CN113126589A - Vehicle-mounted self-diagnosis method, vehicle-mounted intelligent system and self-diagnosis system - Google Patents
Vehicle-mounted self-diagnosis method, vehicle-mounted intelligent system and self-diagnosis system Download PDFInfo
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Abstract
The invention discloses a vehicle-mounted self-diagnosis method, which comprises the following steps: the vehicle-mounted intelligent system sends a diagnosis instruction to the TBOX to control the TBOX to read the fault information of the nodes; the vehicle-mounted intelligent system receives fault information fed back by the TBOX; the vehicle-mounted intelligent system queries a diagnosis strategy according to the fault information; when the vehicle-mounted intelligent system inquires a diagnosis strategy, the vehicle-mounted intelligent system repairs the fault according to the diagnosis strategy; when the diagnosis strategy is not inquired by the vehicle-mounted intelligent system, the vehicle-mounted intelligent system sends the fault information to the cloud server to control the cloud server to inquire the diagnosis strategy and repair the fault according to the diagnosis strategy fed back by the cloud server. By adopting the invention, the faults can be effectively checked, analyzed and confirmed, a suggested solution is given through artificial intelligence big data, the faults are automatically tried to be repaired, the manpower and capital investment of the whole car factory after sale is reduced, and the failure rate of the whole car is reduced.
Description
Technical Field
The invention relates to the technical field of automobiles, in particular to a vehicle-mounted self-diagnosis method, a vehicle-mounted intelligent system and a vehicle-mounted self-diagnosis system.
Background
With the rapid development of electronics and computer technology, automotive electronics has also met with tremendous changes. The artificial intelligence technology is used as the leading edge technology of the time-to-day hot door, and is widely applied to the fields of entertainment, automobiles, medical treatment and other industries. In the automobile industry, artificial intelligence is mainly embodied in the aspects of entertainment and driving, and mature technical schemes which are really applied to the aspect of automobile self-diagnosis are few.
In the prior art, for detection and problem troubleshooting and maintenance of automobile part faults, after-sale or 4S shop professionals read a complete automobile fault code through a diagnostic instrument to preliminarily troubleshoot which node the problem is located, and then all functions of the node are verified through a diagnostic technology to determine the location of the problem, so that the workload of relevant after-sale workers is undoubtedly increased, and the labor cost of a complete automobile factory after sale is increased.
In addition, most of the currently grasped technical solutions adopt a diagnostic technique to analyze the fault so as to determine the location of the problem, but no repair suggestion is given about the problem or the repair is attempted by the system itself; meanwhile, the possible failure or service life of the vehicle-mounted part is pre-estimated, and the advantages of artificial intelligence cannot be really embodied.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a vehicle-mounted self-diagnosis method, a vehicle-mounted intelligent system and a vehicle-mounted self-diagnosis system, which can effectively carry out self-diagnosis on faults.
In order to solve the technical problem, the invention provides a vehicle-mounted self-diagnosis method, which comprises the following steps: the vehicle-mounted intelligent system sends a diagnosis instruction to the TBOX to control the TBOX to read the fault information of the nodes; the vehicle-mounted intelligent system receives fault information fed back by the TBOX; the vehicle-mounted intelligent system queries a diagnosis strategy according to the fault information; when the vehicle-mounted intelligent system inquires a diagnosis strategy, the vehicle-mounted intelligent system repairs the fault according to the diagnosis strategy; when the diagnosis strategy is not inquired by the vehicle-mounted intelligent system, the vehicle-mounted intelligent system sends the fault information to the cloud server to control the cloud server to inquire the diagnosis strategy and repair the fault according to the diagnosis strategy fed back by the cloud server.
As an improvement of the above scheme, the diagnosis strategy is used for recording a fault detection method, a fault confirmation method and a fault repair method; when the vehicle-mounted intelligent system repairs the fault according to the diagnosis strategy, the fault is detected according to the fault detection method, then the fault is confirmed according to the fault confirmation method and the detection result, and finally the fault is attempted to be repaired according to the fault repair method and the confirmation result.
As an improvement of the above aspect, the vehicle-mounted self-diagnosis method further includes: and the vehicle-mounted intelligent system and the cloud server respectively record relevant information in the fault repairing process.
As an improvement of the above aspect, the vehicle-mounted self-diagnosis method further includes: the vehicle-mounted intelligent system receives real-time state information of the nodes; when the real-time state information is matched with any relevant information in the fault repairing process recorded by a vehicle-mounted intelligent system or a cloud server, the vehicle-mounted intelligent system analyzes whether the node has a fault or not according to the real-time state information and the relevant information; when the vehicle-mounted intelligent system analyzes that the node has a fault, the vehicle-mounted intelligent system sends a diagnosis instruction to the TBOX to control the TBOX to read the fault information of the node.
As an improvement of the above aspect, the vehicle-mounted self-diagnosis method further includes: the vehicle-mounted intelligent system receives real-time parameter information of a vehicle, wherein the real-time parameter information comprises node use duration information or vehicle driving mileage information; and when the real-time parameter information reaches a preset value, the vehicle-mounted intelligent system predicts the nodes which reach the service life according to the real-time parameter information and sends prompt information to a user.
As an improvement of the above aspect, the vehicle-mounted self-diagnosis method further includes: and when the fault cannot be repaired, the vehicle-mounted intelligent system feeds back the repair result to the user.
As an improvement of the above aspect, the vehicle-mounted self-diagnosis method further includes: and when the cloud server does not inquire the diagnosis strategy, the cloud server feeds back the fault information to the user.
Correspondingly, the invention also provides a vehicle-mounted intelligent system which comprises a diagnosis instruction sending unit, a diagnosis instruction sending unit and a diagnosis instruction sending unit, wherein the diagnosis instruction sending unit is used for sending a diagnosis instruction to the TBOX so as to control the fault information of the TBOX reading node; a fault information receiving unit, configured to receive fault information fed back by the TBOX; the diagnosis strategy query unit is used for querying a diagnosis strategy according to the fault information; the fault information sending unit is used for sending the fault information to a cloud server so as to control the cloud server to inquire a diagnosis strategy; the diagnosis strategy execution unit is used for repairing the fault according to the diagnosis strategy;
as an improvement of the scheme, the vehicle-mounted intelligent system also comprises a fault recording unit, a fault recovery unit and a fault recovery unit, wherein the fault recording unit is used for recording relevant information in the fault recovery process; the state information receiving unit is used for receiving the real-time state information of the nodes; the fault analysis unit is used for analyzing whether the node has a fault according to the real-time state information and the related information when the real-time state information is matched with any related information in the fault repair process recorded by the vehicle-mounted intelligent system or the cloud server; and the diagnosis instruction driving unit is used for driving the diagnosis instruction sending unit when the vehicle-mounted intelligent system analyzes that the node has a fault.
As an improvement of the scheme, the vehicle-mounted intelligent system also comprises a parameter information receiving unit, a parameter information processing unit and a parameter information processing unit, wherein the parameter information receiving unit is used for receiving real-time parameter information of the vehicle, and the real-time parameter information comprises node use duration information or vehicle driving mileage information; and the service life analysis unit is used for predicting the nodes which reach the service life according to the real-time parameter information when the real-time parameter information reaches a preset value, and sending prompt information to a user.
Correspondingly, the invention also provides a vehicle-mounted self-diagnosis system, which comprises: the vehicle-mounted intelligent system; TBOX, is used for reading the trouble information according to the diagnostic command; and the cloud server is used for inquiring the diagnosis strategy according to the fault information.
The implementation of the invention has the following beneficial effects:
the vehicle-mounted intelligent system, the TBOX and the cloud server are combined, the fault information is obtained through the vehicle-mounted intelligent system and the TBOX, and the cloud server extracts the diagnosis strategy to enable the intelligent system to repair the fault. Therefore, the invention can effectively carry out troubleshooting, analysis and confirmation on the faults through the self-diagnosis mode of the automobile parts, and provides a suggested solution through artificial intelligence big data, and autonomously tries to repair the faults, thereby reducing the manpower and capital investment of the whole automobile factory after sale and reducing the failure rate of the whole automobile.
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Fig. 1 is a flowchart of a first embodiment of an on-vehicle self-diagnosis method of the invention;
fig. 2 is a flowchart of a second embodiment of the on-vehicle self-diagnosis method of the invention;
FIG. 3 is a schematic structural view of the on-vehicle self-diagnosis system of the present invention;
FIG. 4 is a schematic structural diagram of an on-vehicle intelligent system in the on-vehicle self-diagnosis system of the present invention;
fig. 5 is another structural schematic diagram of the on-vehicle intelligent system in the on-vehicle self-diagnosis system of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 shows a flowchart of a first embodiment of the on-vehicle self-diagnosis method of the invention, which includes:
s101, the vehicle-mounted intelligent system sends a diagnosis instruction to the TBOX to control the fault information of the TBOX reading node.
It should be noted that the onboard intelligence system may actively or passively send diagnostic instructions to TBOX. For example, the active mode is: when the main vehicle-mounted intelligent system detects that the battery power is too low, a diagnosis instruction can be actively sent to the TBOX; as another example, the passive mode is: when the user finds that the part is abnormal, the user can send a request instruction for checking the fault to the intelligent system in a voice mode or a key mode, then the intelligent system converts a voice signal into a digital signal or converts a key signal into the digital signal through the voice recognition system, and then a diagnosis instruction is generated according to the digital signal.
In the invention, the information transmission between the vehicle-mounted intelligent system and each node (namely each part of the whole vehicle) is realized through TBOX. After the vehicle-mounted intelligent system generates a diagnosis command, the vehicle-mounted intelligent system sends the diagnosis command to the TBOX through a communication protocol between the vehicle-mounted intelligent system and the TBOX, and therefore the TBOX is controlled to read fault information. The fault information comprises a fault vehicle type, a fault node and a fault code.
For example, TBOX may read and send currently existing fault information to the onboard intelligence system via diagnostic instructions (e.g., 0x19 service).
And S102, receiving the fault information fed back by the TBOX by the vehicle-mounted intelligent system.
S103, the vehicle-mounted intelligent system inquires a diagnosis strategy according to the fault information.
And S104, when the vehicle-mounted intelligent system inquires the diagnosis strategy, the vehicle-mounted intelligent system repairs the fault according to the diagnosis strategy.
And S105, when the diagnosis strategy is not inquired by the vehicle-mounted intelligent system, the vehicle-mounted intelligent system sends the fault information to the cloud server to control the cloud server to inquire the diagnosis strategy, and the fault is repaired according to the diagnosis strategy fed back by the cloud server.
It should be noted that the diagnosis strategy is used for recording a fault detection method, a fault confirmation method and a fault repair method; when the vehicle-mounted intelligent system repairs the fault according to the diagnosis strategy, the fault is detected according to the fault detection method, then the fault is confirmed according to the fault confirmation method and the detection result, and finally the fault is attempted to be repaired according to the fault repair method and the confirmation result.
For example, when a certain fault code is generated and cannot be repaired through some diagnostic instructions or reset operations, software needs to be updated, in this case, the vehicle-mounted intelligent system downloads the latest version of software of the node from the cloud server, and then updates the software after permission of a user, so that the problem of some fault codes is solved.
For another example, for a trial repair by a diagnostic policy but not a successful repair, the on-board intelligent system may need to further analyze whether the failure is caused by a hardware failure of a node. For example, when a fault code that the entire vehicle loses communication with a certain node occurs, the situation may be a software fault of some nodes or a hardware fault of the node. For such conditions, after software problems are eliminated, the hardware needs to be checked again.
Therefore, the diagnosis strategy can be quickly retrieved and the fault can be tentatively repaired through the large data information accumulated by the vehicle-mounted intelligent system and the cloud server.
It should be noted that the cloud server is established and maintained by each large host factory, and for different vehicle models and different nodes, corresponding fault codes are established and diagnosis strategies are designed according to the fault codes.
For example, the cloud server database stores fault codes and corresponding diagnosis strategies of all nodes (e.g., the meter ICM, the reverse sensor RPA, the blind spot detection system BSD, etc.) of the vehicle type a26 and the vehicle type A3K. When a vehicle-mounted intelligent system acquires fault information of a whole vehicle through TBOX, the vehicle-mounted intelligent system firstly queries a self-stored diagnosis strategy, if a diagnosis strategy matched with the fault information is queried, the fault is repaired according to the diagnosis strategy, and if a diagnosis strategy matched with the fault information is not queried, the fault information is sent to a cloud server; after receiving the fault information, the cloud server can inquire the unique corresponding diagnosis strategy according to the fault vehicle type, the fault node and the fault code recorded in the fault information, send the diagnosis strategy to the corresponding vehicle-mounted intelligent system, and then repair the fault according to the diagnosis strategy by the vehicle-mounted intelligent system.
In addition, in the diagnosis process, the vehicle-mounted intelligent system may simultaneously acquire a plurality of diagnosis strategies sent by the cloud server, and the vehicle-mounted intelligent system needs to execute the diagnosis strategies after receiving the diagnosis strategies. The diagnosis strategy can be designed by technicians or generated by a vehicle-mounted intelligent system in a self-learning mode, and different diagnosis strategies can be adopted for different fault information.
For example, the a diagnostic strategy is: the method comprises the steps of sending a detection message to a fault node and analyzing whether the fault node feeds back the message or not, if the fault node does not send the feedback message, on one hand, judging whether the fault node is abnormal in communication due to too low voltage or caused by wire harness connection and the like by reading related states of the voltage of the fault node and the like, once the problem is confirmed, automatically trying to repair according to a corresponding repair strategy by the vehicle-mounted intelligent system, if the fault needs to be solved through updating software, downloading the latest software of the fault node to the local and transmitting the latest software to a TBOX (tunnel boring oxide oxygen sensor), then sending a diagnosis instruction to enter a Bootloader of the fault node through the TBOX, and updating the fault node so as to solve the problem.
For another example, if the reverse sensor does not work, the failure may be caused by software, and the failure can be repaired by updating the software.
If the rearview camera is shielded during backing, the fault is caused by the fact that the camera is blocked by certain things (sludge and the like), the vehicle-mounted intelligent system can inform a user of a solution through a host screen, the user can process the solution by himself and feed back a processing result; and prompting the user to a 4S shop to perform professional maintenance on the problem which cannot be solved.
Therefore, when the vehicle-mounted intelligent system receives the diagnosis strategy, it needs to analyze which messages are to be sent to detect and confirm the fault according to the diagnosis strategy, and determine the cause of the fault according to whether the response condition of each component to the diagnosis messages can be determined, or further confirm which messages are to be sent to try to repair according to the response message data.
Further, when the cloud server does not inquire the diagnosis strategy, the cloud server feeds back the fault information to the user; meanwhile, when the fault cannot be repaired, the vehicle-mounted intelligent system feeds back the repair result to the user.
Therefore, the vehicle-mounted intelligent system, the TBOX and the cloud server are combined, the self-diagnosis mode of the automobile parts is realized, the faults can be effectively checked, analyzed and confirmed, a suggested solution is given through artificial intelligent big data, the faults are automatically tried to be repaired, the manpower and fund investment of the whole automobile factory after sale is reduced, and the failure rate of the whole automobile is reduced.
Referring to fig. 2, fig. 2 shows a flowchart of a second embodiment of the on-vehicle self-diagnosis method of the invention, including:
s201, the vehicle-mounted intelligent system sends a diagnosis instruction to the TBOX to control the fault information of the TBOX reading node.
S202, the vehicle-mounted intelligent system receives fault information fed back by the TBOX.
S203, the vehicle-mounted intelligent system queries a diagnosis strategy according to the fault information.
S204, when the vehicle-mounted intelligent system inquires a diagnosis strategy, the vehicle-mounted intelligent system repairs the fault according to the diagnosis strategy.
S205, when the diagnosis strategy is not inquired by the vehicle-mounted intelligent system, the vehicle-mounted intelligent system sends the fault information to a cloud server to control the cloud server to inquire the diagnosis strategy, and the fault is repaired according to the diagnosis strategy fed back by the cloud server.
S206, the vehicle-mounted intelligent system and the cloud server respectively record relevant information in the fault repairing process
It should be noted that, for a fault that has been repaired once, the vehicle-mounted intelligent system and the cloud server may respectively record relevant information in the fault repair process, thereby implementing the filing of the fault.
And S207, receiving the real-time state information of the nodes by the vehicle-mounted intelligent system.
The real-time status information includes, but is not limited to, current information, voltage information, temperature information, and the like.
And S208, when the real-time state information is matched with any relevant information in the fault repairing process recorded by the vehicle-mounted intelligent system or the cloud server, the vehicle-mounted intelligent system analyzes whether the node has a fault according to the real-time state information and the relevant information.
S209, when the vehicle-mounted intelligent system analyzes that the node has a fault, returning to the step S201.
When the vehicle-mounted intelligent system finds that the real-time state information of some nodes is the same as the real-time state information when the node fails last time, the node may fail the same as the node last time. Therefore, the vehicle-mounted intelligent system needs to perform predictive analysis on the fault according to the abnormal real-time state information, so as to perform pre-judgment on the fault possibly occurring in the node.
Therefore, the invention can obtain the relevant parameters of each part in real time through the diagnosis technology, and realize the prejudgment and the processing of the fault.
Further, the vehicle-mounted self-diagnosis method of the invention further comprises: the vehicle-mounted intelligent system receives real-time parameter information of a vehicle; and when the real-time parameter information reaches a preset value, the vehicle-mounted intelligent system predicts the nodes which reach the service life according to the real-time parameter information and sends prompt information to a user. The real-time parameter information includes node use duration information or vehicle mileage information, but is not limited thereto.
For example, when the vehicle-mounted intelligent system finds that the vehicle mileage information reaches a preset value, the vehicle-mounted intelligent system can prompt a user to perform operations such as tire replacement or engine oil replacement. Therefore, the prediction of the life can be effectively realized by the invention.
The invention is further illustrated by the following specific examples:
the vehicle-mounted intelligent system control TBOX reads that the fault code of the meter ICM (the physical address ID of the meter ICM is 0x72B) in the a26 vehicle model is "0 xC12987 (the fault code is a communication fault code lost with the BCS node)" by the diagnostic instruction "0 x 190209". At the moment, the vehicle-mounted intelligent system acquires fault information 'A26 (fault vehicle type), 72B (fault node) and C12987 (fault code)' through TBOX, when the vehicle-mounted intelligent system does not inquire a diagnosis strategy locally, the fault information is sent to the cloud server through a 4G/5G communication technology, after the cloud server receives the fault information, the fault information is retrieved according to the fault vehicle type, the fault node and the fault code, and a corresponding diagnosis strategy '0 x72B.001:0x 280003' is returned; 0x7ab.100.001: 680003 [101.500 ═ 0x264.0[ … ] ].101[ … ] ", and finally, the vehicle-mounted intelligent system processes the fault according to the diagnosis strategy.
Diagnostic strategy "0 x72B.001:0x 280003; 0x7ab.100.001: 680003 [101.500 ═ 0x264.0[ … ] ].101[ … ] "is command data for controlling the vehicle-mounted intelligent system to execute relevant actions according to instructions, wherein" 0x72B "is an address; "001" is a send instruction code; "002" receives an instruction code; ".' is a command separator; "100" is a control condition, similar to if; "101" is the control condition turn, similar to else; "500" is a special instruction, referring to an address; "[ ]" is a control condition execution section.
The diagnosis strategy is analyzed by the vehicle-mounted intelligent system as follows: 0x 280003 is sent at 0x728 (the physical address of the meter ICM) and if 0x 680003 is sent at 0x7AB (the response address of the meter) (i.e. a positive response to a 0x28 service request), the instruction in "[ ]" is executed, i.e. if the ID 0x264 message is not on-line (where the data code 0x264.0 indicates that the message is not present and 0x264.1 indicates that the message is present), the instruction in the subsequent "[ ]" is executed until the cause of the fault is determined.
Therefore, the vehicle-mounted intelligent system and the cloud server can realize the functions of analyzing fault codes, detecting faults, predicting faults, confirming faults and repairing the faults through the diagnosis strategy. Accordingly, the function implementation is based on a huge database, and the database establishment is accumulated in practice at all, which is the foundation of the artificial vehicle-mounted intelligent system, namely based on big data, and related behaviors are realized through deep learning of a neural network.
Referring to fig. 3, fig. 3 shows a specific structure of the vehicle-mounted self-diagnosis system of the present invention, which includes a vehicle-mounted intelligent system 1, a TBOX2, and a cloud server 3; the vehicle-mounted intelligent system 1 is used as the brain of the whole system and is responsible for carrying out complex calculation and command processing, supporting wireless networking, uploading or downloading files, data records and the like; the TBOX2 is used as an interactive system of each node (each part of the whole vehicle), and can send and receive information through the TBOX 2; the cloud server 3 is established and maintained by each large host factory, and for different vehicle types and different nodes, corresponding fault codes are established and diagnosis strategies are designed according to the fault codes.
As shown in fig. 4, the in-vehicle intelligent system 1 includes:
a diagnostic instruction sending unit 11 for sending a diagnostic instruction to the TBOX2 to control the TBOX2 to read the fault information of the node;
a failure information receiving unit 12, configured to receive failure information fed back by TBOX 2; the fault information comprises a fault vehicle type, a fault node and a fault code.
A diagnosis strategy query unit 13, configured to query a diagnosis strategy according to the fault information;
a fault information sending unit 14, configured to send the fault information to a cloud server 3 to control the cloud server 3 to query a diagnosis policy;
and the diagnosis strategy execution unit 15 is used for repairing the fault according to the diagnosis strategy.
Therefore, the vehicle-mounted intelligent system 1 arranged on the vehicle and the TBOX2 connected with the vehicle-mounted intelligent system realize the diagnosis of the vehicle to obtain the fault information, the diagnosis strategy corresponding to the fault information can be inquired through the vehicle-mounted intelligent system 1 or the fault information is sent to the cloud server 3, the cloud server 3 correspondingly inquires the diagnosis strategy corresponding to the fault information through the accumulated big data information, and the vehicle-mounted intelligent system 1 repairs the fault according to the diagnosis strategy.
As shown in fig. 5, the vehicle-mounted intelligent system 1 further includes:
a fault recording unit 16, configured to record relevant information in a fault repairing process;
a status information receiving unit 17 for receiving real-time status information of the node;
the fault analysis unit 18 is used for analyzing whether a fault exists in the node according to the real-time state information and the relevant information when the real-time state information is matched with any relevant information in the fault repairing process recorded by the vehicle-mounted intelligent system or the cloud server;
and the diagnosis instruction driving unit 19 is used for driving the diagnosis instruction sending unit when the vehicle-mounted intelligent system analyzes that the node has a fault.
When the vehicle-mounted intelligent system finds that the real-time state information of some nodes is abnormal and is the same as the real-time state information when the node fails last time, the node may fail the same as the node last time. Therefore, the vehicle-mounted intelligent system needs to perform predictive analysis on the fault according to the abnormal real-time state information, so as to perform pre-judgment on the fault possibly occurring in the node.
Further, the vehicle-mounted intelligent system further comprises:
and the parameter information receiving unit is used for receiving the real-time parameter information of the vehicle, wherein the real-time parameter information comprises the node use duration information or the vehicle mileage information.
And the service life analysis unit is used for predicting the nodes which reach the service life according to the real-time parameter information when the real-time parameter information reaches a preset value, and sending prompt information to a user.
Therefore, the fault which occurs at present can be recorded through the invention, and the fault which may occur to the part can be pre-judged through the algorithm.
In addition, in the present invention, TBOX2 is used to read failure information according to a diagnostic instruction. The vehicle-mounted intelligent system 1 and each node (namely each part of the whole vehicle) realize information transmission through TBOX2, and the vehicle-mounted intelligent system 1 sends a diagnosis command to TBOX2 through a communication protocol with TBOX2, so that TBOX2 is controlled to read fault information.
Meanwhile, the cloud server 3 is configured to query a diagnosis policy according to the fault information. It should be noted that the database of the cloud server 3 stores fault codes of all nodes (e.g., the meter ICM, the reverse radar RPA, the blind area detection system BSD, etc.) of each vehicle model and corresponding diagnosis strategies. When the vehicle-mounted intelligent system 1 acquires fault information of a whole vehicle through the TBOX2, the vehicle-mounted intelligent system 1 can send the fault information to the cloud server 3; after receiving the fault information, the cloud server 3 queries a unique corresponding diagnosis strategy according to the fault vehicle type, the fault node and the fault code recorded in the fault information, and sends the diagnosis strategy to the corresponding vehicle-mounted intelligent system 1.
Therefore, the vehicle-mounted intelligent system, the TBOX and the cloud server are combined, the self-diagnosis mode of the automobile parts is realized, the faults can be effectively checked, predicted, analyzed and confirmed, a suggested solution is given through artificial intelligent big data, the faults are automatically tried to be repaired, the manpower and fund investment of the whole automobile factory after sale is reduced, and the failure rate of the whole automobile is reduced.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113960988A (en) * | 2021-11-15 | 2022-01-21 | 合众新能源汽车有限公司 | Vehicle-mounted multimedia equipment with diagnosis function and diagnosis method |
| CN114579373A (en) * | 2021-12-13 | 2022-06-03 | 北京市建筑设计研究院有限公司 | Method and device for repairing algorithm resources, electronic equipment and storage medium |
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