confirming that the fault has been eliminated, the valid feedback information, the fault diagnosis result corresponding to the valid feedback information, and the software upgrade package are stored in the second event database.

[0020] Optionally, the system further includes an early warning model, and the method further includes:

[0021] The second event database is synchronized to the early warning model so that the early warning model can be updated according to the second event database.

[0022] Optionally, the system further includes an early warning model, and the method further includes:

[0023] The warning model acquires the vehicle's status data in real time and determines whether the vehicle has a risk of failure based on the status data.

[0024] In response to the determination of a potential fault risk, a warning message is issued to the vehicle through the warning model.

[0025] A second aspect of this application also provides a vehicle diagnostic and repair system, the system comprising a cloud diagnostic unit and a cloud diagnostic model;

[0026] The cloud diagnostic unit is configured to receive fault information sent by the vehicle when a vehicle malfunctions, perform remote fault diagnosis on the vehicle based on the fault information, and send the fault diagnosis results to the cloud diagnostic model.

[0027] The cloud diagnostic model is configured to determine the software upgrade package corresponding to the fault diagnosis result and send the software upgrade package to the vehicle to repair the fault.

[0028] A third aspect of this application also provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in the first aspect.

[0029] A fourth aspect of this application also provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method as described in the first aspect.

[0030] As described above, the vehicle diagnostic and repair method, system, electronic device, and storage medium provided in this application include the following steps: In response to a vehicle malfunction, the method sends fault information from the vehicle to the cloud diagnostic unit; based on the fault information, the cloud diagnostic unit performs remote fault diagnosis on the vehicle to determine the cause of the malfunction in vehicle components, thereby achieving remote vehicle diagnosis and improving diagnostic efficiency. The method also involves sending the fault diagnosis results to the cloud diagnostic model, which automatically identifies and determines a fault repair plan, i.e., determines the software upgrade package corresponding to the fault diagnosis results, and sends the software upgrade package to the vehicle; the software upgrade package is then used to repair the vehicle malfunction, and the vehicle's software is updated to achieve the fault repair. Compared to offline repair by technicians, the method of this application enables remote vehicle fault repair, improving vehicle fault repair efficiency and enhancing user convenience. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a schematic flowchart of a vehicle diagnosis and repair method according to an embodiment of this application;

[0033] Figure 2 This is a flowchart of the diagnostic and repair system according to an embodiment of this application;

[0034] Figure 3 This is a schematic diagram of the vehicle diagnostic and repair system according to an embodiment of this application;

[0035] Figure 4This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0037] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0038] As described in the background section, vehicle technology is rapidly developing, with increasingly higher levels of intelligence and a growing number of electronic controllers in vehicles. This improves vehicle performance and comfort, but also increases complexity, leading to various malfunctions. In response, vehicle diagnostics are increasingly being implemented. Vehicle diagnostics determines the vehicle's technical condition and identifies faulty components and their causes without disassembling the vehicle. Once the cause of the malfunction is determined, if it's a software issue, it can be fixed by upgrading the vehicle's software; if it's a hardware issue, professional repair personnel can be consulted for repair. However, current fault repair methods, regardless of the cause, require professional repair personnel to perform on-site repairs, resulting in low efficiency and inconvenience for users. In view of this, this application proposes a vehicle diagnosis and repair method. When a vehicle malfunctions, the method performs remote fault diagnosis and sends a software upgrade package to the vehicle via Over-the-Air Technology (OTA) to repair the fault on the vehicle. This improves the efficiency of vehicle fault diagnosis and repair, and provides users with an efficient and convenient vehicle fault solution.

[0039] The embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0040] This application provides a vehicle diagnostic and repair method, applied to a vehicle diagnostic and repair system, and executable by the system's central controller. The system includes a cloud diagnostic unit and a cloud diagnostic model. (Refer to...) Figure 1 The method includes:

[0041] Step 102: In response to a vehicle malfunction, the fault information is sent to the cloud diagnostic unit via the vehicle terminal.

[0042] Specifically, in the vehicle diagnostic and repair system, the cloud diagnostic unit is responsible for remotely diagnosing vehicle faults, while the cloud diagnostic model is responsible for determining the corresponding fault repair plan based on the diagnostic results of the cloud diagnostic unit to repair the fault on the vehicle side. Both the cloud diagnostic unit and the cloud diagnostic model are deployed in the cloud. After a vehicle fault occurs, the vehicle controller sends the fault information to the vehicle communication module, which then sends the fault information to the cloud diagnostic unit. The fault information describes relevant information about the faulty vehicle components, such as the identification of the faulty components. Based on the fault information, the cloud diagnostic unit can determine which vehicle component is currently faulty and thus formulate a remote diagnostic strategy.

[0043] Furthermore, the system also includes a service unit. For example, the service unit can be the vehicle's after-sales system, providing after-sales service for the vehicle. When a vehicle malfunctions, the user reports the vehicle malfunction information to the service unit through the vehicle-side communication module. The service unit then distributes a fault task to the cloud diagnostic unit based on the vehicle malfunction information, triggering the cloud diagnostic unit to perform remote fault diagnosis on the vehicle.

[0044] Step 104: Based on the fault information, perform remote fault diagnosis on the vehicle through the cloud diagnostic unit, and send the fault diagnosis results to the cloud diagnostic model.

[0045] Specifically, after receiving fault information, the cloud diagnostic unit determines the corresponding remote diagnostic strategy based on the fault information and sends the remote diagnostic strategy to the vehicle. The vehicle controller then performs fault diagnosis on the faulty components according to the remote diagnostic strategy, generates fault diagnosis results, and sends these results back to the cloud diagnostic model to complete the vehicle fault diagnosis. The fault diagnosis results may include fault identifiers of the faulty components, such as fault codes. Based on the fault diagnosis results, the cause of the faulty component can be determined. This remote fault diagnosis process improves the efficiency of vehicle fault diagnosis, helps users determine the cause of vehicle faults, and saves time and diagnostic costs compared to manual fault diagnosis.

[0046] Step 106: Determine the software upgrade package corresponding to the fault diagnosis result through the cloud diagnostic model, and send the software upgrade package to the vehicle to repair the vehicle fault.

[0047] Specifically, after receiving the fault diagnosis result, the cloud diagnostic model searches its database for a fault repair solution that closely matches the diagnosis. If the solution is determined to be software-related, the model retrieves the corresponding software upgrade package and sends it to the vehicle via OTA (Over-The-Air) technology to remotely repair the vehicle fault. If the solution is hardware-related, the user is notified that in-person hardware repair is required.

[0048] It should be noted that when repairing vehicle software faults based on software upgrade packages, user privacy data may be involved. Therefore, a legality check is required before the fault repair process. This legality check can be performed by relevant organizations or departments. After passing the legality check, the cloud diagnostic model sends the software upgrade package to the vehicle via OTA technology, and the vehicle controller upgrades the vehicle software according to the upgrade package. This allows for remote fault repair of the vehicle, greatly improving the efficiency of vehicle fault repair, eliminating reliance on manual repair, and saving labor costs and user time.

[0049] Based on steps 102 to 106 above, the vehicle diagnosis and repair method provided in this embodiment includes, in response to a vehicle malfunction, sending fault information from the vehicle to the cloud diagnostic unit; based on the fault information, performing remote fault diagnosis on the vehicle through the cloud diagnostic unit to determine the cause of the vehicle component malfunction, thereby achieving remote vehicle diagnosis and improving diagnostic efficiency; sending the fault diagnosis result to the cloud diagnostic model, which automatically identifies and determines a fault repair plan, i.e., determines the software upgrade package corresponding to the fault diagnosis result, and sending the software upgrade package to the vehicle via over-the-air (OTA) download technology; and repairing the vehicle malfunction by updating the vehicle's software. Compared to offline repair by technicians, the method of this application achieves remote vehicle fault repair, improving vehicle fault repair efficiency and enhancing user convenience.

[0050] The method for remote fault diagnosis is described below through specific embodiments.

[0051] In some embodiments, the remote fault diagnosis of the vehicle via the cloud diagnostic unit includes the following steps:

[0052] The cloud diagnostic unit determines the configuration information corresponding to the fault information and sends the configuration information to the vehicle.

[0053] The current status information of the vehicle-side device corresponding to the fault information is determined by the vehicle-side device, the current status information is compared with the configuration information, and the fault diagnosis result is generated based on the comparison result.

[0054] Specifically, after receiving fault information, the cloud diagnostic unit identifies the faulty component based on the component identifier in the fault information, for example, identifying the faulty component as an airbag. Based on the standard component parameters related to the faulty component stored in the cloud, it determines the configuration information, which may include multiple configuration files. Then, the configuration information is sent to the vehicle. Upon receiving the configuration information, the vehicle determines the current status information of the vehicle-side device (i.e., the faulty component), which includes the current component parameters of the vehicle-side device. The current component parameters are compared with the standard component parameters; those that differ from the standard component parameters are designated as difference parameters, and all difference parameters form a comparison result. All difference parameters are analyzed, and the current fault cause is determined based on the correspondence between the difference parameters and the fault cause, generating a fault diagnosis result. The fault diagnosis result can be in the form of a fault diagnosis code. Using the method of this embodiment, remote fault diagnosis of vehicles can be performed via the cloud diagnostic unit, eliminating the need for offline manual diagnosis, providing convenience for users, and improving the efficiency of vehicle fault diagnosis compared to manual diagnosis.

[0055] After a vehicle completes remote fault repair, a follow-up visit is needed to verify the repair results and provide users with better diagnostic and repair services. Therefore, in some embodiments, the system further includes a service unit; the method further includes:

[0056] The service unit sends an inquiry to the vehicle to ask whether the fault has been resolved.

[0057] In response to the service unit receiving feedback information corresponding to the query information, the feedback information is sent to the cloud diagnostic unit;

[0058] The cloud diagnostic unit sends the feedback information to the cloud diagnostic model to update the cloud diagnostic model based on the feedback information.

[0059] Specifically, after remote fault repair is completed on the vehicle side, the service unit sends an inquiry to the vehicle side to inquire whether the fault has been resolved, in order to understand whether the fault repair was successful. The inquiry can be sent at preset time intervals. When the vehicle side begins fault repair, the service unit continuously sends inquiry messages to the vehicle side at preset time intervals until it receives feedback from the vehicle side. This allows for timely knowledge of the fault repair result and subsequent responses. For example, the preset time interval can be 30 seconds. The user sends feedback information to the service unit through the vehicle side communication module. The feedback information can include whether the fault repair was successful or unsuccessful. The service unit synchronizes the feedback information to the cloud diagnostic unit, which then synchronizes the feedback information to the cloud diagnostic model. The cloud diagnostic model can update or correct historical data in its database based on the feedback information, so as to determine a more suitable fault repair solution based on the fault diagnosis results, and thus determine a more suitable software upgrade package.

[0060] Furthermore, when the cloud diagnostic model is a machine learning model, a deep learning model, or a large artificial intelligence model, feedback information, corresponding fault diagnosis results, and software upgrade packages can be used as training data updated in real time to train the cloud diagnostic model, thereby continuously improving the matching accuracy of the cloud diagnostic model and providing users with more accurate fault repair solutions.

[0061] The method in this embodiment can update the cloud diagnostic model in real time through feedback information, continuously optimize the recognition accuracy of the cloud diagnostic model for fault diagnosis results, enrich the database of the cloud diagnostic model, provide users with more suitable fault repair solutions, and thus improve the success rate of fault repair.

[0062] In addition to the service unit proactively inquiring with the vehicle terminal whether the fault has been resolved in the aforementioned embodiments, the vehicle terminal can also proactively report the result of the fault repair to the service unit. For example, in some embodiments, the system further includes a service unit; the method also includes:

[0063] The vehicle sends feedback information after fault repair to the service unit, so that the service unit forwards the feedback information to the cloud diagnostic unit.

[0064] The cloud diagnostic unit sends the feedback information to the cloud diagnostic model to update the cloud diagnostic model based on the feedback information.

[0065] Specifically, once the fault is repaired, the vehicle immediately sends feedback information to the service unit. The user sends this feedback via the vehicle's communication module, and the feedback may indicate whether the fault repair was successful or unsuccessful. The service unit then synchronizes the feedback information to the cloud diagnostic unit, which in turn synchronizes it to the cloud diagnostic model. The cloud diagnostic model can update or correct historical data in its database based on the feedback information, enabling it to determine a more suitable fault repair plan and, consequently, a more appropriate software upgrade package based on the fault diagnosis results.

[0066] Compared to the aforementioned embodiments, the method in this embodiment avoids the service unit from continuously sending query information, thus saving communication resources. Simultaneously, it ensures that the service unit receives feedback information promptly and can forward it to the cloud diagnostic unit and cloud diagnostic model in a timely manner. The cloud diagnostic model is updated in real time using feedback information, continuously optimizing the model's accuracy in identifying fault diagnosis results, enriching the cloud diagnostic model's database, and providing users with more suitable fault repair solutions, thereby improving the success rate of fault repair. The method for updating the cloud diagnostic model is described below through specific embodiments.

[0067] In some embodiments, the cloud diagnostic model includes a first event library; updating the cloud diagnostic model based on the feedback information includes:

[0068] The feedback information, the fault diagnosis result, and the software upgrade package corresponding to the fault diagnosis result are stored in the first event database; the historical data in the first event database are corrected according to the feedback information, the fault diagnosis result, and the software upgrade package corresponding to the fault diagnosis result.

[0069] Specifically, after receiving a fault diagnosis result, the cloud diagnostic model determines a software upgrade package based on the result. Simultaneously, the fault diagnosis result and the software upgrade package are stored in a first event database, which records fault events. When feedback information is received, it is associated with the fault diagnosis result and the software upgrade package and stored as historical data. When new feedback information is received, the new feedback information, the corresponding fault diagnosis result, and the software upgrade package are compared with the historical data. If they differ, the historical data is corrected. For example, if the new fault diagnosis result and the new feedback information are the same as the historical data, but the software upgrade package is different, the software upgrade package in the historical data is replaced with the new one to correct the historical data. This method allows for the storage of real-time data and the correction of historical data based on the real-time data, ensuring real-time updates to the cloud diagnostic model and enabling it to continuously provide users with matching fault repair solutions.

[0070] In some embodiments, the cloud diagnostic model further includes a second event library; the method further includes:

[0071] In response to the feedback information being valid feedback confirming that the fault has been eliminated, the valid feedback information, the fault diagnosis result corresponding to the valid feedback information, and the software upgrade package are stored in the second event database.

[0072] Specifically, the cloud diagnostic model also includes a second event library, which records valid fault events, i.e., fault events that have been successfully repaired. Compared to the first event library, the second event library stores valid feedback information, corresponding fault diagnosis results, and software upgrade packages. Valid feedback information confirms that the fault has been resolved. Feedback information indicating that the fault has not been resolved after repair is stored in the first event library, not the second event library. In other words, the data stored in the second event library consists entirely of successfully repaired fault data. Storing successfully repaired fault data separately facilitates the cloud diagnostic model in finding more optimized software upgrade packages when determining software upgrade packages, thus providing users with better remote fault repair services.

[0073] Furthermore, when determining the software upgrade package using the cloud diagnostic model, the software upgrade package corresponding to the fault diagnosis result can be matched first in the second event database. If no matching software upgrade package is found in the second event database, matching can continue in the first event database, and the matched software upgrade package can be sent to the vehicle. Through the method of this embodiment, a corresponding event database can be constructed based on valid feedback information. When determining the software upgrade package, the search priority of the second event database is higher than that of the first event database, thus improving the search speed for the optimal fault repair solution.

[0074] In addition to remote fault diagnosis and repair of vehicles, this application can also provide fault warnings for vehicles, as described in the following embodiments.

[0075] In some embodiments, the system further includes an early warning model, and the method further includes:

[0076] The warning model acquires the vehicle's status data in real time and determines whether the vehicle has a risk of failure based on the status data.

[0077] In response to the determination of a potential fault risk, a warning message is issued to the vehicle through the warning model.

[0078] Specifically, the vehicle's diagnostic and repair system also includes a warning model. This model can provide fault warnings to the vehicle, issuing corresponding risk alerts when a fault risk exists. For example, the warning model can be a machine learning model, a deep learning model, etc.; this embodiment does not specifically limit the type of warning model. The warning model acquires real-time vehicle status data, including the status information of various components within the vehicle. The real-time status data is input into the warning model, which then outputs the fault risk type. The warning model can be a classification model. Different risk types are pre-assigned corresponding labels, such as 0 for no risk, 1 for airbag risk, and 2 for fuel system risk. If the warning model outputs a value of zero, it indicates that there is no fault risk in the current vehicle; if the warning model outputs a value other than zero, the fault risk of the relevant components is determined according to the label.

[0079] Furthermore, to conserve computing resources, vehicle status data can be acquired periodically when the vehicle is in good condition. For example, vehicle status data can be acquired every two hours. If a potential malfunction is detected, the frequency of acquiring vehicle status data is increased to ensure timely alerts to the user regarding driving safety.

[0080] Furthermore, fault risks can be categorized into different risk levels, such as Level 1, Level 2, and Level 3 risks. In addition to the specific fault risk type, the warning information can also include the risk level to indicate the urgency of vehicle maintenance for the user. A higher risk level indicates a greater risk. When the risk level in the warning information is Level 3, the user is advised to maintain the relevant vehicle components as soon as possible to ensure driving safety. Through the method of this embodiment, a warning model can provide early warnings of vehicle fault risks, prompting users to maintain their vehicles promptly, reducing the vehicle fault rate, and improving vehicle driving safety.

[0081] In some embodiments, the system further includes an early warning model, and the method further includes:

[0082] The second event database is synchronized to the early warning model so that the early warning model can be updated according to the second event database.

[0083] As described in the foregoing embodiments, the historical data in the second event database consists of data from successfully repaired faults tested by users, ensuring high reliability. Training the early warning model using this historical data can improve its accuracy. During training, fault diagnosis results are extracted from the second event database, and the corresponding vehicle status information is obtained. These results and vehicle status information are combined to form training data, which is then used to train the early warning model. The model learns the correlation between the fault diagnosis results in the training data and the status information of their corresponding vehicle-side devices. When the second event database is updated, the early warning model is also updated accordingly to ensure accuracy. When issuing warnings using the model, features of the status information are extracted and compared with the features of each fault diagnosis result. Fault diagnosis results with high similarity are used as predicted risk faults and sent to the vehicle-side device to achieve early warning. Users can perform vehicle maintenance based on the predicted risk fault alerts to prevent malfunctions. The method in this embodiment allows for real-time updates of the early warning model's parameters based on the second event database, continuously improving the model's accuracy and providing users with reliable early warning information to minimize and reduce the occurrence of faults. It should be noted that... (The sentence is incomplete and requires further context to be fully translated.) Figure 2 The embodiments of this application can also be further described in the following ways:

[0084] Figure 2 A flowchart of a diagnostic repair system according to an embodiment of this application is shown, including the following steps:

[0085] Step 1.0: The user reports vehicle fault information to the service unit via the vehicle terminal. When a vehicle fault occurs, the user sends the fault information to the vehicle communication module via the vehicle controller, and then the vehicle communication module sends the fault information to the service unit. For example, the service unit can be the vehicle's after-sales system, providing after-sales service for the vehicle.

[0086] Step 1.1: The service unit dispatches a fault diagnosis task to the cloud diagnostic unit based on the fault information;

[0087] After receiving the fault information, the service unit generates a fault diagnosis task and dispatches the fault diagnosis task to the cloud diagnosis unit to trigger the cloud diagnosis unit to perform remote fault diagnosis on the vehicle.

[0088] Step 2.0: The cloud diagnostic unit actively triggers fault diagnosis to perform remote fault diagnosis on the vehicle.

[0089] After receiving fault information, the cloud diagnostic unit determines a corresponding remote diagnostic strategy based on the fault information and sends the remote diagnostic strategy to the vehicle-side controller, enabling the vehicle-side controller to perform fault diagnosis on the faulty component according to the remote diagnostic strategy. Specifically, the remote diagnostic strategy can be configuration information. After receiving the fault information, the cloud diagnostic unit identifies the faulty component based on the component identifier in the fault information and determines the configuration information based on the standard component parameters related to the faulty component stored in the cloud. The configuration information can include multiple configuration files. Then, the configuration information is sent to the vehicle-side controller. After receiving the configuration information, the vehicle-side controller determines the current status information of the vehicle-side device (i.e., the faulty component), which includes the current component parameters of the vehicle-side device. The current component parameters are compared with the standard component parameters. Parameters that differ from the standard component parameters are designated as difference parameters, and all difference parameters form a comparison result. All difference parameters are analyzed, and the current fault cause is determined based on the correspondence between the difference parameters and the fault cause, generating a fault diagnosis result.

[0090] Step 2.1: After the vehicle-side completes the fault diagnosis, it sends the fault diagnosis results back to the cloud diagnostic unit;

[0091] The fault diagnosis results can include fault identifiers of the faulty components, such as fault codes. Based on the fault diagnosis results, the cause of the faulty component's failure can be determined. After determining the fault diagnosis results, they are transmitted back to the cloud diagnostic unit.

[0092] Step 2.2: The cloud diagnostic unit synchronizes the fault diagnosis results to the cloud diagnostic model;

[0093] The cloud diagnostic unit synchronizes the fault diagnosis results to the cloud diagnostic model, enabling the cloud diagnostic model to determine the corresponding fault solution based on the fault diagnosis results, thereby achieving remote fault repair for the vehicle.

[0094] Step 2.3: The cloud diagnostic model determines the solution corresponding to the fault based on the fault diagnosis results. When the fault is determined to be a software fault, the software upgrade package corresponding to the fault diagnosis results is determined.

[0095] After receiving the fault diagnosis result, the cloud diagnostic model searches its database for a fault repair solution that closely matches the diagnosis result. If the solution is determined to be a software-related solution, the corresponding software upgrade package is retrieved.

[0096] Step 2.4: Perform a legality check on the software upgrade;

[0097] When repairing vehicle-side software based on software upgrade packages, user privacy data may be involved. Therefore, a legality check is required before the repair can proceed. This legality check can be performed by relevant agencies or departments, and only after passing the legality check can subsequent remote repairs be carried out.

[0098] Step 2.5: After the legality check is passed, the software upgrade package is sent to the vehicle via OTA technology, and the vehicle performs the software upgrade.

[0099] The cloud diagnostic model sends the software upgrade package to the vehicle via OTA technology. The vehicle controller then upgrades the vehicle software based on the upgrade package, thereby repairing any faults in the vehicle software.

[0100] Step 2.6: The service unit sends an inquiry to the vehicle to ask whether the fault has been resolved;

[0101] After the remote fault repair is completed on the vehicle, the service unit sends an inquiry to the vehicle to ask whether the fault has been resolved, in order to know whether the fault repair was successful.

[0102] Step 2.7: The user sends feedback information corresponding to the query information to the service unit through the vehicle terminal;

[0103] Users send feedback information to the service unit through the vehicle-side communication module. The feedback information can include whether the fault repair was successful or unsuccessful. If the software repair is successful, the feedback information sent will be "Fault Repair Successful"; if the software repair is unsuccessful, the feedback information sent will be "Fault Repair Unsuccessful".

[0104] Step 2.8: The service unit synchronizes the feedback information to the cloud diagnostic unit to achieve information synchronization and consistency;

[0105] Step 2.9: The cloud diagnostic unit synchronizes the feedback information to the cloud diagnostic model. The cloud diagnostic model updates itself based on the feedback information and stores the fault events in the first event database and the second event database according to the type of feedback information. It also corrects and optimizes the historical data in the first event database.

[0106] The cloud diagnostic model can update or correct historical data in its own database based on feedback information. Simultaneously, fault diagnosis results and software upgrade packages are stored in a first event database, which records fault events. Upon receiving feedback information, the feedback information is associated with the fault diagnosis results and software upgrade packages and stored as historical data. Upon receiving new feedback information, the new feedback information, the corresponding fault diagnosis results, and the software upgrade packages are compared with the historical data; if they differ, the historical data is corrected. A second event database records valid fault events, i.e., fault events where faults have been successfully repaired. Compared to the first event database, the second event database stores valid feedback information, the corresponding fault diagnosis results, and the software upgrade packages. Storing successfully repaired data separately facilitates the cloud diagnostic model in finding more optimized software upgrade packages when determining software upgrade packages, thus providing users with better remote fault repair services. Step 2.10: Synchronize the second event database to the early warning model to update the early warning model;

[0107] When training the early warning model, fault diagnosis results are extracted from the second event database, and the corresponding vehicle status information is obtained. These fault diagnosis results and their corresponding vehicle status information are combined to form training data, which is then used to train the early warning model. The early warning model learns the correlation between the fault diagnosis results in the training data and the status information of their corresponding vehicle-side devices. When the second event database is updated, the early warning model is also updated accordingly to ensure the accuracy of the early warning.

[0108] Step 3.0: Provide real-time warnings to the vehicle using the early warning model.

[0109] When issuing warnings through the early warning model, the features of the status information are extracted and compared with the features of each fault diagnosis result. Fault diagnosis results with high similarity are used as predicted risk faults and sent to the vehicle to achieve the purpose of early warning.

[0110] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0111] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0112] Based on the same inventive concept, and corresponding to any of the above-described embodiments, this application also provides a vehicle diagnostic and repair system.

[0113] refer to Figure 3 The vehicle diagnostic and repair system includes: a cloud diagnostic unit 302 and a cloud diagnostic model 304;

[0114] The cloud diagnostic unit 302 is configured to receive fault information sent by the vehicle terminal when a vehicle malfunctions, and based on the fault information, perform remote fault diagnosis on the vehicle and send the fault diagnosis results to the cloud diagnostic model.

[0115] The cloud diagnostic model 304 is configured to determine the software upgrade package corresponding to the fault diagnosis result and send the software upgrade package to the vehicle to repair the vehicle fault.

[0116] In some embodiments, the cloud diagnostic unit 302 is further configured to determine configuration information corresponding to the fault information and send the configuration information to the vehicle terminal;

[0117] The current status information of the vehicle-side device corresponding to the fault information is determined by the vehicle-side device, the current status information is compared with the configuration information, and the fault diagnosis result is generated based on the comparison result.

[0118] In some embodiments, the system further includes a service unit 306, which is configured to send an inquiry to the vehicle terminal regarding whether the fault has been resolved; and in response to receiving feedback information corresponding to the inquiry information, to send the feedback information to the cloud diagnostic unit.

[0119] The cloud diagnostic unit 302 is further configured to send the feedback information to the cloud diagnostic model to update the cloud diagnostic model based on the feedback information.

[0120] In some embodiments, the cloud diagnostic model 304 includes a first event library; the cloud diagnostic model 304 is further configured to store the feedback information, the fault diagnosis result, and the software upgrade package corresponding to the fault diagnosis result in the first event library; and to correct the historical data in the first event library according to the feedback information, the fault diagnosis result, and the software upgrade package corresponding to the fault diagnosis result.

[0121] In some embodiments, the cloud diagnostic model 304 further includes a second event library; the cloud diagnostic model 304 is also configured to, in response to the feedback information being valid feedback information confirming that the fault has been eliminated, store the valid feedback information, the fault diagnosis result corresponding to the valid feedback information, and the software upgrade package in the second event library.

[0122] In some embodiments, the system further includes an early warning model 308; the cloud diagnostic model 304 is further configured to synchronize the second event database to the early warning model in order to update the early warning model according to the second event database.

[0123] In some embodiments, the warning model 308 is further configured to acquire the vehicle's status data in real time through the warning model, and determine whether the vehicle has a fault risk based on the status data; in response to determining that a fault risk exists, to issue a warning message to the vehicle through the warning model.

[0124] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing this application, the functions of each module can be implemented in one or more software and / or hardware.

[0125] The apparatus described above is used to implement the corresponding vehicle diagnosis and repair method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0126] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle diagnosis and repair method described in any of the above embodiments.

[0127] Figure 4This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0128] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0129] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0130] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0131] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0132] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0133] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0134] The electronic devices described above are used to implement the corresponding vehicle diagnosis and repair methods in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0135] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the vehicle diagnostic and repair method as described in any of the above embodiments.

[0136] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0137] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the vehicle diagnosis and repair method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0138] Based on the same concept, corresponding to any of the above embodiments, this application also provides a computer program product, including computer program instructions, which, when run on a computer, cause the computer to perform the method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0139] It is understood that before using the technical solutions of the various embodiments in this disclosure, users will be informed of the type, scope of use, and usage scenarios of the personal information involved in an appropriate manner, and user authorization will be obtained.

[0140] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to choose, based on the prompt message, whether to provide personal information to the software or hardware such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution.

[0141] As an optional but not limited implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose whether to "agree" or "disagree" to the electronic device providing personal information.

[0142] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0143] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0144] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0145] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0146] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.

Claims

1. A method for diagnosing and repairing a vehicle, characterized in that, A diagnostic and repair system for vehicles, the system comprising a cloud diagnostic unit and a cloud diagnostic model, the method comprising: In response to a vehicle malfunction, fault information is sent from the vehicle terminal to the cloud diagnostic unit; the fault information describes relevant information about the faulty vehicle components. Based on the fault information, remote fault diagnosis of the vehicle is performed through the cloud diagnostic unit, including: determining the configuration information corresponding to the fault information through the cloud diagnostic unit, and sending the configuration information to the vehicle terminal; The vehicle-side device determines the current status information of the vehicle-side equipment corresponding to the fault information, compares the current status information with the configuration information, generates a fault diagnosis result based on the comparison result, and sends the fault diagnosis result to the cloud diagnosis model; the form of the fault diagnosis result may be a fault diagnosis code. The cloud diagnostic model includes a first event library and a second event library. The first event library stores feedback information indicating that a fault has not been resolved, corresponding fault diagnosis results, and corresponding software upgrade packages. The feedback information is issued by the vehicle in response to an inquiry, which asks whether the fault has been resolved. The second event library stores valid feedback information, corresponding fault diagnosis results, and software upgrade packages. The valid feedback information is confirmation that the fault has been resolved. The cloud diagnostic model determines the software upgrade package corresponding to the fault diagnosis result, including: The software upgrade package corresponding to the fault diagnosis result is matched in the second event database. If no matching software upgrade package is found in the second event database, the software upgrade package corresponding to the fault diagnosis result is matched in the first event database and sent to the vehicle to repair the vehicle fault.

2. The method according to claim 1, characterized in that, The system further includes a service unit; the method further includes: The service unit sends an inquiry to the vehicle to ask whether the fault has been resolved. In response to the service unit receiving feedback information corresponding to the query information, the feedback information is sent to the cloud diagnostic unit; The cloud diagnostic unit sends the feedback information to the cloud diagnostic model to update the cloud diagnostic model based on the feedback information.

3. The method according to claim 2, characterized in that, The step of updating the cloud diagnostic model based on the feedback information includes: The feedback information, the fault diagnosis results, and the software upgrade package corresponding to the fault diagnosis results are stored in the first event database; The historical data in the first event database is corrected based on the feedback information, the fault diagnosis results, and the software upgrade package corresponding to the fault diagnosis results.

4. The method according to claim 3, characterized in that, The method further includes: In response to the feedback information being valid feedback confirming that the fault has been eliminated, the valid feedback information, the fault diagnosis result corresponding to the valid feedback information, and the software upgrade package are stored in the second event database.

5. The method according to claim 4, characterized in that, The system also includes an early warning model, and the method further includes: The second event database is synchronized to the early warning model so that the early warning model can be updated according to the second event database.

6. The method according to claim 1, characterized in that, The system also includes an early warning model, and the method further includes: The warning model acquires the vehicle's status data in real time and determines whether the vehicle has a risk of failure based on the status data. In response to the determination of a potential fault risk, a warning message is issued to the vehicle through the warning model.

7. A vehicle diagnostic and repair system, characterized in that, The system includes a cloud diagnostic unit and a cloud diagnostic model; The cloud diagnostic unit is configured to receive fault information sent by the vehicle terminal when a vehicle malfunctions, and to perform remote fault diagnosis on the vehicle based on the fault information, including: determining configuration information corresponding to the fault information through the cloud diagnostic unit, and sending the configuration information to the vehicle terminal; The vehicle-side device determines the current status information of the vehicle-side device corresponding to the fault information, compares the current status information with the configuration information, generates a fault diagnosis result based on the comparison result, and sends the fault diagnosis result to the cloud diagnosis model; the fault information is used to describe the relevant information of the faulty parts of the vehicle, and the form of the fault diagnosis result can be a fault diagnosis code; The cloud diagnostic model is configured to determine the software upgrade package corresponding to the fault diagnosis result, and send the software upgrade package to the vehicle via over-the-air download technology to repair the vehicle fault. The cloud diagnostic model includes a first event library and a second event library. The first event library stores feedback information indicating that a fault has not been resolved, corresponding fault diagnosis results, and corresponding software upgrade packages. The feedback information is issued by the vehicle in response to an inquiry, which asks whether the fault has been resolved. The second event library stores valid feedback information, corresponding fault diagnosis results, and software upgrade packages. The valid feedback information is confirmation that the fault has been resolved. Determining the software upgrade package corresponding to the fault diagnosis result includes: In the second event database, a software upgrade package corresponding to the fault diagnosis result is matched. If no corresponding software upgrade package is matched in the second event database, a software upgrade package corresponding to the fault diagnosis result is matched in the first event database.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 6.

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