An intelligent cockpit system problem analysis method and device

Abstract

The present application belongs to the field of intelligent cockpit of automobile, and particularly relates to a method and device for analyzing problems of intelligent cockpit system. The present application comprises an execution module, a cockpit client, a remote server and an analysis terminal. The specific process is as follows: when a fault occurs in the intelligent cockpit system, the cockpit client sends a diagnosis request to the analysis terminal through the remote server, and after the diagnosis request is sent to the analysis terminal, the diagnosis request is screened; the analysis terminal analyzes and diagnoses the problems of the intelligent cockpit system, and feeds back the diagnosis result and part of the fault repair file to the cockpit client; the cockpit client converts the repair file into an intelligent cockpit system control instruction execution feedback to the execution module, and locates and repairs the fault of the intelligent cockpit system. The present application develops a method and device which can effectively and quickly analyze and diagnose the problems of the cockpit system, so as to further improve the reliability and safety of the intelligent cockpit system in use.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of intelligent cockpit of automobile, and particularly relates to a method and device for analyzing problems of intelligent cockpit system BACKGROUND

[0002] With the development of intelligence and networking of automobiles, the systems and functions in the cockpit of automobiles are becoming more and more complex, and the problems that may occur in the cockpit are also becoming diversified and complicated. At present, when a fault occurs in the cockpit system, the developer needs to analyze the faulty vehicle, acquire diagnostic codes through a diagnostic instrument, acquire message information through a CAN tool, and capture system logs to position the problem. This requires going to the customer site, and each information collection needs to be operated separately. In the early development process, the tester generally records the scene in which the problem occurs, and exports the logs saved in the system, and then hands them over to the developer for analysis. However, there are too many log information in the whole process, and it is difficult to know the running state at that time, such as the memory occupation and CPU occupation at that time. It is also difficult to know the information that is not reserved for printing through the logs, which may cause difficulty in problem positioning. When the vehicle is delivered to the user in the later stage, the user also needs to cooperate, which makes it more difficult to troubleshoot and analyze the problem, and the experience of the user is also poor. Android system can provide rich entertainment, navigation, communication, and auxiliary driving functions for drivers and passengers due to its openness and flexibility, and is widely used in the field of intelligent cockpit of automobile. For the cockpit of Android system, the existing technology generally uses ADB to acquire relevant logs of the system, and uses a CAN tool to acquire message information, which all need the on-site support of the developer, and each information needs to be acquired separately. The present application provides a method and device for analyzing problems of intelligent cockpit system to solve the problems of difficult information collection and poor timeliness in the prior art, and effectively improves the efficiency of problem solving. SUMMARY

[0003] The purpose of the present application is to develop a method and device that can effectively and quickly analyze and diagnose problems of cockpit system, so as to further improve the reliability and safety of intelligent cockpit system in use.

[0004] To achieve the above purpose, the first aspect of the present application provides a device for analyzing problems of intelligent cockpit system, which specifically comprises: an execution module, a cockpit client, a remote server and an analysis terminal; wherein,

[0005] The execution module is responsible for communicating with various modules of the vehicle infotainment system, collecting, viewing, and saving vehicle infotainment system data, receiving execution commands and applying them to the cockpit system; wherein, the execution module communicates with various modules of the vehicle infotainment system through the IPC (InterProcess Communication) communication protocol, and the various modules include, but are not limited to, MCU (Microcontroller Unit), and the vehicle infotainment system data includes vehicle infotainment system log information, vehicle diagnostic code information, and CAN message information;

[0006] The remote server is used for data storage and bidirectional network communication;

[0007] The cockpit client obtains vehicle system data and cockpit system log data from the execution module, and converts the vehicle system data into usage data for bidirectional network communication with the remote server; wherein, the cockpit client can obtain system operating status such as cockpit system memory usage and CPU usage by executing ADB (Android Debug Bridge) instructions;

[0008] The analysis terminal engages in bidirectional network communication with a remote server to acquire usage data from the cockpit client, establishing a problem analysis method for intelligent cockpit systems based on a remote analysis and diagnostic mode. Simultaneously, developers use the analysis terminal to analyze and diagnose the usage data. Specifically, the usage data includes test data and user usage data.

[0009] Preferably, the usage data includes real-time usage data and usage data within a specified time period; wherein the real-time usage data is obtained through the logcat command, the kernel log is obtained through dmesg, and usage data within the specified time period is extracted from the kernel log. Specifically, the real-time usage data is used to acquire and monitor the current operating status of the intelligent cockpit system; the usage data within the specified time period is used to analyze the causes and development process of faults in the intelligent cockpit system.

[0010] Preferably, a real-time bidirectional network communication protocol based on a WebSocket server framework is established on the remote server. This real-time bidirectional network communication protocol directly deploys and corrects remotely for certain faults. By directly deploying and correcting certain faults remotely, the efficiency of developers is improved, thereby helping users quickly resolve cockpit system malfunctions.

[0011] The second aspect of this invention proposes a problem analysis method for intelligent cockpit systems, the specific analysis process of which is as follows:

[0012] S1, when the intelligent cockpit system fails, the cockpit client sends a diagnosis request to the analysis terminal through the remote server, and after the diagnosis request is sent to the analysis terminal, the diagnosis request is screened;Specifically, the operation mode of sending the diagnosis request includes: large screen interface operation, language operation and specific physical button operation;

[0013] S2, the analysis terminal analyzes and diagnoses the problem of the intelligent cockpit system, and feeds back the diagnosis result and part of the fault repair file to the cockpit client;

[0014] S3, the cockpit client converts the repair file into intelligent cockpit system control instructions and feeds back to the execution module for intelligent cockpit system fault positioning and repair.

[0015] Preferably, in the process of converting the car machine system data into usage data, a log keyword filtering operation is established.

[0016] Preferably, in the log keyword filtering operation, the usage data is first traversed and screened according to the specified format, and the data segment outside the specified format is filtered out, then the data segment inside the specified format is segmented, and after the segmentation is completed, the similar field data of each data segment is aggregated, and a rollback evaluation mechanism is established in the similar field data aggregation step, and after the rollback evaluation mechanism reaches the set value, the obtained field data is transmitted to the analysis terminal.

[0017] Preferably, in the screening of the diagnosis request, the diagnosis request is divided into a general problem diagnosis request and a specific problem diagnosis request, wherein:

[0018] The general problem diagnosis request is analyzed and processed by constructing a standardized diagnosis model based on the remote analysis diagnosis mode;

[0019] The specific problem diagnosis request simplifies the field capture logic on the basis of the standardized diagnosis model analysis processing.

[0020] Preferably, in the standardized diagnosis model, regular expression is constructed for log keyword feature matching.

[0021] 1. The intelligent cockpit system problem analysis device is established to remotely and quickly analyze and diagnose the problems of the cockpit system. The two-way communication control between the remote server, the cockpit client and the analysis terminal can help the developer to monitor and capture the running situation of the cockpit system in real time, find potential problems in time, and effectively solve the problems of high maintenance cost and low troubleshooting efficiency caused by the on-site support of the developer.

[0022] 2. On the basis of 1, the intelligent cockpit system problem analysis method is established to further overcome the problem that there are too many cockpit system logs everywhere in the test and use process, and it is difficult to know the running state at that time. The problem analysis method in the application, on the basis of realizing the remote analysis and diagnosis of the developer, also performs log keyword filtering operation on the collected log data, thereby reducing the data amount and reducing the transmission frequency in the use data transmission process to the analysis terminal. By establishing a diagnosis request screening mechanism, the developer of the analysis terminal can quickly capture problem data, and filter and screen non-problem data, finally realize the effect of simplifying the use data and helping the developer to effectively and quickly analyze and diagnose the cockpit system. BRIEF DESCRIPTION OF DRAWINGS

[0023] The drawings constituting a part of the specification of the application are used to provide further understanding of the application, the illustrative embodiments of the application and the description thereof are used to explain the application, and do not constitute improper limitation on the application. In the drawings:

[0024] Figure 1 It is an intelligent cockpit system problem analysis device module diagram;

[0025] Figure 2 It is an intelligent cockpit system problem analysis method flow chart;

[0026] Figure 3 It is a standardized diagnosis model flow chart based on remote analysis and diagnosis mode;

[0027] Figure 4 It is a simplified field capture logic flow chart based on the analysis and processing of the standardized diagnosis model. DETAILED DESCRIPTION

[0028] The application will be described in detail below with reference to the drawings and in combination with the embodiments. It should be noted that the embodiments in the application and the features in the embodiments can be combined with each other without conflict.

[0029] The following detailed description is exemplary description, which is intended to provide further detailed description of the application. Unless otherwise specified, all technical terms used in the application have the same meaning as generally understood by those skilled in the art to which the application belongs. The terms used in the application are only used to describe the specific embodiments, and are not intended to limit the exemplary embodiments according to the application.

[0030] The first aspect provided in the embodiment proposes an intelligent cockpit system problem analysis device, as shown in Figure 1 The specific embodiments include: an execution module, a cockpit client, a remote server and an analysis terminal; wherein,

[0031] The execution module is responsible for communication with each module of the vehicle machine system, collecting, viewing and saving vehicle machine system data, receiving execution instructions and applying them to the cockpit system; wherein the execution module communicates with each module of the vehicle machine system through an IPC communication protocol, and the modules include but are not limited to MCU, and the vehicle machine system data includes vehicle machine system log information, vehicle diagnostic code information and CAN message information;

[0032] The remote server is used for data storage and bidirectional network communication;

[0033] The cockpit client obtains vehicle machine system data and cockpit system log data in the execution module, and converts the vehicle machine system data into usage data for bidirectional network communication with the remote server; wherein the cockpit client can obtain cockpit system memory usage and CPU usage and other system running conditions by executing ADB instructions;

[0034] The analysis terminal communicates with the remote server for bidirectional network communication to obtain usage data in the cockpit client, and establishes an intelligent cockpit system problem analysis method based on a remote analysis and diagnosis mode, and a developer analyzes and diagnoses the usage data through the analysis terminal. Specifically, the usage data includes test data and user usage data;

[0035] The usage data includes real-time usage data and usage data in a specified time period; wherein the real-time usage data is obtained through a logcat instruction, kernel logs are obtained through dmesg, and usage data in a specified time period is intercepted in the kernel logs. Specifically, the real-time usage data is used to obtain and monitor the current running state of the intelligent cockpit system; and the usage data in the specified time period is used to analyze the causes and fault development process of the intelligent cockpit system failure.

[0036] In the remote server, a real-time bidirectional network communication protocol based on a WebSocket server framework is established, and the real-time bidirectional network communication protocol directly deploys and corrects a remote correction file for partial faults.

[0037] In an embodiment, the bidirectional network communication protocol is combined with real-time usage data monitoring to perform cockpit system usage safety real-time monitoring and alarm during user use of the intelligent cockpit system, and encryption transmission, identity verification and permission control operations are set for the transmitted data to avoid leakage of user driving information.

[0038] Direct remote deployment and correction for partial faults are used to improve the work efficiency of developers, thereby helping users quickly solve cockpit system failure problems.

[0039] In one implementation, the partial faults include faults generated by routine problem diagnosis requests and faults generated by specific problem diagnosis requests. The criterion for their definition is whether the problems generated by the intelligent cockpit system can be directly repaired by means of, but not limited to, remote correction file replacement, supplementation, and remote upgrade control.

[0040] The second aspect of this embodiment proposes a problem analysis method for intelligent cockpit systems, such as... Figure 2 As shown, the specific analysis process is as follows:

[0041] S1. When the intelligent cockpit system malfunctions, the cockpit client sends a diagnostic request to the analysis terminal through a remote server. After the diagnostic request is sent to the analysis terminal, the diagnostic request is filtered. Specifically, the operation modes for sending the diagnostic request include: large screen interface operation, voice operation, and specific physical button operation.

[0042] S2. The analysis terminal analyzes and diagnoses problems in the intelligent cockpit system and feeds back the diagnosis results and some fault repair documents to the cockpit client.

[0043] S3. The cockpit client converts the repair file into intelligent cockpit system control commands and sends the execution feedback to the execution module to locate and repair faults in the intelligent cockpit system. The feedback can be provided via interface prompts, voice prompts, etc.

[0044] In the process of converting vehicle system data into usage data, a log keyword filtering operation was established.

[0045] In the log keyword filtering operation, the data is first traversed and filtered according to the specified format to filter out data segments outside the specified format. Then, the data segments within the specified format are segmented. After the segmentation is completed, the data segments are aggregated for similar fields. A rollback evaluation mechanism is set up in the similar field data aggregation step. After the rollback evaluation mechanism reaches the set value, the obtained field data is transmitted to the analysis terminal.

[0046] In the screening of diagnostic requests, the diagnostic requests are divided into regular problem diagnostic requests and specific problem diagnostic requests, wherein:

[0047] The routine problem diagnosis requests are analyzed and processed by constructing a standardized diagnostic model based on a remote analysis and diagnosis mode;

[0048] The specific problem diagnosis request simplifies the field capture logic based on the analysis and processing of the standardized diagnostic model.

[0049] In the standardized diagnostic model, log keyword feature matching is performed by constructing regular expressions, such as... Figure 3 As shown, the specific process is as follows:

[0050] A1. In the log keyword feature matching, field capture groups with different tag types are created for the log attributes of different cockpit system modules;

[0051] A2. Match fault types based on the log keywords captured by the field capture group;

[0052] A3. Automatically locate and process the fault based on the matched fault type.

[0053] like Figure 4 As shown, the specific process of the simplified field capture logic is as follows:

[0054] B1. When matching fault types based on log keywords captured by the field capture group, only fields that start and end with specific characters are matched.

[0055] B2. Filter and remove characters in the middle of the field;

[0056] B3. Conduct manual troubleshooting based on the matched log keywords and provide feedback on the results;

[0057] B4. After performing manual repair processing based on the diagnostic results of the standardized diagnostic model, the manual repair processing results are finally stored in the standardized diagnostic model library for use as routine problem diagnosis requests.

[0058] In a preferred embodiment, by storing the results of manual repair processing in a standardized diagnostic model library, it is possible to transform specific problem diagnostic requests into routine problem diagnostic requests. Through multiple cockpit system problem analyses and repairs, the manual operation process for developers is gradually reduced, thereby improving the automatic repair efficiency of the intelligent cockpit system.

[0059] As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative in all respects and are not the only ones. All modifications within the scope of this invention or its equivalents are included in this invention.

[0060] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0061] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0062] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0063] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0064] Finally, it should be noted that the above-mentioned embodiments are merely used to illustrate the technical solutions of the present application, rather than limit the technical solutions of the present application. Although the present application is described in detail with reference to the above embodiments, those skilled in the art should understand that the specific embodiments of the present application can be modified or replaced, and any modification or replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. An intelligent cockpit system problem analysis method based on an intelligent cockpit system problem analysis device, characterized by, The intelligent cockpit system problem analysis device specifically comprises: an execution module, a cockpit client, a remote server and an analysis terminal; wherein, The execution module is responsible for communication with each module of the vehicle machine system, simultaneously collects, views and saves vehicle machine system data, receives execution instructions and applies them to the cockpit system; The remote server is used for data storage and bidirectional network communication; The cockpit client acquires vehicle machine system data and cockpit system log data in the execution module, converts the vehicle machine system data into usage data and performs bidirectional network communication with the remote server; The analysis terminal performs bidirectional network communication with the remote server, acquires usage data in the cockpit client, establishes an intelligent cockpit system problem analysis method based on a remote analysis and diagnosis mode, and simultaneously analyzes and diagnoses the usage data through the analysis terminal by the developer; The specific analysis process is as follows: S1. When the intelligent cockpit system fails, the cockpit client sends a diagnosis request to the analysis terminal through the remote server, and after the diagnosis request is sent to the analysis terminal, the diagnosis request is screened; S2. The analysis terminal analyzes and diagnoses the intelligent cockpit system problem and feeds back the diagnosis result and part of the fault repair file to the cockpit client; S3. The cockpit client converts the repair file into an intelligent cockpit system control instruction execution feedback to the execution module for intelligent cockpit system fault positioning and repair; In the conversion of the vehicle machine system data into usage data, a log keyword filtering operation is established; In the log keyword filtering operation, the usage data is first traversed and screened according to the specified format, and data segments outside the specified format are filtered out, then the data segments in the specified format are segmented, and after the segmentation is completed, the usage data of each data segment is aggregated according to similar fields, a rollback evaluation mechanism is established in the similar field data aggregation step, and when the rollback evaluation mechanism reaches the set value, the obtained field data is transmitted to the analysis terminal.

2. The smart cabin system problem analysis method of claim 1, wherein, In the screening of the diagnosis request, the diagnosis request is divided into a general problem diagnosis request and a specific problem diagnosis request. 3.The smart cabin system problem analysis method of claim 2, wherein, The general problem diagnosis request is analyzed and processed by constructing a standardized diagnosis model based on a remote analysis and diagnosis mode.

4. The smart cabin system problem analysis method of claim 3, wherein, The specific problem diagnosis request simplifies the field capture logic on the basis of the standardized diagnosis model analysis and processing. 5.The smart cabin system problem analysis method of claim 3 or 4, characterized in that, In the standardized diagnosis model, regular expressions are constructed for log keyword feature matching. 6.The smart cabin system problem analysis method of claim 1, wherein, The usage data includes real-time usage data and usage data in a specified time period; wherein the real-time usage data is obtained through a logcat instruction, kernel logs are obtained through dmesg, and usage data in a specified time period is intercepted in the kernel logs.

7. The smart cabin system problem analysis method of claim 1, wherein, In the remote server, a real-time bidirectional network communication protocol based on a WebSocket server framework is established, and the real-time bidirectional network communication protocol directly deploys and corrects the remote correction file for part of the fault.

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