CN115951658A - Vehicle remote diagnosis method, device, server and storage medium - Google Patents
Vehicle remote diagnosis method, device, server and storage medium Download PDFInfo
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Abstract
The application relates to the technical field of vehicles, in particular to a remote diagnosis method, a remote diagnosis device, a server and a storage medium for a vehicle, wherein the method is applied to the server and comprises the following steps: acquiring vehicle data uploaded when a vehicle fails; diagnosing the state of parts of the whole vehicle according to the data of the whole vehicle to obtain a diagnosis result of the whole vehicle, positioning a fault source and a fault reason according to the diagnosis result, and generating a fault solution based on the fault source and the fault reason; and generating a diagnosis report according to the fault source, the fault reason and the fault solution, and sending the diagnosis report to a preset terminal so as to solve the fault of the vehicle based on the diagnosis report. Therefore, the problems that in the related technology, a fault algorithm model is backward and single, the accuracy of a fault diagnosis result is poor, server remote diagnosis cannot be performed on finished automobile data, the fault diagnosis difficulty is high, and meanwhile, the human-computer interaction experience of fault diagnosis is poor are solved.
Description
Technical Field
The present application relates to the field of vehicle technologies, and in particular, to a method, an apparatus, a server, and a storage medium for remote diagnosis of a vehicle.
Background
Along with the continuous development of the automobile industry, the intelligent and automatic degree of an automobile is gradually improved, the fault maintenance difficulty is higher and higher, when the automobile sends a fault in the driving process and cannot continuously drive, maintenance personnel cannot immediately reach a fault site for maintenance under the influence of factors such as geographical environment or weather, and maintenance personnel capable of quickly and accurately positioning and diagnosing the fault are relatively deficient, so that the current fault maintenance mechanism cannot meet the increasingly developed technology of the automobile.
In the related art, the controllers of the vehicles are used for performing fault self-diagnosis respectively and sending diagnosis results to the mobile terminal, but a fault diagnosis algorithm model in the prior art is too old and single, and meanwhile, remote diagnosis cannot be performed on data of the whole vehicle, so that the precision of the fault diagnosis result is poor, and a user cannot obtain friendly human-computer interaction experience when obtaining the fault diagnosis result.
Disclosure of Invention
The application provides a remote diagnosis method, a remote diagnosis device, a server and a storage medium of a vehicle, and aims to solve the problems that in the related technology, a fault algorithm model is backward and single, so that the accuracy of a fault diagnosis result is poor, server remote diagnosis cannot be performed on data of the whole vehicle, so that the fault diagnosis difficulty is high, and meanwhile, the man-machine interaction experience of fault diagnosis is poor.
The embodiment of the first aspect of the application provides a remote diagnosis method of a vehicle, which is applied to a server and comprises the following steps: acquiring whole vehicle data uploaded when a vehicle fails; diagnosing the state of the parts of the whole vehicle according to the data of the whole vehicle to obtain a diagnosis result of the whole vehicle, positioning a fault source and a fault reason according to the diagnosis result, and generating a fault solution based on the fault source and the fault reason; and generating a diagnosis report according to the fault source, the fault reason and the fault solution, and issuing the diagnosis report to a preset terminal so as to solve the fault of the vehicle based on the diagnosis report.
According to the technical means, the vehicle can be remotely diagnosed when the vehicle breaks down, the difficulty of fault diagnosis can be effectively reduced, meanwhile, the diagnosis result can be analyzed by improving the algorithm dimension of the fault algorithm model, the accuracy of the fault diagnosis result is improved, and the experience of a user for acquiring a fault diagnosis report can be improved by selecting or setting the preset terminal.
Optionally, in an embodiment of the application, the diagnosing the state of the component of the entire vehicle according to the data of the entire vehicle to obtain a diagnosis result of the entire vehicle includes: identifying a fault diagnosis alarm zone bit of a preset core component of an intelligent vehicle control domain, if the fault diagnosis alarm zone bit is identified, judging that the preset core component is in a fault state, otherwise, judging that the intelligent vehicle control domain is in a normal state; calculating the grade of the residual wearing degree of the wearing part of the intelligent vehicle control domain by using a wearing part residual wearing degree algorithm, if the grade of the wearing degree is less than a preset grade, judging that the wearing part of the intelligent vehicle control domain is in a wearing fault state, and if not, judging that the wearing part is in a normal state; and identifying whether any component of the intelligent cabin domain triggers an alarm, if so, judging that the intelligent cabin domain is in a fault state, otherwise, judging that the intelligent cabin domain is in a normal state.
According to the technical means, whether the areas of the damaged parts are in the fault state or not can be judged by identifying the fault diagnosis alarm zone bits of the core components of the intelligent vehicle control domain, calculating the residual wearing degree grade of the damaged parts, comparing the residual wearing degree grade with the preset grade and identifying the alarm state of the intelligent cabin domain, and the specific fault diagnosis is carried out on the states of the parts of the whole vehicle by utilizing the multi-dimensional fault algorithm, so that the accuracy of diagnosing whether the parts are in the fault state or not is improved.
Optionally, in an embodiment of the present application, the locating a fault source and a fault cause according to the diagnosis result includes: identifying the diagnosis result by using a fault detection and identification algorithm engine, and judging whether a fault is identified; and if the fault is identified, positioning a fault source and a fault reason, otherwise, entering a manual diagnosis mode, and determining the fault source and the fault reason based on manual diagnosis.
According to the technical means, the fault detection and identification algorithm engine and the manual diagnosis can be used for identifying the fault result and positioning the fault source and reason, so that the singleness and limitation of a diagnosis mode are avoided, the possibility of failure of the identification and diagnosis result is caused, and the success rate of fault diagnosis is improved.
Optionally, in an embodiment of the present application, the diagnostic report includes one or more of vehicle basic information, fault diagnosis quantity, fault information, fault handling advice, and fault resolution.
The embodiment of the second aspect of the present application provides a remote diagnosis device for a vehicle, where the device is applied to a server, and the device includes: the acquisition module is used for acquiring the whole vehicle data uploaded when the vehicle fails; the generating module is used for diagnosing the state of the parts of the whole vehicle according to the data of the whole vehicle to obtain a diagnosis result of the whole vehicle, positioning a fault source and a fault reason according to the diagnosis result, and generating a fault solution based on the fault source and the fault reason; and the sending module is used for generating a diagnosis report according to the fault source, the fault reason and the fault solution and sending the diagnosis report to a preset terminal so as to solve the fault of the vehicle based on the diagnosis report.
Optionally, in an embodiment of the present application, the generating module is further configured to: identifying a fault diagnosis alarm zone bit of a preset core component of an intelligent vehicle control domain, if the fault diagnosis alarm zone bit is identified, judging that the preset core component is in a fault state, otherwise, judging that the intelligent vehicle control domain is in a normal state; calculating the residual wearing degree grade of the wearing part in the intelligent vehicle control domain by using a wearing part residual wearing degree algorithm, if the wearing degree grade is smaller than a preset grade, judging that the wearing part in the intelligent vehicle control domain is in a wearing fault state, otherwise, judging that the wearing part is in a normal state; and identifying whether any part of the intelligent cabin domain triggers an alarm, if so, judging that the intelligent cabin domain is in a fault state, and otherwise, judging that the intelligent cabin domain is in a normal state.
Optionally, in an embodiment of the present application, the generating module is further configured to: identifying the diagnosis result by using a fault detection and identification algorithm engine, and judging whether a fault is identified; and if the fault is identified, positioning a fault source and a fault reason, otherwise, entering a manual diagnosis mode, and determining the fault source and the fault reason based on manual diagnosis.
Optionally, in one embodiment of the present application, the diagnostic report includes one or more of vehicle basic information, a fault diagnosis number, fault information, a fault handling recommendation, and a fault resolution.
An embodiment of a third aspect of the present application provides a server, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the remote diagnosis method of the vehicle as described in the above embodiments.
A fourth aspect of the present application provides a computer-readable storage medium, on which a computer program is stored, the program being executed by a processor for implementing a remote diagnosis method for a vehicle as described in the above embodiments.
Therefore, the application has at least the following beneficial effects:
1. according to the embodiment of the application, the vehicle can be remotely diagnosed when the vehicle breaks down, the difficulty of fault diagnosis can be effectively reduced, meanwhile, the diagnosis result can be analyzed through the algorithm dimension of the improved fault algorithm model, the accuracy of the fault diagnosis result is improved, and the experience of a user for acquiring a fault diagnosis report can be improved through the selection or setting of the preset terminal.
2. According to the method and the device, whether the areas of the vulnerable parts are in the fault state or not can be judged by identifying the fault diagnosis alarm zone bits of the core parts of the intelligent vehicle control domain, calculating the grade of the residual abrasion degree of the vulnerable parts, comparing the grade with the preset grade and identifying the alarm state of the intelligent cabin domain, and specific fault diagnosis is carried out on the states of the parts of the whole vehicle by utilizing a multi-dimensional fault algorithm, so that the accuracy of diagnosing whether the parts are in the fault state or not is improved.
3. According to the embodiment of the application, the fault result can be identified and the fault source and reason can be located through the fault detection and identification algorithm engine and the manual diagnosis, so that the singleness and limitation of a diagnosis mode are avoided, the possibility of failure of identification and diagnosis results is caused, and the success rate of fault diagnosis is improved.
Therefore, the technical problems that in the related technology, a fault algorithm model is backward and single, the accuracy of a fault diagnosis result is poor, server remote diagnosis cannot be performed on finished automobile data, the fault diagnosis difficulty is high, and meanwhile, the man-machine interaction experience of fault diagnosis is poor are solved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a block diagram of a fault diagnosis system provided in accordance with an embodiment of the present application;
FIG. 2 is a flow chart of a method for remote diagnosis of a vehicle provided in an embodiment of the present application;
FIG. 3 is a flow chart of a fault diagnosis service provided according to an embodiment of the present application;
fig. 4 is an exemplary diagram of a remote diagnosis apparatus of a vehicle provided according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a server according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
A remote diagnosis method, apparatus, server, and storage medium for a vehicle according to an embodiment of the present application are described below with reference to the accompanying drawings. In order to solve the problems mentioned in the background art, the application provides a remote vehicle diagnosis method, in the method, vehicle data uploaded when a vehicle has a fault are acquired, the states of parts of the vehicle are diagnosed according to the vehicle data to obtain a vehicle diagnosis result, a fault source and a fault reason are located according to the diagnosis result, a fault solution is generated according to the fault source and the fault reason, a diagnosis report is generated according to the fault source, the fault reason and the fault solution, and the diagnosis report is issued to a preset terminal so as to solve the fault of the vehicle based on the diagnosis report. Therefore, the problems that in the related technology, a fault algorithm model is backward and single, the accuracy of a fault diagnosis result is poor, server remote diagnosis cannot be performed on finished automobile data, the fault diagnosis difficulty is high, and meanwhile, the human-computer interaction experience of fault diagnosis is poor are solved.
As shown in fig. 1, the fault diagnosis system structure includes: the system comprises an automobile, a vehicle-mounted information acquisition module and a fault diagnosis system.
The method comprises the steps that vehicle data and fault information reported by a vehicle are analyzed through a cloud end, the vehicle part state, the fault source, the fault reason and specific solution suggestions of the vehicle are judged remotely, fault diagnosis reports are provided for users and 4S stores and serve as suggestion references of diagnosis results, and the vehicle serves as a signal generation end of a system and can generate various data and messages during normal operation and vehicle fault; the vehicle-mounted information acquisition module is used for storing and converting data and messages and transmitting the data and the messages to a server of the fault diagnosis system through a wireless network; the fault diagnosis system is used for pushing fault diagnosis results (reports) to users and 4S as references in a cloud diagnosis mode, and helps the users to quickly locate problems.
Based on the fault diagnosis system described in the above embodiment, the following explains the remote vehicle diagnosis method provided in the embodiment of the present application, where the method is applied to a server.
As shown in fig. 2, the remote diagnosis method of a vehicle includes the steps of:
in step S101, the entire vehicle data uploaded when the vehicle has a failure is acquired.
It can be understood that, before performing fault diagnosis on a vehicle, the embodiment of the present application needs to acquire vehicle data when the vehicle has a fault, where the data may be uploaded to a server through the vehicle.
Specifically, as shown in fig. 3, after the vehicle is powered on, before the vehicle fault is identified, the vehicle health status is detected by using a "vehicle health detection engine", and the detection contents include: maintenance reminders based on time, mileage, and user habits; displaying the residual wearing degree of the wearing parts based on the dimensions of time, driving mileage, use frequency, use duration, use scenes and the like; and detecting the states of important parts such as a camera, a radar and the like. The embodiment of the application can carry out health detection on the vehicle, so that the whole vehicle data when the vehicle fails is obtained through the server.
In step S102, the states of the parts of the whole vehicle are diagnosed according to the data of the whole vehicle to obtain a diagnosis result of the whole vehicle, a fault source and a fault reason are positioned according to the diagnosis result, and a fault solution is generated based on the fault source and the fault reason.
It can be understood that the vehicle can be remotely diagnosed when the vehicle has a fault, the difficulty of fault diagnosis can be effectively reduced, and meanwhile, the diagnostic result can be analyzed by improving the algorithm dimension of the fault algorithm model, so that the accuracy of the fault diagnosis result is improved.
Optionally, in an embodiment of the present application, diagnosing a state of a component of the entire vehicle according to data of the entire vehicle to obtain a diagnosis result of the entire vehicle, including: identifying a fault diagnosis alarm zone bit of a preset core component of the intelligent vehicle control domain, if the fault diagnosis alarm zone bit is identified, judging that the preset core component is in a fault state, otherwise, judging that the intelligent vehicle control domain is in a normal state; calculating the grade of the residual wearing degree of the wearing part of the intelligent vehicle control domain by using a wearing part residual wearing degree algorithm, if the grade of the wearing degree is less than a preset grade, judging that the wearing part of the intelligent vehicle control domain is in a wearing fault state, and otherwise, judging that the wearing part is in a normal state; and identifying whether any part of the intelligent cabin domain triggers an alarm, if so, judging that the intelligent cabin domain is in a fault state, and otherwise, judging that the intelligent cabin domain is in a normal state.
The preset core components may include a battery, a vehicle-mounted energy storage device, an SOC (State of Charge), a DC-DC (Data Controller-Data Controller), a brake system, a drive motor Controller, and the like, and are not particularly limited.
The preset level may be specifically set according to an actual situation, and is not specifically limited.
It can be understood that according to the embodiment of the application, whether each region is in a fault state can be judged by identifying the fault diagnosis alarm zone bit of the core component of the intelligent vehicle control domain, calculating the grade of the residual wearing capacity of the wearing part, comparing the grade with the preset grade and identifying the alarm state of the intelligent cabin domain, and the specific fault diagnosis is performed on the state of the parts of the whole vehicle by using a multi-dimensional fault algorithm, so that the fault diagnosis accuracy is improved.
Specifically, the fault diagnosis is performed on the whole vehicle through the fault detection and identification algorithm engine, wherein the algorithm dimension of the fault detection and identification algorithm engine is based on the fault diagnosis of the whole vehicle multi-dimensional parts of the intelligent vehicle control domain, the intelligent driving domain and the intelligent cabin domain, and any abnormality or fault of the intelligent vehicle control domain, the intelligent driving domain and the intelligent cabin domain triggers the fault detection and identification algorithm engine to perform the fault diagnosis, wherein the fault diagnosis algorithm dimension is as follows:
the diagnosis of the three-core electric component of the intelligent vehicle control domain can be based on GB/T32960.3-2016 technical specification third part of electric vehicle remote service and management system: communication protocol and data format, wherein the fault diagnosis alarm flag bit comprises: the system comprises a temperature difference alarm, a battery high-temperature alarm, a vehicle-mounted energy storage device type overvoltage alarm, a vehicle-mounted energy storage device type undervoltage alarm, an SOC low alarm, a single battery overvoltage alarm, a single battery undervoltage alarm, an SOC overhigh alarm, an SOC jump alarm, a rechargeable energy storage system mismatching alarm, a battery single body consistency poor alarm, an insulation alarm, a DC-DC temperature alarm, a brake system alarm, a DC-DC state alarm, a driving motor controller temperature alarm, a high-voltage interlocking state alarm and a driving motor temperature alarm, wherein any part alarm can trigger a three-power state to be a fault state.
The calculation rule of the residual wearing degree algorithm of the wearing parts of the intelligent vehicle control domain is as follows:
(1) Remaining mileage percentage =100% - (current accumulated mileage-last serviced mileage)/interval change mileage 100%.
(2) Percentage of remaining time =100% - (current date-date of last maintenance)/interval change time 100%.
(3) Remaining length of time percent wear =100% -current length of use/interval change length 100%.
(4) Residual use wear percentage =100% -current use/interval change times 100%.
(5) The health percentage of the air conditioner filter element is the minimum value of the remaining mileage percentage, the remaining time percentage and the remaining long wear percentage.
(6) And the health percentage of the antifreeze and the brake fluid is the minimum value of the remaining mileage percentage and the remaining time percentage.
(7) The health percentage of the wiper blade and the brake blade is the minimum value of the remaining mileage percentage, the remaining time percentage and the remaining use times abrasion degree percentage.
Wherein, the state standard of the wearing parts is as follows:
the state of the wearing part is normal: the percentage of residual wear is equal to or greater than a certain percentage, such as 30%.
Abnormal state of wearing parts: the percent residual wear is in a range, such as 5% to 30%.
Failure of the status of the wearing part: the percent remaining abrasiveness is less than a certain percentage, such as 5%.
The fault diagnosis algorithm of an IP Multimedia System (IMS) camera, a power amplifier, a central control screen, an instrument screen, an electronic rearview mirror screen, a left transparent A column screen and a right transparent A column screen of the intelligent cabin domain is a multi-dimensional fault diagnosis algorithm based on high-voltage fault alarm, low-voltage fault alarm, overhigh-temperature alarm, overlow-temperature alarm, abnormal network communication, overtime network and abnormal function, and the state of the cabin domain can be triggered by any part alarm to be a fault state.
The fault diagnosis algorithm of the millimeter wave radar, the laser radar and the DMS (Digital Media Storage, digital Media camera) camera in the intelligent driving domain is a multi-dimensional fault diagnosis algorithm based on high-voltage fault alarm, low-voltage fault alarm, overhigh temperature alarm, overlow temperature alarm, abnormal network communication, overtime network and abnormal function, and the alarm of any part can trigger the state of the driving domain to be a fault state.
Optionally, in an embodiment of the present application, locating a fault source and a fault cause according to the diagnosis result includes: identifying the diagnosis result by using a fault detection and identification algorithm engine, and judging whether a fault is identified; and if the fault is identified, positioning a fault source and a fault reason, otherwise, entering a manual diagnosis mode, and determining the fault source and the fault reason based on manual diagnosis.
It can be understood that the fault detection and identification algorithm engine and the manual diagnosis can be used for identifying the fault result and positioning the fault source and reason, so that the singleness and limitation of the diagnosis mode are avoided, the possibility of failure of the identification and diagnosis result is caused, and the success rate of fault diagnosis is improved.
Specifically, a fault detection and identification algorithm engine is used for automatically analyzing reported faults and giving an alarm to inform a user, if the fault detection and identification algorithm engine automatically identifies and diagnoses the faults, the fault detection and identification algorithm engine automatically pushes a diagnosis report and a corresponding strategy to the user, the strategy comprises reserving remote air upgrading and reserving to-store maintenance, if the engine cannot identify the faults, a manual diagnosis mode is entered, a professional technician carries out remote diagnosis and analysis on the user, the diagnosis report and the corresponding strategy are pushed to the user, and the strategy can be configured and comprises reserving remote air upgrading and reserving to-store maintenance.
In step S103, a diagnosis report is generated according to the fault source, the fault cause, and the fault solution, and the diagnosis report is issued to a preset terminal to solve the fault of the vehicle based on the diagnosis report.
It can be understood that the embodiment of the application can generate a diagnosis report through the fault diagnosis result and the solution, and send the diagnosis report to the user, and the user uses the diagnosis report to solve the fault of the vehicle.
Specifically, after the fault is generated, different fault contents can be displayed for users by using a friendly man-machine interaction mode to different levels of faults, the man-machine interaction mode takes an intelligent voice assistant as an example and provides different solution strategies for the users to refer, when the cloud receives a serious fault signal, the fault contents are prompted and fault voice prompts are broadcasted by the intelligent voice assistant, and a fault solution is recommended for the users in a card form, wherein when the fault exists, the fault prompts are broadcasted repeatedly after the vehicle is powered on until the fault prompts are closed by the users in a voice or manual mode.
After the fault diagnosis is completed, the user receives a fault diagnosis report provided by the fault detection and identification algorithm engine, the report comprises the global diagnosis results of the intelligent driving domain, the intelligent vehicle control domain and the intelligent cockpit domain, and if a fault is found, the diagnosis report shows the analyzed fault reason and the fault processing suggestion in detail.
Optionally, in one embodiment of the present application, the diagnostic report includes one or more of vehicle basic information, a number of fault diagnoses, fault information, a fault handling recommendation, and a fault resolution.
Specifically, the diagnostic report content includes: the method comprises the following steps of vehicle basic information, fault diagnosis quantity, fault overview, fault processing suggestions, processing suggestion display rules and fault solutions, wherein the method specifically comprises the following steps:
(1) Basic information of the vehicle: diagnostic time, carriage number, version.
(2) Number of failure diagnoses: planning diagnosis items, diagnosis completion items and fault numbers.
(3) Overview of the faults: the fault diagnosis system comprises a diagnosis domain, a total fault number of the domain, detailed fault description and processing suggestions of the domain and parts related to faults, wherein the fault display content comprises intelligent driving, an intelligent cockpit, the total fault number of the intelligent vehicle control and system risk degree, detailed part fault description, risk degree and processing suggestions of each plate, and related parts related to the faults, such as a data source diagnosis background, wherein the risk degree is health < early warning < fault.
(4) And (3) fault processing suggestion: automatically generated by a backend system or manually entered by an engineer.
(5) Processing a suggestion presentation rule: the processing recommendations are classified into three categories according to industry recommendations, with rules and content filled in by back-end engineers.
(6) The failure solution scheme comprises the following steps: recommending reservation remote air upgrade or reservation maintenance.
According to the remote diagnosis method for the vehicle, the vehicle data uploaded when the vehicle has a fault are acquired, the vehicle part state is diagnosed according to the vehicle data, a vehicle diagnosis result is obtained, the fault source and the fault reason are located according to the diagnosis result, a fault solution is generated based on the fault source and the fault reason, a diagnosis report is generated according to the fault source, the fault reason and the fault solution, and the diagnosis report is sent to a preset terminal so that the fault of the vehicle is solved based on the diagnosis report. Therefore, the problems that in the related technology, a fault algorithm model is backward and single, the accuracy of a fault diagnosis result is poor, server remote diagnosis cannot be performed on finished automobile data, the fault diagnosis difficulty is high, and meanwhile, the man-machine interaction experience of fault diagnosis is poor are solved.
Next, a remote diagnosis apparatus for a vehicle according to an embodiment of the present application, which is applied to a server, will be described with reference to the drawings.
Fig. 4 is a block schematic diagram of a remote diagnosis apparatus of a vehicle according to an embodiment of the present application.
As shown in fig. 4, the remote diagnosis apparatus 10 of the vehicle includes: the device comprises an acquisition module 100, a generation module 200 and a sending module 300.
The acquisition module 100 is used for acquiring vehicle data uploaded when a vehicle fails; the generating module 200 is configured to diagnose a state of a component of the entire vehicle according to data of the entire vehicle to obtain a diagnosis result of the entire vehicle, locate a fault source and a fault cause according to the diagnosis result, and generate a fault solution based on the fault source and the fault cause; the sending module 300 is configured to generate a diagnosis report according to a fault source, a fault cause, and a fault solution, and issue the diagnosis report to a preset terminal, so as to solve a fault of a vehicle based on the diagnosis report.
Optionally, in an embodiment of the present application, the generating module 200 is further configured to: identifying a fault diagnosis alarm zone bit of a preset core component of the intelligent vehicle control domain, if the fault diagnosis alarm zone bit is identified, judging that the preset core component is in a fault state, otherwise, judging that the intelligent vehicle control domain is in a normal state; calculating the residual wearing degree grade of the wearing part in the intelligent vehicle control domain by using a wearing part residual wearing degree algorithm, if the wearing degree grade is less than a preset grade, judging that the wearing part in the intelligent vehicle control domain is in a wearing fault state, otherwise, judging that the wearing part is in a normal state; and identifying whether any part of the intelligent cabin domain triggers an alarm, if so, judging that the intelligent cabin domain is in a fault state, and otherwise, judging that the intelligent cabin domain is in a normal state.
Optionally, in an embodiment of the present application, the generating module 200 is further configured to: identifying the diagnosis result by using a fault detection and identification algorithm engine, and judging whether a fault is identified; and if the fault is identified, positioning a fault source and a fault reason, otherwise, entering a manual diagnosis mode, and determining the fault source and the fault reason based on manual diagnosis.
Optionally, in one embodiment of the present application, the diagnostic report includes one or more of vehicle basic information, a number of fault diagnoses, fault information, a fault handling recommendation, and a fault resolution.
It should be noted that the foregoing explanation of the embodiment of the remote diagnosis method for a vehicle is also applicable to the remote diagnosis device for a vehicle of this embodiment, and is not repeated herein.
According to the remote diagnosis device for the vehicle, the vehicle data uploaded when the vehicle has a fault are acquired, the vehicle part state is diagnosed according to the vehicle data, a vehicle diagnosis result is obtained, the fault source and the fault reason are located according to the diagnosis result, a fault solution is generated according to the fault source and the fault reason, a diagnosis report is generated according to the fault source, the fault reason and the fault solution, and the diagnosis report is sent to the preset terminal so that the fault of the vehicle is solved based on the diagnosis report. Therefore, the problems that in the related technology, a fault algorithm model is backward and single, the accuracy of a fault diagnosis result is poor, server remote diagnosis cannot be performed on finished automobile data, the fault diagnosis difficulty is high, and meanwhile, the human-computer interaction experience of fault diagnosis is poor are solved.
Fig. 5 is a schematic structural diagram of a server according to an embodiment of the present application. The server may include:
a memory 501, a processor 502, and a computer program stored on the memory 501 and executable on the processor 502.
The processor 502, when executing the program, implements the remote diagnosis method of the vehicle provided in the above-described embodiment.
Further, the server further comprises:
a communication interface 503 for communication between the memory 501 and the processor 502.
A memory 501 for storing computer programs that can be run on the processor 502.
The Memory 501 may include a high-speed RAM (Random Access Memory) Memory, and may also include a non-volatile Memory, such as at least one disk Memory.
If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 may be connected to each other through a bus and perform communication with each other. The bus may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.
Optionally, in a specific implementation, if the memory 501, the processor 502, and the communication interface 503 are integrated on a chip, the memory 501, the processor 502, and the communication interface 503 may complete communication with each other through an internal interface.
The processor 502 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.
Embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements a remote diagnosis method of a vehicle as above.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a programmable gate array, a field programmable gate array, or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware that is related to instructions of a program, and the program may be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A remote diagnosis method for a vehicle, which is applied to a server, comprises the following steps:
acquiring vehicle data uploaded when a vehicle fails;
diagnosing the state of the parts of the whole vehicle according to the data of the whole vehicle to obtain a diagnosis result of the whole vehicle, positioning a fault source and a fault reason according to the diagnosis result, and generating a fault solution based on the fault source and the fault reason;
and generating a diagnosis report according to the fault source, the fault reason and the fault solution, and issuing the diagnosis report to a preset terminal so as to solve the fault of the vehicle based on the diagnosis report.
2. The method of claim 1, wherein the diagnosing the vehicle component state according to the vehicle data to obtain a vehicle diagnosis result comprises:
identifying a fault diagnosis alarm zone bit of a preset core component of an intelligent vehicle control domain, if the fault diagnosis alarm zone bit is identified, judging that the preset core component is in a fault state, otherwise, judging that the intelligent vehicle control domain is in a normal state;
calculating the residual wearing degree grade of the wearing part in the intelligent vehicle control domain by using a wearing part residual wearing degree algorithm, if the wearing degree grade is smaller than a preset grade, judging that the wearing part in the intelligent vehicle control domain is in a wearing fault state, otherwise, judging that the wearing part is in a normal state;
and identifying whether any part of the intelligent cabin domain triggers an alarm, if so, judging that the intelligent cabin domain is in a fault state, and otherwise, judging that the intelligent cabin domain is in a normal state.
3. The method of claim 1, wherein said locating a source of a fault and a cause of a fault based on said diagnostic results comprises:
identifying the diagnosis result by using a fault detection and identification algorithm engine, and judging whether a fault is identified;
and if the fault is identified, locating a fault source and a fault reason, otherwise, entering a manual diagnosis mode, and determining the fault source and the fault reason based on manual diagnosis.
4. The method of any of claims 1-3, wherein the diagnostic report includes one or more of vehicle basic information, a number of fault diagnoses, fault information, fault handling recommendations, and fault resolution.
5. A remote diagnosis apparatus for a vehicle, applied to a server, comprising:
the acquisition module is used for acquiring vehicle data uploaded when a vehicle fails;
the generating module is used for diagnosing the state of the parts of the whole vehicle according to the data of the whole vehicle to obtain a diagnosis result of the whole vehicle, positioning a fault source and a fault reason according to the diagnosis result, and generating a fault solution based on the fault source and the fault reason;
and the sending module is used for generating a diagnosis report according to the fault source, the fault reason and the fault solution and issuing the diagnosis report to a preset terminal so as to solve the fault of the vehicle based on the diagnosis report.
6. The apparatus of claim 5, wherein the generating module is further configured to:
identifying a fault diagnosis alarm zone bit of a preset core component of an intelligent vehicle control domain, if the fault diagnosis alarm zone bit is identified, judging that the preset core component is in a fault state, otherwise, judging that the intelligent vehicle control domain is in a normal state;
calculating the grade of the residual wearing degree of the wearing part of the intelligent vehicle control domain by using a wearing part residual wearing degree algorithm, if the grade of the wearing degree is less than a preset grade, judging that the wearing part of the intelligent vehicle control domain is in a wearing fault state, and if not, judging that the wearing part is in a normal state;
and identifying whether any part of the intelligent cabin domain triggers an alarm, if so, judging that the intelligent cabin domain is in a fault state, and otherwise, judging that the intelligent cabin domain is in a normal state.
7. The apparatus of claim 5, wherein the generating module is further configured to:
identifying the diagnosis result by using a fault detection and identification algorithm engine, and judging whether a fault is identified;
and if the fault is identified, positioning a fault source and a fault reason, otherwise, entering a manual diagnosis mode, and determining the fault source and the fault reason based on manual diagnosis.
8. The apparatus of any of claims 5-7, wherein the diagnostic report includes one or more of vehicle basic information, a number of fault diagnoses, fault information, fault handling recommendations, and fault resolution.
9. A server, comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the remote diagnosis method of a vehicle according to any one of claims 1 to 4.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor for implementing a remote diagnosis method of a vehicle according to any one of claims 1 to 4.
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| CN202310002867.XA CN115951658A (en) | 2023-01-03 | 2023-01-03 | Vehicle remote diagnosis method, device, server and storage medium |
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