WO2021142613A1 - 一种模拟诊断方法、设备及可读存储介质 - Google Patents

一种模拟诊断方法、设备及可读存储介质 Download PDF

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Publication number
WO2021142613A1
WO2021142613A1 PCT/CN2020/071981 CN2020071981W WO2021142613A1 WO 2021142613 A1 WO2021142613 A1 WO 2021142613A1 CN 2020071981 W CN2020071981 W CN 2020071981W WO 2021142613 A1 WO2021142613 A1 WO 2021142613A1
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vehicle
diagnostic
data
information
target
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PCT/CN2020/071981
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English (en)
French (fr)
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刘均
冯向军
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深圳市元征科技股份有限公司
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Priority to PCT/CN2020/071981 priority Critical patent/WO2021142613A1/zh
Priority to CN202080000791.1A priority patent/CN111448562A/zh
Publication of WO2021142613A1 publication Critical patent/WO2021142613A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9032—Query formulation
    • G06F16/90324—Query formulation using system suggestions
    • G06F16/90328—Query formulation using system suggestions using search space presentation or visualization, e.g. category or range presentation and selection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/20—Education
    • G06Q50/205—Education administration or guidance
    • G06Q50/2057—Career enhancement or continuing education service

Definitions

  • This application relates to the technical field of vehicle diagnosis, and in particular to a simulation diagnosis method, a diagnosis learning device and a readable storage medium.
  • the purpose of this application is to provide a simulation diagnosis method, a diagnosis learning device and a readable storage medium to simulate real-vehicle diagnosis learning by looking up the vehicle response data corresponding to the requested diagnosis information from the diagnosis data database, which can solve the problem of difficult to find The problem of real vehicle diagnosis and learning cannot be performed on the actual vehicle.
  • One aspect of this application provides a simulation diagnosis method, which includes:
  • the vehicle response data is fed back to the vehicle diagnostic program.
  • a diagnostic learning device which includes:
  • Memory used to store computer programs
  • the processor is used to implement the following steps when executing the computer program:
  • the vehicle response data is fed back to the vehicle diagnostic program.
  • This application also provides a readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:
  • the vehicle response data is fed back to the vehicle diagnostic program.
  • the vehicle diagnosis program corresponding to the target vehicle is started. Then, obtain the request data information that the vehicle diagnostic program interacts with the target vehicle during the running process. Query the vehicle response data corresponding to the requested data information in the diagnostic data database, and feed the vehicle response data back to the vehicle diagnostic program, so that the vehicle diagnostic program can simulate and diagnose the target vehicle based on the vehicle response data. In this way, the process of actual vehicle feedback response data can be simulated.
  • the vehicle diagnosis program can simulate and diagnose the target vehicle based on the vehicle response data. In this way, real-vehicle simulation diagnosis can be performed, allowing users to quickly become familiar with the diagnosis operations of various vehicle models without the user having to search for different real vehicles by themselves.
  • the embodiment of the present application also provides a diagnosis learning device and a readable storage medium corresponding to the above-mentioned analog diagnosis method, which has the above-mentioned technical effect, and will not be repeated here.
  • Fig. 1 is an implementation flowchart of a simulation diagnosis method in an embodiment of the application
  • Figure 2 is a schematic diagram of a target vehicle selection in an embodiment of the application
  • FIG. 3 is a schematic diagram of another target vehicle selection in an embodiment of the application.
  • Fig. 4 is a schematic diagram of a target vehicle selection confirmation in an embodiment of the application.
  • Fig. 5 is a schematic diagram of a simulated diagnosis menu in an embodiment of the application.
  • FIG. 6 is a schematic diagram of a specific request data information in an embodiment of the application.
  • FIG. 7 is a schematic diagram of a confirmation of requested data information in an embodiment of the application.
  • FIG. 8 is a schematic diagram of the state of each system after scanning by a CAN gateway in an embodiment of the application.
  • FIG. 9 is a schematic diagram of a specific state of the gearbox electronic control system after scanning by the CAN gateway in an embodiment of the application;
  • FIG. 10 is a schematic diagram of the state of the engine electronic control system after scanning by the CAN gateway in an embodiment of the application;
  • FIG. 11 is a schematic diagram of a specific implementation of a simulation diagnosis method in an embodiment of the application.
  • FIG. 12 is the request data information of an engine electronic control system in an embodiment of the application.
  • FIG. 13 is the response data of reading fault code of an engine electronic control system in an embodiment of the application.
  • FIG. 14 is a schematic structural diagram of a diagnostic learning device in an embodiment of the application.
  • FIG. 15 is a schematic diagram of a specific structure of a diagnostic learning device in an embodiment of the application.
  • Fig. 1 is a flowchart of a simulation diagnosis method in an embodiment of this application. The method includes the following steps:
  • This method can be applied to equipment capable of running vehicle diagnostic programs, such as vehicle diagnostic equipment or other smart equipment (smartphones, computers, etc.), or diagnostic learning equipment.
  • vehicle diagnostic equipment such as vehicle diagnostic equipment or other smart equipment (smartphones, computers, etc.), or diagnostic learning equipment.
  • the simulation diagnosis method will be described by taking the application in the diagnosis learning equipment as an example. When it is applied to other equipment, please refer to this, and will not repeat them here.
  • the user can operate the buttons and visual operation interface of the diagnostic learning device to input real-vehicle simulation diagnostic instructions to the diagnostic learning device.
  • the diagnosis learning equipment can determine the target vehicle to be simulated and diagnosed by using the actual vehicle simulation diagnosis instruction.
  • the target vehicle can be a specific vehicle or a vehicle of a certain model.
  • the methods for determining the target vehicle include but are not limited to the following two methods:
  • Method 1 Specify the target vehicle by the real-vehicle simulation diagnosis instruction: if the real-vehicle simulation diagnosis instruction carries vehicle information, the vehicle corresponding to the vehicle information is determined as the target vehicle.
  • the vehicle information may specifically be any kind of information that can uniquely determine the target vehicle, such as the vehicle model, the unique identification number of the vehicle, or the number of the existing vehicle that can be simulated by the actual vehicle.
  • the user can select the target vehicle (for example, check the vehicle information or directly input the vehicle information) on the real vehicle simulation interface of the learning diagnosis equipment, and determine to perform the real vehicle simulation.
  • the user can select the target vehicle by entering vehicle type or VIN information in the search box.
  • the target vehicle is determined to be Volkswagen/touareg[Touareg]/2009.
  • FIG. 3 shows the vehicle type information and VIN information, which can be combined to illustrate how to directly and quickly determine the target vehicle when the vehicle type information or VIN information is carried.
  • Method 2 When receiving the real-vehicle simulation diagnosis instruction, randomly determine the target vehicle: if no vehicle is specified in the real-vehicle diagnosis instruction, randomly select a vehicle/model from the real-vehicle simulation list as the target vehicle.
  • the real vehicle simulation list may specifically be a list of vehicles that can currently perform real vehicle simulation. If a vehicle is not specified in the actual vehicle diagnosis instruction, a vehicle/model can be randomly selected as the target vehicle from the actual vehicle simulation list. For example, the user can choose to perform a real vehicle simulation by randomly determining a real vehicle simulation object (the simulation object is the target vehicle) in the learning diagnosis device.
  • FIG. 2 is a schematic diagram of a target vehicle selection in an embodiment of this application.
  • the visualization interface the production areas of different models are divided for users to choose, such as the Americas, Europe, Asia, and China.
  • the visual interface After selecting a different region, the visual interface correspondingly displays the selection boxes of various vehicle types in the region.
  • FIG. 3 is a schematic diagram of another target vehicle selection in an embodiment of this application.
  • the user may recommend to the user a list of real vehicle simulations that the user may need to perform a simulation diagnosis.
  • the user can determine the target vehicle by clicking on the touch area corresponding to the corresponding model vehicle in the real vehicle simulation list.
  • Figure 4 is a schematic diagram of a target vehicle selection confirmation in an embodiment of the application, that is, after the user touches the selection box corresponding to the Volkswagen vehicle, the learning diagnosis device outputs a confirmation box that prompts confirmation so that the user can confirm whether to choose Volkswagen models are the target vehicles.
  • S102 Start a vehicle diagnostic program corresponding to the target vehicle, and obtain request data information that the vehicle diagnostic program interacts with the target vehicle during operation.
  • the vehicle diagnostic program corresponding to the target vehicle can be determined first. Specifically, the vehicle diagnostic program corresponding to the vehicle type to which the target vehicle belongs can be determined through the corresponding relationship between the vehicle type and the vehicle diagnostic program and by searching the corresponding relationship, and then the vehicle diagnostic program can be started.
  • the vehicle diagnosis program of the corresponding Volkswagen Touareg 2014 can be found according to the vehicle information, and then the vehicle diagnosis program is started;
  • the target vehicle is a BMW x2 model
  • the target vehicle to be simulated and diagnosed is a Toyota Corolla model
  • obtaining the requested data information may specifically be monitoring and identifying user operations during the operation of the vehicle diagnostic program, so as to obtain the requested data information.
  • FIG. 5 is a schematic diagram of a simulated diagnosis menu in an embodiment of this application
  • FIG. 6 is a schematic diagram of a specific request data information in an embodiment of this application
  • FIG. 7 is an application A schematic diagram of requesting data information confirmation in an embodiment.
  • Visible, 2009-Volkswagen-Touareg ⁇ Touareg ⁇ corresponding to the vehicle diagnostic program provided by the menu the menu includes: quick test, system scan (CAN scan), system selection, special functions, online functions, LT3 and maintenance help information;
  • CAN scan system scan
  • the vehicle diagnostic program outputs the specific options of the system scan and CAN gateway scan in the visual interface.
  • a prompt confirmation message about the CAN gateway scan can be output on the visual interface.
  • the vehicle diagnostic program corresponding to 2009-Volkswagen-Touareg [Touareg] can determine the specific request data information based on pre-defined, that is, when the target vehicle is actually stored, it needs to be sent to the real target vehicle The requested data information.
  • the requested data information there is no difference between the requested data information and the requested data information sent by the vehicle diagnostic program to the actual target vehicle under the same user operation and control in the case of a real target vehicle. That is, after the vehicle diagnostic program is started, the user can operate the vehicle diagnostic program. At this time, there is no actual target vehicle for the vehicle diagnostic program to diagnose. In order to make the user's operation smooth, it better simulates the actual vehicle diagnosis. At this time, the request data information of the interaction with the target vehicle during the running of the vehicle diagnostic program can be directly obtained. If the target vehicle actually exists, the requested data information needs to be transmitted to the target vehicle, and the target vehicle will respond to the requested data information.
  • the requested data information may be specifically different according to different user operations. That is, different request data is sent according to the different functions provided by the user operating the vehicle diagnostic program. It should be noted that for different functions, which specifically correspond to the data information requested by the river chief, you can refer to the specific settings of the specific vehicle diagnostic program, which will not be repeated here.
  • S103 Query vehicle response data corresponding to the requested data information in the diagnostic data database.
  • a diagnostic data database in order to simulate a real vehicle to respond to the requested data information, can be set in advance, and vehicle information and interaction data between the vehicle diagnostic equipment and the vehicle can be pre-stored in the diagnostic data database.
  • the diagnosis data database creation process includes:
  • Step 1 Obtain the interaction data between the diagnostic program and the corresponding vehicle type, as well as vehicle information;
  • Step 2 Use the interactive data and vehicle information to create a diagnostic data database.
  • the diagnostic learning equipment can collect the interactive data between the diagnostic program and the actual vehicle and record the vehicle information when the diagnostic program and the corresponding model of the vehicle are performing a real vehicle diagnosis. Then, analyze the interaction data and vehicle information, and store the interaction data and vehicle information in the diagnostic data database. Specifically, when storing interactive data and vehicle information, the vehicle information can be used as the tag information of the interactive data. Correspondence between vehicle information and interactive data can also be established.
  • the diagnostic program corresponding to the real-time acquisition of interactive information and vehicle information by the diagnostic learning device can be a program running in the diagnostic learning device, or it can be used in other devices that have a communication and interactive connection with the designated learning device.
  • the diagnostic data database includes vehicle information and interaction data between the diagnostic program and the actual vehicle; among them, the process of querying the vehicle response data corresponding to the requested data information in the diagnostic data database may include:
  • Step 1 Query the target vehicle information and target interaction data corresponding to the target vehicle in the diagnostic data database;
  • Step 2 Combining target interaction data and target vehicle information to determine vehicle response data.
  • the target vehicle information corresponding to the target vehicle can be queried from the diagnostic data database first, and then the target interaction data can be found according to the corresponding relationship between the vehicle information and the interaction data. Then combine the target interaction data and target vehicle information to determine the vehicle response data. For example, you can directly find the vehicle response data corresponding to the requested data information from the target interaction data; when the interaction data records how to obtain the vehicle response data based on the vehicle information, you can also use the vehicle information to determine the vehicle response data based on the interaction data . For example, the vehicle response data needs to include the frame number in the vehicle information.
  • a communication connection can be established between the diagnostic learning device and the diagnostic data database through any of the common communication methods such as network, serial port, USB, Bluetooth, or program.
  • Query the vehicle response data corresponding to the requested data information in the diagnostic data database that is, query the diagnostic data database connected via any one of the network, serial port, USB, Bluetooth, or program to obtain vehicle response data.
  • the vehicle response data is obtained by using the request data information and based on the interactive data and vehicle information collected during the actual vehicle diagnosis process. That is, the vehicle response data is the same as the vehicle response data fed back by the actual vehicle in response to the request data information.
  • the vehicle response data can be fed back to the vehicle diagnostic program.
  • the target vehicle can be simulated and diagnosed based on the vehicle response data.
  • the process of processing the vehicle response data is the same as the vehicle response data fed back by the actual vehicle. Therefore, at the level of the vehicle diagnostic program and the user experience, the effect and experience of the actual vehicle diagnosis can be achieved.
  • FIG. 8 is a schematic diagram of the state of each system after scanning by a CAN gateway in an embodiment of the application
  • FIG. 9 is a gearbox electrical system after scanning by a CAN gateway in an embodiment of the application.
  • FIG. 10 is a schematic diagram of the state of the engine electronic control system after a CAN gateway scan in an embodiment of the application.
  • the vehicle response data can specifically include but not limited to: engine electronic control system, transmission electronic control system, brake electronics, steering angle sensor, entry and start permit, front passenger seat adjustment device, air conditioning/heating Electronic devices, electronic central electrical systems, airbags, steering column electronic equipment, instrument panels, data bus diagnostic interfaces, four-wheel drive electronic equipment, level control systems and other systems, the corresponding status can be normal or faulty.
  • the user can select the specific content that needs to be viewed in detail. For example, when the electronic control system of the rear transmission is selected, the specific information of the electronic control system of the transmission is output; when the electronic control system of the engine is selected, the specific information of the engine electronic control system is output.
  • the specific information may include but not limited to VW/Audi part number, system description, software version, car computer control unit code, coding workshop code, and other prompt information.
  • the specific information can be the specific content of the vehicle response data, or the content obtained after processing based on the vehicle response data.
  • the method provided in the embodiment of the application is applied to the diagnostic learning device to determine the target vehicle to be simulated and diagnosed by using the actual vehicle simulation diagnosis instruction; start the vehicle diagnostic program corresponding to the target vehicle, and obtain the vehicle diagnostic program and the target vehicle during operation.
  • Vehicle interaction request data information query the vehicle response data corresponding to the request data information in the diagnostic data database; feedback the vehicle response data to the vehicle diagnostic program.
  • the diagnostic learning device determines the target vehicle to be simulated and diagnosed, it starts the vehicle diagnostic program corresponding to the target vehicle. Then, obtain the request data information that the vehicle diagnostic program interacts with the target vehicle during the running process. Query the vehicle response data corresponding to the requested data information in the diagnostic data database, and feed the vehicle response data back to the vehicle diagnostic program, so that the vehicle diagnostic program can simulate and diagnose the target vehicle based on the vehicle response data. In this way, the process of actual vehicle feedback response data can be simulated.
  • the vehicle diagnosis program can simulate and diagnose the target vehicle based on the vehicle response data. In this way, real-vehicle simulation diagnosis can be performed, allowing users to quickly become familiar with the diagnosis operations of various vehicle models without the user having to search for different real vehicles by themselves.
  • FIG. 11 is a schematic diagram of a specific implementation of a simulation diagnosis method in an embodiment of this application.
  • the specific implementation process includes the following steps:
  • the interactive data includes, but is not limited to, vehicle diagnostic communication protocol data.
  • the interactive data and vehicle information corresponding to different vehicles stored in the diagnostic data database may adopt a unified format or a non-statistical format.
  • the non-uniform format can be different according to the order in which the commands are sent (that is, there are count bits in the data), and such data is subjected to unified naturalization processing during analysis and response.
  • the diagnostic learning device is connected to the diagnostic data database through any of the network, serial port, USB, Bluetooth, program and other methods.
  • the diagnostic learning equipment can start real vehicle simulation by randomly selecting or selecting from a list.
  • the diagnostic learning device randomly selects a piece of vehicle information from the diagnostic data database.
  • the diagnostic learning device obtains the stored vehicle information list from the diagnostic data database.
  • the diagnostic learning device starts the model diagnostic program of the corresponding vehicle (that is, the diagnostic program corresponding to the specific vehicle, the same as the vehicle diagnostic program).
  • the request data information that the vehicle type diagnostic program interacts with the vehicle during operation is transmitted to the data interaction processing program.
  • the data interaction processing program can be combined with the diagnostic data database to act as the process of the actual vehicle responding to the requested data information.
  • the data interaction processing program is transmitted to the diagnostic data database query program.
  • the diagnostic data database query program queries the response data according to the requested data information and transmits it to the data interaction processing program.
  • the data interaction processing program transmits the response data (same as the vehicle response data above) to the running vehicle diagnostic program.
  • the vehicle data interaction during the operation of the vehicle model diagnostic program repeatedly executes steps 8 to 11 to complete the real vehicle simulation.
  • Figure 12 is the request data information of an engine electronic control system in an embodiment of this application
  • Figure 13 is an engine electric control system in an embodiment of this application. Read the fault code response data of the control system.
  • the diagnostic learning equipment can present the corresponding car model selection boxes for real car simulation diagnosis in Europe, including 2009-Volkswagen-Touareg [Touareg], by touching or tapping 2009-Volkswagen-Touareg [ Touareg]; or, directly enter 2009-Volkswagen-Touareg [Touareg] in the model input box; or select 2009-Volkswagen-Touareg [Touareg] from the list of recommended real car simulation diagnosis.
  • the diagnostic learning device can learn that the user has selected the 2009-Volkswagen-Touareg [Touareg] as the target vehicle.
  • the diagnostic learning device outputs the confirmation message corresponding to 2009-Volkswagen-Touareg [Touareg].
  • the user can determine whether to perform a real car simulation diagnosis for the 2009-Volkswagen-Touareg [Touareg] according to the information prompt.
  • system scan CAN
  • a corresponding confirmation message for CAN gateway scanning will pop up.
  • the user can determine whether to perform the 2009-Volkswagen-Touareg [Touareg] corresponding CAN gateway scan according to the introduction content corresponding to the CAN gateway scan.
  • the diagnostic learning device enters the corresponding analog detection process.
  • the scan result of the 2009-Volkswagen-Touareg [Touareg] CAN gateway scan is displayed on the interface.
  • the scanning results are classified and displayed, and status results are given for each category, namely, fault or normal.
  • the user can select and confirm the item of interest to view specific details.
  • the diagnostic learning device can pop up the specific content of the gearbox electronic control system, such as the diagnosis system: 02 gearbox electronic control system (where 02 is the sequence of the gearbox electronic control system Number), VM/Audi part number: 09D927750HJ; System description: AL 750 6A; Software version: 1406; Automobile computer control unit number: 0004200; Coding workshop code: 31414 790 0001; Vehicle identification number (VIN): WVGAV67LX9D033064.
  • diagnosis system 02 gearbox electronic control system (where 02 is the sequence of the gearbox electronic control system Number), VM/Audi part number: 09D927750HJ; System description: AL 750 6A; Software version: 1406; Automobile computer control unit number: 0004200; Coding workshop code: 31414 790 0001; Vehicle identification number (VIN): WVGAV67LX9D033064.
  • the corresponding diagnosis system of the engine electronic control system is also displayed: 01 engine electronic control system (where 01 is the sequence number of the engine electronic control system), VM/Audi part number: 03H906032CS; System description: T-GP 0GE E; software version: 2001; car computer control unit number: 0011175; coding workshop code: 31414 790 0001; vehicle identification code (VIN): WVGAV67LX9D033064.
  • the user can also correspondingly select the requested data under the engine electronic control system.
  • the requested data information of the engine electronic control system includes but not limited to: version information, read fault code, clear fault, read data stream, read freeze frame, address test, channel adjustment Matching, basic system adjustment, security login, control unit coding, online security login and readiness test. After selecting different specific request data information, corresponding response data can be obtained. For example, after choosing to read the fault code, when there is no fault code content, no fault code will be displayed.
  • simulation diagnosis method provided by the embodiments of the present application can enable users such as vehicle maintenance technicians to simulate and complete the diagnosis operation learning of the actual vehicle without the actual vehicle.
  • the embodiments of the present application also provide a diagnosis learning device, and the following description of the diagnosis learning device and the above description of the simulation diagnosis method can correspond to each other and refer to each other.
  • the diagnostic learning equipment includes:
  • the memory D1 is used to store computer programs
  • the processor D2 is used to implement the following steps when executing a computer program:
  • the vehicle response data is fed back to the vehicle diagnostic program.
  • the processor is configured to implement the following steps when executing the computer program:
  • Use real-vehicle simulation diagnosis instructions to determine the target vehicle to be simulated and diagnosed including:
  • the vehicle corresponding to the vehicle information is determined as the target vehicle.
  • the processor is configured to implement the following steps when executing the computer program:
  • Use real-vehicle simulation diagnosis instructions to determine the target vehicle to be simulated and diagnosed including:
  • a vehicle/model of the vehicle is randomly selected as the target vehicle from the actual vehicle simulation list.
  • the processor is configured to implement the following steps when executing the computer program:
  • the diagnostic data database includes vehicle information and interaction data between the diagnostic program and the actual vehicle; querying the vehicle response data corresponding to the requested data information in the diagnostic data database includes:
  • the processor is configured to implement the following steps when executing the computer program:
  • Query the vehicle response data corresponding to the requested data information in the diagnostic data database including:
  • the diagnostic data database connected via any one of the network, serial port, USB, Bluetooth, or program to obtain vehicle response data.
  • the processor further implements the following steps when used to execute the computer program:
  • FIG. 15 is a schematic diagram of a specific structure of a diagnostic learning device provided by this embodiment.
  • the diagnostic learning device may have relatively large differences due to different configurations or performance, and may include one or more processors ( Central processing units, CPU) 322 (for example, one or more processors) and memory 332, and one or more storage media 330 (for example, one or more storage devices with a large amount of data) storing application programs 342 or data 344.
  • the memory 332 and the storage medium 330 may be short-term storage or persistent storage.
  • the program stored in the storage medium 330 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the data processing device.
  • the central processing unit 322 may be configured to communicate with the storage medium 330 and execute a series of instruction operations in the storage medium 330 on the diagnosis learning device 301.
  • the diagnostic learning device 301 may also include one or more power supplies 326, one or more wired or wireless network interfaces 350, one or more input and output interfaces 358, and/or one or more operating systems 341.
  • operating systems 341. For example, Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.
  • the steps in the analog diagnosis method described above can be implemented by the structure of the diagnosis learning device.
  • the embodiment of the present application also provides a readable storage medium, and a readable storage medium described below and a simulation diagnosis method described above can be referred to each other.
  • the vehicle response data is fed back to the vehicle diagnostic program.
  • Use real-vehicle simulation diagnosis instructions to determine the target vehicle to be simulated and diagnosed including:
  • the vehicle corresponding to the vehicle information is determined as the target vehicle.
  • Use real-vehicle simulation diagnosis instructions to determine the target vehicle to be simulated and diagnosed including:
  • a vehicle/model of the vehicle is randomly selected as the target vehicle from the actual vehicle simulation list.
  • the diagnostic data database includes vehicle information and interaction data between the diagnostic program and the actual vehicle; querying the vehicle response data corresponding to the requested data information in the diagnostic data database includes:
  • Query the vehicle response data corresponding to the requested data information in the diagnostic data database including:
  • the diagnostic data database connected via any one of the network, serial port, USB, Bluetooth, or program to obtain vehicle response data.
  • the readable storage medium may specifically be a U disk, a mobile hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk, or an optical disk that can store program codes. Readable storage medium.

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Abstract

一种模拟诊断方法、设备及可读存储介质。利用实车模拟诊断指令确定出待模拟诊断的目标车辆（S101）；启动目标车辆对应的车辆诊断程序，并获取车辆诊断程序在运行过程中与目标车辆交互的请求数据信息（S102）；查询诊断数据数据库中请求数据信息对应的车辆响应数据（S103）；将车辆响应数据反馈给车辆诊断程序（S104）。可模拟实际车辆反馈响应数据的过程。车辆诊断程序基于车辆响应数据即可对目标车辆进行模拟诊断。如此，便可进行实车模拟诊断，可让用户无需用户自行寻找不同真实车辆，便可快速熟悉各种车型的诊断操作。

Description

一种模拟诊断方法、设备及可读存储介质 技术领域
本申请涉及车辆诊断技术领域，特别是涉及一种模拟诊断方法、诊断学习设备及可读存储介质。
背景技术
汽车维修技师在日常维修过程中，经常遇到多种车型，需要使用多种不同的车型诊断程序对车辆进行维修检测。大部分技师仅对经常维修的车型熟悉诊断检测过程，遇到未维修过的车辆诊断检测过程就需要自行摸索或者求助别人。
目前，维修技师要熟悉更多车型诊断流程，需要找到大量实际的车辆进行学习。但通常情况下，找到大量实际车辆并进行实车诊断学习，是相对比较困难的。
综上所述，如何有效地解决实车诊断学习等问题，是目前本领域技术人员急需解决的技术问题。
发明内容
本申请的目的是提供一种模拟诊断方法、诊断学习设备及可读存储介质，以通过从诊断数据数据库中查找出请求诊断信息对应的车辆响应数据，来模拟实车诊断学习，可解决难以找到实际车辆，无法进行实车诊断学习的问题。
本申请一方面提供了一种模拟诊断方法，该方法包括：
利用实车模拟诊断指令确定出待模拟诊断的目标车辆；
启动所述目标车辆对应的车辆诊断程序，并获取所述车辆诊断程序在运行过程中与所述目标车辆交互的请求数据信息；
查询诊断数据数据库中所述请求数据信息对应的车辆响应数据；
将所述车辆响应数据反馈给所述车辆诊断程序。
本申请另一方面提供了一种诊断学习设备，该设备包括：
存储器，用于存储计算机程序；
处理器，用于执行所述计算机程序时实现以下步骤：
利用实车模拟诊断指令确定出待模拟诊断的目标车辆；
启动所述目标车辆对应的车辆诊断程序，并获取所述车辆诊断程序在运行过程中与所述目标车辆交互的请求数据信息；
查询诊断数据数据库中所述请求数据信息对应的车辆响应数据；
将所述车辆响应数据反馈给所述车辆诊断程序。
本申请还提供了一种可读存储介质，所述可读存储介质上存储有计算机程序，所述计算机程序被处理器执行时实现以下步骤：
利用实车模拟诊断指令确定出待模拟诊断的目标车辆；
启动所述目标车辆对应的车辆诊断程序，并获取所述车辆诊断程序在运行过程中与所述目标车辆交互的请求数据信息；
查询诊断数据数据库中所述请求数据信息对应的车辆响应数据；
将所述车辆响应数据反馈给所述车辆诊断程序。
应用本申请实施例所提供的方法，利用实车模拟诊断指令确定出待模拟诊断的目标车辆；启动目标车辆对应的车辆诊断程序，并获取车辆诊断程序在运行过程中与目标车辆交互的请求数据信息；查询诊断数据数据库中请求数据信息对应的车辆响应数据；将车辆响应数据反馈给车辆诊断程序。
在本方法中，确定出待模拟诊断的目标车辆之后，便启动该目标车辆对应的车辆诊断程序。然后，获得车辆诊断程序在运行过程中与目标车辆交互的请求数据信息。在诊断数据数据库中查询请求数据信息对应的车辆响应数据，并将车辆响应数据反馈的车辆诊断程序，以便车辆诊断程序基于车辆响应数据对目标车辆进行模拟诊断。如此，便可模拟实际车辆反馈响应数据的过程。车辆诊断程序基于车辆响应数据即可对目标车辆进行模拟诊断。如此，便可进行实车模拟诊断，可让用户无需用户自行寻找不同真实车辆，便可快速熟悉各种车型的诊断操作。
相应地，本申请实施例还提供了与上述模拟诊断方法相对应的诊断学习设备和可读存储介质，具有上述技术效果，在此不再赘述。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本申请实施例中一种模拟诊断方法的实施流程图；
图2为本申请实施例中一种目标车辆选择示意图；
图3为本申请实施例中另一种目标车辆选择示意图；
图4为本申请实施例中一种目标车辆选择确认示意图；
图5为本申请实施例中一种模拟诊断菜单示意图；
图6为本申请实施例中一种具体的请求数据信息示意图；
图7为本申请实施例中一种请求数据信息确认示意图；
图8为本申请实施例中一种CAN网关扫描后各系统的状态示意图；
图9为本申请实施例中一种CAN网关扫描后变速箱电控系统的具体状态示意图；
图10为本申请实施例中一种CAN网关扫描后发动机电控系统的状态示意图；
图11为本申请实施例中一种模拟诊断方法的具体实施示意图；
图12为本申请实施例中一种发动机电控系统的请求数据信息；
图13为本申请实施例中一种发动机电控系统的读故障码响应数据；
图14为本申请实施例中一种诊断学习设备的结构示意图；
图15为本申请实施例中一种诊断学习设备的具体结构示意图。
具体实施方式
为了使本技术领域的人员更好地理解本申请方案，下面结合附图和具体实施方式对本申请作进一步的详细说明。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
实施例一：
请参考图1，图1为本申请实施例中一种模拟诊断方法的流程图，该方 法包括以下步骤：
S101、利用实车模拟诊断指令确定出待模拟诊断的目标车辆。
该方法可应用能够运行车辆诊断程序的设备中，如车辆诊断设备或其他智能设备(智能手机、计算机等)，或诊断学习设备。下文以应用于诊断学习设备为例对模拟诊断方法进行说明，应用于其他设备时，可参照与此，在此不再一一赘述。
用户可对诊断学习设备的按钮、可视化操作界面进行操作，以向诊断学习设备输入实车模拟诊断指令。
诊断学习设备利用实车模拟诊断指令，便可确定出待模拟诊断的目标车辆。其中，目标车辆可以为某一具体车辆，也可为某一车型的车辆。
具体的，确定目标车辆的方式包括但不限于以下两种方式：
方式一，由实车模拟诊断指令指定目标车辆：若实车模拟诊断指令中携带了车辆信息，则将车辆信息对应的车辆确定为目标车辆。其中，车辆信息可以具体为车辆车型、车辆唯一识别号、或已有可实车模拟的车辆编号等任意一种能够唯一确定目标车辆的信息。举例说明，用户可在学习诊断设备的实车模拟界面选中目标车辆(如勾选车辆信息或直接输入车辆信息)，并确定进行实车模拟。例如，用户可在检索框了输入车型或VIN信息的方式选择目标车辆。例如，当用户在检索框内输入大众/touareg【途锐】/2009(或者该车型对应的VIN：WVGAV67LX9D0*****)，则确定目标车辆为大众/touareg【途锐】/2009。
附图3中有车型信息和VIN信息，可以结合这些信息说明，当携带了车型信息或者VIN信息时如何直接快速的确定目标车辆。
方式二，在接收到实车模拟诊断指令时，随机确定目标车辆：若实车诊断指令中未指定车辆，则从实车模拟列表中随机选择一个车辆/车型为目标车辆。其中，实车模拟列表可具体为当前能够进行实车模拟的车辆列表。在实车诊断指令中未指定车辆，则可从实车模拟列表中随机选择一个车辆/车型为目标车辆。举例说明，用户可在学习诊断设备中选择以随机确定实车模拟对象(模拟对象即目标车辆)的方式进行实车模拟。
举例说明，请参考图2，图2为本申请实施例中一种目标车辆选择示意图。在可视化操作界面，不同车型产地进行划分，以便用户选择，如划分 为美洲、欧洲、亚洲、中国。在选择了不同的地区之后，在可视化界面对应显示该地区的各类车型选择框。
举例说明，请参考图3，图3为本申请实施例中另一种目标车辆选择示意图。在用户使用学习诊断设备过程中，可基于用户的操作行为记录，向用户推荐用户可能需要进行模拟诊断的实车模拟列表。用户可通过点击实车模拟列表中相应的车型车辆对应的触摸区域，即可确定目标车辆。
如图4所示，图4为本申请实施例中一种目标车辆选择确认示意图，即在用户触摸大众车辆对应的选择框后，学习诊断设备输出信息提示确认的确认框，以便用户确认是否选择大众车型作为目标车辆。
S102、启动目标车辆对应的车辆诊断程序，并获取车辆诊断程序在运行过程中与目标车辆交互的请求数据信息。
不同的车型对应的车辆诊断程序不同，在确定出待模拟诊断的目标车辆之后，可首先确定出目标车辆对应的车辆诊断程序。具体的，可通过车型与车辆诊断程序的对应关系，通过查找对应关系，确定目标车辆所属车型对应的车辆诊断程序，然后启动车辆诊断程序。
举例说明：在确定出待模拟诊断的目标车辆为大众途锐2014款时，则可根据该车型信息找到对应的大众途锐2014款的车辆诊断程序，然后启动该车辆诊断程序；在确定出待模拟诊断的目标车辆为宝马x2款时，则可根据该车型信息找到对应的宝马x2款的车辆诊断程序，然后启动该车辆诊断程序；在确定出待模拟诊断的目标车辆为丰田卡罗拉款时，则可根据该车型信息找到对应的丰田卡罗拉款的车辆诊断程序，然后启动该车辆诊断程序。
其中，获取请求数据信息，可具体为在车辆诊断程序在运行过程中，对用户操作进行监控识别，以便获取请求数据信息。
下面以目标车型具体为2009-大众-Touareg【途锐】为例，来详细说明请求数据信息具体如何获取：
请参考图5、图6和图7，其中，图5为本申请实施例中一种模拟诊断菜单示意图；图6为本申请实施例中一种具体的请求数据信息示意图；图7为本申请实施例中一种请求数据信息确认示意图。可见，2009-大众-Touareg【途锐】对应的车辆诊断程序所提供的菜单，该菜单中包括：快速测试、 系统扫描(CAN扫描)，系统选择、特殊功能、在线功能、LT3和维修帮助信息；当用户选择系统扫描(CAN扫描)之后，车辆诊断程序在可视化界面对应输出系统扫描和CAN网关扫描的具体选项。当用户触摸选择了CAN网关扫描之后，可在可视化界面输出关于CAN网关扫描的提示确认信息。在用户选择确认之后，2009-大众-Touareg【途锐】对应的车辆诊断程序便可基于预先定义，确定出具体的请求数据信息，即在真实存储目标车辆的情况下，需要向真实的目标车辆发送的请求数据信息。
需要说明的是，该请求数据信息与在存在真实的目标车辆的情况下，在同样的用户操作控制作用下，车辆诊断程序发送给真实存在目标车辆的请求数据信息无差异。即，车辆诊断程序启动之后，用户便可操作车辆诊断程序。而此时，并没有实际目标车辆可供车辆诊断程序进行诊断，为了使得用户操作流畅，更好地模拟实车诊断。此时可直接获得车辆诊断程序在运行过程中与目标车辆交互的请求数据信息。若真实存在目标车辆，该请求数据信息即为需传输至目标车辆，而目标车辆会对该请求数据信息进行响应。
该请求数据信息可具体根据用户的操作不同而不同。即，根据用户操作车辆诊断程序所提供的不同功能而发送的不同请求数据。需要说明的是，对于不同功能具体对应河长请求数据信息，则可具体参照具体的车辆诊断程序的具体设置，在此不再一一赘述。
S103、查询诊断数据数据库中请求数据信息对应的车辆响应数据。
在本实施例中，为了实现模拟实车对请求数据信息进行响应，可预先设置一个诊断数据数据库，在该诊断数据数据库中可预先存储车辆信息和车辆诊断设备与车辆的交互数据。在利用实车模拟诊断指令确定出待模拟诊断的目标车辆之前，诊断数据数据库创建过程，包括：
步骤一、获取诊断程序与对应车型车辆的交互数据，以及车辆信息；
步骤二、利用交互数据和车辆信息创建诊断数据数据库。
为便于描述，下面将上述两个步骤结合起来进行说明。
诊断学习设备可在诊断程序与对应车型车辆进行实车诊断时，收集诊断程序与实车的交互数据，并记录车辆信息。然后，对交互数据和车辆信息进行分析，在诊断数据数据库中存储交互数据和车辆信息。具体的，在 存储交互数据和车辆信息时，可将车辆信息作为交互数据的标记信息。也可建立车辆信息与交互数据之间的对应关系。特别地，诊断学习设备实时获取交互信息和车辆信息所对应的诊断程序可为运行于诊断学习设备中的程序，也可为运用于与指定学习设备具有通信交互连接的其他设备中。
也就是说，诊断数据数据库包括车辆信息和诊断程序与实际车辆的交互数据；其中，查询诊断数据数据库中请求数据信息对应的车辆响应数据的过程，可包括：
步骤一、查询诊断数据数据库中目标车辆对应的目标车辆信息和目标交互数据；
步骤二、结合目标交互数据和目标车辆信息确定出车辆响应数据。
具体的，可首先从诊断数据数据库可中查询到与目标车辆对应的目标车辆信息，然后按照车辆信息与交互数据之间的对应关系，找到目标交互数据。然后结合目标交互数据和目标车辆信息确定出车辆响应数据。例如，可直接从目标交互数据中查找出与请求数据信息对应的车辆响应数据；当交互数据记录了如何基于车辆信息获取车辆响应数据时，也可基于交互数据，利用车辆信息确定出车辆响应数据。例如，车辆响应数据需要包括车辆信息中的车架号。
其中，诊断学习设备与诊断数据数据库之间可通过网络、串口、USB、蓝牙或程序等常见的通信方式中的任意一种方式建立通信连接。查询诊断数据数据库中请求数据信息对应的车辆响应数据，即查询通过网络、串口、USB、蓝牙或程序中的任意一种方式连接的诊断数据数据库，以获得车辆响应数据。
需要说明的是，该车辆响应数据为利用请求数据信息并基于实车诊断过程中收集的交互数据和车辆信息所获得的。即，该车辆响应数据与实际车辆响应请求数据信息而反馈的车辆响应数据相同。
S104、将车辆响应数据反馈给车辆诊断程序。
得到车辆响应数据之后，便可将车辆响应数据反馈给车辆诊断程序。
车辆诊断程序得到车辆响应数据之后，便可基于车辆响应数据对目标车辆进行模拟诊断。对于车辆诊断程序而言，它处理该车辆响应数据与实际车辆反馈的车辆响应数据的处理过程相同，因此在车辆诊断程序层面以 及用户体验上，可达到实车诊断的效果和体验。
举例说明：为便于理解，下面以目标车型具体为2009-大众-Touareg【途锐】为例，来详细说明车辆响应数据的具体内容以及车辆诊断程序基于车辆响应数据基于该车辆响应数据进行诊断后，在可视化界面反馈的响应结果：
请参考图8、图9和图10，其中，图8为本申请实施例中一种CAN网关扫描后各系统的状态示意图；图9为本申请实施例中一种CAN网关扫描后变速箱电控系统的具体状态示意图；图10为本申请实施例中一种CAN网关扫描后发动机电控系统的状态示意图。可见，车辆响应数据可具体包括但不限于：发动机电控系统、变速箱电控系统、制动电子装置、转向角传感器、进入及其起动许可、前乘客测座椅调整装置、空调/暖风电子装置、电子中央电气系统、安全气囊、转向柱电子设备、仪表板、数据总线诊断接口、四轮驱动电子设备、水平高度控制系统等系统，对应的状态可为正常或故障。用户可选择需要详细查看的具体内容，例如当选择后变速箱电控系统之后，则输出变速箱电控系统的具体信息；当选择发动机电控系统之后，则输出发动机电控系统的具体信息。其中，具体信息可包括但不限于VW/Audi零件号，系统说明、软件版本、汽车电脑控制单元编码、编码车间代码、以及其他提示信息。其中，具体信息即可为车辆响应数据的具体内容，也可为基于车辆响应数据处理后得到的内容。
在诊断学习设备中应用本申请实施例所提供的方法，利用实车模拟诊断指令确定出待模拟诊断的目标车辆；启动目标车辆对应的车辆诊断程序，并获取车辆诊断程序在运行过程中与目标车辆交互的请求数据信息；查询诊断数据数据库中请求数据信息对应的车辆响应数据；将车辆响应数据反馈给车辆诊断程序。
在本方法中，诊断学习设备确定出待模拟诊断的目标车辆之后，便启动该目标车辆对应的车辆诊断程序。然后，获得车辆诊断程序在运行过程中与目标车辆交互的请求数据信息。在诊断数据数据库中查询请求数据信息对应的车辆响应数据，并将车辆响应数据反馈的车辆诊断程序，以便车辆诊断程序基于车辆响应数据对目标车辆进行模拟诊断。如此，便可模拟实际车辆反馈响应数据的过程。车辆诊断程序基于车辆响应数据即可对目 标车辆进行模拟诊断。如此，便可进行实车模拟诊断，可让用户无需用户自行寻找不同真实车辆，便可快速熟悉各种车型的诊断操作。
为便于本领域技术人员更好地理解本申请实施例所提供的模拟诊断方法，下面结合具体的应用实例对上述模拟诊断方法进行详细说明。
请参考图11，图11为本申请实施例中一种模拟诊断方法的具体实施示意图。具体实现过程，包括以下步骤：
1、收集汽车诊断设备与车辆的交互数据。
其中，交互数据包括但不限于车辆诊断通讯协议数据。
2、分析交互数据及车辆信息，创建诊断数据数据库。
其中，诊断数据数据库中的存储的不同车辆对应的交互数据及车辆信息，可采用统一格式，也可采用非统计格式。例如，非统一格式可根据命令发送顺序(即数据中有计数位的)而不同的，这样的数据在解析时和应答时对数据进行统一归化处理。
3、诊断学习设备通过网络、串口、USB、蓝牙、程序等任意一种方式连接诊断数据数据库。
4、诊断学习设备可通过随机选择或者从列表中选择的方式开始实车模拟。
5、如果随机选择，则诊断学习设备随机从诊断数据数据库选出一项车辆信息。
6、如果列表选择，则诊断学习设备从诊断数据数据库中获取已存储的车辆信息列表。
7、诊断学习设备启动对应车辆的车型诊断程序(即具体车辆对应的诊断程序，同车辆诊断程序)。
8、车型诊断程序在运行过程中与车辆交互的请求数据信息传输给数据交互处理程序。
其中，数据交互处理程序即可结合诊断数据数据库扮演实际车辆对请求数据信息进行响应的过程。
9、数据交互处理程序传输给诊断数据数据库查询程序。
10、诊断数据数据库查询程序根据请求数据信息查询响应数据并传输给数据交互处理程序。
11、数据交互处理程序把响应数据(同上文中的车辆响应数据)传输给运行中的车型诊断程序。
车型诊断程序运行过程中的车辆数据交互反复执行步骤8至11，即可完成实车模拟。
下面以2009-大众-Touareg【途锐】为例，对上文步骤1至11的具体实现进行详细说明。
具体的，请参考图2-图10，图12和图13；其中，图12为本申请实施例中一种发动机电控系统的请求数据信息；图13为本申请实施例中一种发动机电控系统的读故障码响应数据。
当用户需要对2009-大众-Touareg【途锐】进行实车模拟时，由于2009-大众-Touareg【途锐】的地域划分为欧洲，因此用户可在诊断学习设备的可视化界面中，首先选定区域为欧洲，如此，诊断学习设备便可呈现出欧洲地区对应的可供进行实车模拟诊断的车型选框，其中即包括2009-大众-Touareg【途锐】，通过触摸或点按2009-大众-Touareg【途锐】的选框；或，在车型输入框中直接输入2009-大众-Touareg【途锐】；或者在推荐实车模拟诊断的列表中选择出2009-大众-Touareg【途锐】。如此，诊断学习设备便可获知用户选择了2009-大众-Touareg【途锐】作为目标车辆。此时，诊断学习设备输出2009-大众-Touareg【途锐】对应的确认信息。用户在看到确认信息之后，可根据信息提示，确定是否确定对2009-大众-Touareg【途锐】进行实车模拟诊断。
在用户点击了确定按钮之后，弹出2009-大众-Touareg【途锐】对应的实车模拟检测的菜单。用户可以根据需要，从快速测试、系统扫描(CAN扫描)、特殊功能、在线功能、LT3和维修帮助信息中选择想要进行测试的项目。
若用户选了系统扫描(CAN)功能选项，对应输出该选项下的两个子选项系统扫描和CAN网关扫描，以供用户进一步选定。
若检测到用户选择了CAN网关扫描这个子功能选项，则对应弹出CAN网关扫描的确认信息。用户可根据CAN网关扫描对应的介绍内容确定是否进行2009-大众-Touareg【途锐】对应的CAN网关扫描。
若用户选中了确定进行CAN网关扫描，则诊断学习设备进入对应的模 拟检测流程。
然后基于响应数据在界面显示对2009-大众-Touareg【途锐】进行CAN网关扫描的扫描结果。该扫描结果分类显示，并为每一个类别给出了状态结果，即故障或正常。用户可对感兴趣的项目进行选择确认，以查看具体的详细信息。
例如，当选择了变速箱电控系统的具体状态之后，诊断学习设备可弹出变速箱电控系统的具体内容，如诊断系统：02变速箱电控系统(其中02为变速箱电控系统的排序编号)，VM/Audi零件号：09D927750HJ；系统说明：AL 750 6A；软件版本：1406；汽车电脑控制单元编号：0004200；编码车间代码：31414 790 0001；车辆识别码(VIN)：WVGAV67LX9D033064。
例如，当选择了发动机电控系统的状态，也相应显示发动机电控系统对应的诊断系统：01发动机电控系统(其中01为发动机电控系统的排序编号)，VM/Audi零件号：03H906032CS；系统说明：T-GP 0GE E；软件版本：2001；汽车电脑控制单元编号：0011175；编码车间代码：31414 790 0001；车辆识别码(VIN)：WVGAV67LX9D033064。
用户还可对应选择发动机电控系统下的请求数据，发动机电控系统的请求数据信息包括但不限于：版本信息、读故障码、清除故障、读数据流、读冻结帧、地址测试、通道调整匹配、系统基本调整、安全登录、控制单元编码、在线安全登录和就绪测试。当选择不同的具体请求数据信息之后，可获得相应的响应数据。如，在选择读故障码之后，当无故障码内容时，则显示无故障码。
可见，采用本申请实施例所提供的模拟诊断方法，便可使用户如车辆维修技师，在没有实际车辆的情况下，模拟完成实际车辆的诊断操作学习。
实施例二：
相应于上面的方法实施例，本申请实施例还提供了一种诊断学习设备，下文描述的一种诊断学习设备与上文描述的一种模拟诊断方法可相互对应参照。
参见图14所示，该诊断学习设备包括：
存储器D1，用于存储计算机程序；
处理器D2，用于执行计算机程序时实现以下步骤：
利用实车模拟诊断指令确定出待模拟诊断的目标车辆；
启动目标车辆对应的车辆诊断程序，并获取车辆诊断程序在运行过程中与目标车辆交互的请求数据信息；
查询诊断数据数据库中请求数据信息对应的车辆响应数据；
将车辆响应数据反馈给车辆诊断程序。
优选地，处理器，用于执行计算机程序时实现以下步骤：
利用实车模拟诊断指令确定出待模拟诊断的目标车辆，包括：
若实车模拟诊断指令中携带了车辆信息，则将车辆信息对应的车辆确定为目标车辆。
优选地，处理器，用于执行计算机程序时实现以下步骤：
利用实车模拟诊断指令确定出待模拟诊断的目标车辆，包括：
若实车诊断指令中未指定车辆，则从实车模拟列表中随机选择一个车辆/车型为目标车辆。
优选地，处理器，用于执行计算机程序时实现以下步骤：
诊断数据数据库包括车辆信息和诊断程序与实际车辆的交互数据；查询诊断数据数据库中请求数据信息对应的车辆响应数据，包括：
查询诊断数据数据库中目标车辆对应的目标车辆信息和目标交互数据；
结合目标交互数据和目标车辆信息确定出车辆响应数据。
优选地，处理器，用于执行计算机程序时实现以下步骤：
查询诊断数据数据库中请求数据信息对应的车辆响应数据，包括：
查询通过网络、串口、USB、蓝牙或程序中的任意一种方式连接的诊断数据数据库，以获得车辆响应数据。
优选地，处理器，用于执行计算机程序时还实现以下步骤：
在利用实车模拟诊断指令确定出待模拟诊断的目标车辆之前，获取诊断程序与对应车型车辆的交互数据，以及车辆信息；
利用交互数据和车辆信息创建诊断数据数据库。
具体的，请参考图15，为本实施例提供的一种诊断学习设备的具体结构示意图，该诊断学习设备可因配置或性能不同而产生比较大的差异，可以包括一个或一个以上处理器(central processing units，CPU)322(例如， 一个或一个以上处理器)和存储器332，一个或一个以上存储应用程序342或数据344的存储介质330(例如一个或一个以上海量存储设备)。其中，存储器332和存储介质330可以是短暂存储或持久存储。存储在存储介质330的程序可以包括一个或一个以上模块(图示没标出)，每个模块可以包括对数据处理设备中的一系列指令操作。更进一步地，中央处理器322可以设置为与存储介质330通信，在诊断学习设备301上执行存储介质330中的一系列指令操作。
诊断学习设备301还可以包括一个或一个以上电源326，一个或一个以上有线或无线网络接口350，一个或一个以上输入输出接口358，和/或，一个或一个以上操作系统341。例如，Windows ServerTM，Mac OS XTM，UnixTM，LinuxTM，FreeBSDTM等。
上文所描述的模拟诊断方法中的步骤可以由诊断学习设备的结构实现。
实施例三：
相应于上面的方法实施例，本申请实施例还提供了一种可读存储介质，下文描述的一种可读存储介质与上文描述的一种模拟诊断方法可相互对应参照。
一种可读存储介质，可读存储介质上存储有计算机程序，计算机程序被处理器执行时实现以下步骤：
利用实车模拟诊断指令确定出待模拟诊断的目标车辆；
启动目标车辆对应的车辆诊断程序，并获取车辆诊断程序在运行过程中与目标车辆交互的请求数据信息；
查询诊断数据数据库中请求数据信息对应的车辆响应数据；
将车辆响应数据反馈给车辆诊断程序。
优选地，计算机程序被处理器执行时实现以下步骤：
利用实车模拟诊断指令确定出待模拟诊断的目标车辆，包括：
若实车模拟诊断指令中携带了车辆信息，则将车辆信息对应的车辆确定为目标车辆。
优选地，计算机程序被处理器执行时实现以下步骤：
利用实车模拟诊断指令确定出待模拟诊断的目标车辆，包括：
若实车诊断指令中未指定车辆，则从实车模拟列表中随机选择一个车辆/车型为目标车辆。
优选地，计算机程序被处理器执行时实现以下步骤：
诊断数据数据库包括车辆信息和诊断程序与实际车辆的交互数据；查询诊断数据数据库中请求数据信息对应的车辆响应数据，包括：
查询诊断数据数据库中目标车辆对应的目标车辆信息和目标交互数据；
结合目标交互数据和目标车辆信息确定出车辆响应数据。
优选地，计算机程序被处理器执行时实现以下步骤：
查询诊断数据数据库中请求数据信息对应的车辆响应数据，包括：
查询通过网络、串口、USB、蓝牙或程序中的任意一种方式连接的诊断数据数据库，以获得车辆响应数据。
优选地，计算机程序被处理器执行时还实现以下步骤：
在利用实车模拟诊断指令确定出待模拟诊断的目标车辆之前，获取诊断程序与对应车型车辆的交互数据，以及车辆信息；
利用交互数据和车辆信息创建诊断数据数据库。
该可读存储介质具体可以为U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可存储程序代码的可读存储介质。
本领域的技术人员还可以进一步意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、计算机软件或者二者的结合来实现，为了清楚地说明硬件和软件的可互换性，在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。本领域的技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。

Claims (15)

  1. 一种模拟诊断方法，其特征在于，包括：
    利用实车模拟诊断指令确定出待模拟诊断的目标车辆；
    启动所述目标车辆对应的车辆诊断程序，并获取所述车辆诊断程序在运行过程中与所述目标车辆交互的请求数据信息；
    查询诊断数据数据库中所述请求数据信息对应的车辆响应数据；
    将所述车辆响应数据反馈给所述车辆诊断程序。
  2. 根据权利要求1所述的模拟诊断方法，其特征在于，所述利用实车模拟诊断指令确定出待模拟诊断的目标车辆，包括：
    若所述实车模拟诊断指令中携带车辆信息，则将所述车辆信息对应的车辆确定为所述目标车辆。
  3. 根据权利要求1所述的模拟诊断方法，其特征在于，所述利用实车模拟诊断指令确定出待模拟诊断的目标车辆，包括：
    若所述实车诊断指令中未携带车辆信息，则从实车模拟列表中随机选择一个车辆为所述目标车辆。
  4. 根据权利要求1所述的模拟诊断方法，其特征在于，所述诊断数据数据库包括车辆信息和诊断程序与实际车辆的交互数据；所述查询诊断数据数据库中所述请求数据信息对应的车辆响应数据，包括：
    查询所述诊断数据数据库中所述目标车辆对应的目标车辆信息和目标交互数据；
    结合所述目标交互数据和所述目标车辆信息确定出所述车辆响应数据。
  5. 根据权利要求1所述的模拟诊断方法，其特征在于，在所述利用实车模拟诊断指令确定出待模拟诊断的目标车辆之前，还包括：
    获取诊断程序与对应车型车辆的交互数据，以及车辆信息；
    利用所述交互数据和所述车辆信息创建所述诊断数据数据库。
  6. 一种诊断学习设备，其特征在于，包括：
    存储器，用于存储计算机程序；
    处理器，用于执行所述计算机程序时实现以下步骤：
    利用实车模拟诊断指令确定出待模拟诊断的目标车辆；
    启动所述目标车辆对应的车辆诊断程序，并获取所述车辆诊断程序在运行过程中与所述目标车辆交互的请求数据信息；
    查询诊断数据数据库中所述请求数据信息对应的车辆响应数据；
    将所述车辆响应数据反馈给所述车辆诊断程序。
  7. 根据权利要求6所述的诊断学习设备，其特征在于，所述处理器，用于执行所述计算机程序时实现以下步骤：
    所述利用实车模拟诊断指令确定出待模拟诊断的目标车辆，包括：
    若所述实车模拟诊断指令中携带车辆信息，则将所述车辆信息对应的车辆确定为所述目标车辆。
  8. 根据权利要求6所述的诊断学习设备，其特征在于，所述处理器，用于执行所述计算机程序时实现以下步骤：
    所述利用实车模拟诊断指令确定出待模拟诊断的目标车辆，包括：
    若所述实车诊断指令中未携带车辆信息，则从实车模拟列表中随机选择一个车辆为所述目标车辆。
  9. 根据权利要求6所述的诊断学习设备，其特征在于，所述处理器，用于执行所述计算机程序时实现以下步骤：
    所述诊断数据数据库包括车辆信息和诊断程序与实际车辆的交互数据；所述查询诊断数据数据库中所述请求数据信息对应的车辆响应数据，包括：
    查询所述诊断数据数据库中所述目标车辆对应的目标车辆信息和目标交互数据；
    结合所述目标交互数据和所述目标车辆信息确定出所述车辆响应数据。
  10. 根据权利要求6所述的诊断学习设备，其特征在于，所述处理器，用于执行所述计算机程序时实现以下步骤：
    在所述利用实车模拟诊断指令确定出待模拟诊断的目标车辆之前，还包括：
    获取诊断程序与对应车型车辆的交互数据，以及车辆信息；
    利用所述交互数据和所述车辆信息创建所述诊断数据数据库。
  11. 一种可读存储介质，其特征在于，所述可读存储介质上存储有计 算机程序，所述计算机程序被处理器执行时实现以下步骤：
    利用实车模拟诊断指令确定出待模拟诊断的目标车辆；
    启动所述目标车辆对应的车辆诊断程序，并获取所述车辆诊断程序在运行过程中与所述目标车辆交互的请求数据信息；
    查询诊断数据数据库中所述请求数据信息对应的车辆响应数据；
    将所述车辆响应数据反馈给所述车辆诊断程序。
  12. 根据权利要求11所述的可读存储介质，其特征在于，所述计算机程序被处理器执行时实现以下步骤：
    所述利用实车模拟诊断指令确定出待模拟诊断的目标车辆，包括：
    若所述实车模拟诊断指令中携带车辆信息，则将所述车辆信息对应的车辆确定为所述目标车辆。
  13. 根据权利要求11所述的可读存储介质，其特征在于，所述计算机程序被处理器执行时实现以下步骤：
    所述利用实车模拟诊断指令确定出待模拟诊断的目标车辆，包括：
    若所述实车诊断指令中未携带车辆信息，则从实车模拟列表中随机选择一个车辆为所述目标车辆。
  14. 根据权利要求11所述的可读存储介质，其特征在于，所述计算机程序被处理器执行时实现以下步骤：
    所述诊断数据数据库包括车辆信息和诊断程序与实际车辆的交互数据；所述查询诊断数据数据库中所述请求数据信息对应的车辆响应数据，包括：
    查询所述诊断数据数据库中所述目标车辆对应的目标车辆信息和目标交互数据；
    结合所述目标交互数据和所述目标车辆信息确定出所述车辆响应数据。
  15. 根据权利要求11所述的可读存储介质，其特征在于，所述计算机程序被处理器执行时实现以下步骤：
    在所述利用实车模拟诊断指令确定出待模拟诊断的目标车辆之前，还包括：
    获取诊断程序与对应车型车辆的交互数据，以及车辆信息； 利用所述交互数据和所述车辆信息创建所述诊断数据数据库。
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