Cloud analysis method, system and equipment for vehicle-mounted data and medium

Abstract

The invention discloses a cloud analysis method, system and device for vehicle-mounted data and a medium. The vehicle-mounted data cloud analysis method comprises the steps that a cloud end receives a data file sent by a vehicle end, and the data file comprises a plurality of data messages; analyzing a plurality of data messages from the data file; if the data file is the first data file, sequentially sending the data messages according to the analyzed message IDs and message periods of the data messages; and if the data message is not the first data message, sequentially sending the data message to the data message according to the message acquisition timestamp of the data message, the message acquisition timestamp of the previous data message, and the analyzed message ID and message period of each data message. By adopting the method and the device, the problem of data cluster sending caused by lack of time interval information is solved, and smoother and more real data playback experience is achieved. In the face of complex or accidental faults, powerful support can be provided, and the speed and accuracy of fault diagnosis and solution are improved.

Description

Technical Field

[0001] This application relates to the technical field of vehicle message processing, and particularly to a method, system, device, and medium for cloud parsing of in-vehicle data. Background Art

[0002] With the increase in the number of intelligent connected vehicles, the demand for solving vehicle faults in the market has increased significantly, resulting in the need to frequently dispatch service stations or maintenance personnel to the site to handle problems. Although modern vehicles support remote reading of fault codes, this method cannot cover all types of faults, especially for the diagnosis of intermittent faults. Therefore, uploading vehicle data to the cloud for remote analysis has become an urgent need so that engineers or after-sales service teams can more effectively conduct fault troubleshooting and repair. After the in-vehicle CAN / LIN communication data (usually each message length is within 13 bytes) is received by the controller, when a certain amount of data accumulates (for example, a large data file of about 1400 bytes can contain at least 100 CAN / LIN messages) or reaches a certain upload period, the system will package this set of data into a large data file and upload it to the cloud. After that, the system will continue to collect new CAN / LIN data, form another large data file and upload it again, and so on in a cycle.

[0003] To achieve remote analysis of the vehicle operating state, engineers need to rely on the large data files uploaded by the vehicle for detailed analysis and expect these data to be played back in the original order when they are transmitted in the vehicle. However, since each large data file contains multiple CAN / LIN messages and these messages do not contain time interval information, it leads to the phenomenon of clustered transmission of data during the remote playback process. This situation not only makes it difficult for engineers to judge whether there is data loss in the cloud, but also because the data is too dense, it is usually impossible to directly use graphical tools for effective data analysis. Summary of the Invention

[0004] Based on this, it is necessary to provide a method, system, device, and medium for cloud parsing of in-vehicle data for the above technical problems, which effectively overcomes the problem of clustered data transmission due to the lack of time interval information and realizes a smoother and more realistic data playback experience. In this way, even when facing complex or intermittent faults, it can provide strong support and significantly improve the speed and accuracy of fault diagnosis and solution.

[0005] In a first aspect, a method for cloud parsing of in-vehicle data is provided, including:

[0006] The cloud receives a data file sent by the vehicle end, where the data file includes multiple data messages;

[0007] Parse multiple data messages from the data file;

[0008] If the data file is the first data file, send each data message sequentially according to the message ID and message period of each parsed data message;

[0009] If the data message is not the first data message, send it sequentially to the data message according to the message acquisition timestamp of the data message, the message acquisition timestamp of the previous data message, the message ID and message period of each parsed data message.

[0010] In some examples, the step of if the data file is the first data file, send each data message sequentially according to the message ID and message period of each parsed data message, includes:

[0011] Determine the sending time of each data message according to the message ID and message period of each parsed data message;

[0012] Send each data message sequentially according to the sending time of each data message.

[0013] In some examples, if the data message is not the first data message, send it sequentially to the data message according to the message acquisition timestamp of the data message, the message acquisition timestamp of the previous data message, the message ID and message period of each parsed data message, includes:

[0014] Determine the sending time of each data message according to the message acquisition timestamp of the data message, the message acquisition timestamp of the previous data message, the message ID and message period of each parsed data message;

[0015] Send each data message sequentially according to the sending time of each data message.

[0016] In some examples, before the cloud receives the data file sent by the vehicle terminal, it further includes:

[0017] The vehicle collects data messages;

[0018] When the number of data messages reaches a predetermined quantity, pack the collected data messages to obtain the data file, and send the data file to the cloud.

[0019] In some examples, before the cloud receives the data file sent by the vehicle terminal, it further includes:

[0020] The vehicle collects data messages;

[0021] When the upload period is reached, pack the collected data messages to obtain the data file, and send the data file to the cloud.

[0022] In some examples, after sequentially sending data packets, it further includes:

[0023] Replaying the data packets according to the sending order and sending interval of the data packets.

[0024] In a second aspect, a cloud parsing system for vehicle-mounted data is provided, including:

[0025] A receiving module for receiving, in the cloud, a data file sent by a vehicle terminal, where the data file includes a plurality of data packets;

[0026] A parsing module for parsing a plurality of the data packets from the data file. When the data file is the first data file, each data packet is sequentially sent according to the packet ID and packet period of each parsed data packet. When the data packet is not the first data packet, it is sequentially sent to the data packet according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet.

[0027] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the steps of the cloud parsing method for vehicle-mounted data in the first aspect and any possible implementation manner of the first aspect.

[0028] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, it implements the steps of the cloud parsing method for vehicle-mounted data in the first aspect and any possible implementation manner of the first aspect.

[0029] In a fifth aspect, a computer program product is provided, on which a computer program is stored. When the program is executed by a processor, it implements the steps of the cloud parsing method for vehicle-mounted data in the first aspect and any possible implementation manner of the first aspect.

[0030] By adopting the embodiments of the present application, without changing the existing data packaging method and the content of the data file, through accurate calculation of the timestamps of message collection and the periods of message packets in large data files, the sending situation of vehicle-end data can be accurately reproduced in the cloud, ensuring the consistency between the data played back in the cloud and the actual data sending moments at the vehicle end. Through the embodiments of the present application, not only the integrity of the original data structure and the transmission efficiency are maintained, but also the accuracy and reliability of remote data analysis are greatly improved. Faults in the message packets can be located more accurately, and efficient data analysis can be carried out using graphical tools. It effectively overcomes the problem of clustered data sending caused by the lack of time interval information, and realizes a smoother and more realistic data playback experience. In this way, even in the face of complex or sporadic faults, strong support can be provided, significantly improving the speed and accuracy of fault diagnosis and solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Other features, objects, and advantages of the present application will become more apparent by reading the detailed description of the non-limiting embodiments with reference to the following drawings:

[0032] Figure 1 It is a flowchart of the method for cloud parsing of vehicle-mounted data provided by the embodiment of the present application;

[0033] Figure 2 It is a schematic diagram of cloud data file reception;

[0034] Figure 3 It is a schematic diagram of the data message packet parsed by the method for cloud parsing of vehicle-mounted data provided by the embodiment of the present application;

[0035] Figure 4 It is a structural block diagram of the system for cloud parsing of vehicle-mounted data provided by the embodiment of the present application;

[0036] Figure 5 It is a structural block diagram of the computer device provided by the embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] The present application will be further described in detail below with reference to the embodiments and the drawings. It can be understood that the specific embodiments described herein are only used to explain the related application, rather than limiting the application. Additionally, it should be noted that only parts related to the application are shown in the drawings for the sake of convenience of description.

[0038] It should be noted that, without conflict, the embodiments and the features of the embodiments in the present application can be combined with each other. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0039] The method, system, device, and medium for cloud parsing of vehicle-mounted data according to the embodiments of the present application will be described in detail below with reference to the drawings.

[0040] Figure 1 is a flowchart of a method for cloud parsing of in-vehicle data according to an embodiment of the present application. As Figure 1 shown, the method for cloud parsing of in-vehicle data according to an embodiment of the present application includes the following steps:

[0041] S101: The cloud receives a data file sent by the vehicle terminal, where the data file includes a plurality of data packets.

[0042] In an embodiment of the present application, before the cloud receives the data file sent by the vehicle terminal, it further includes: the vehicle collects data packets; when the number of data packets reaches a predetermined quantity, the collected data packets are packaged to obtain the data file, and the data file is sent to the cloud. Alternatively, the vehicle collects data packets; when the upload period arrives, the collected data packets are packaged to obtain the data file, and the data file is sent to the cloud.

[0043] S102: Parse a plurality of the data packets from the data file.

[0044] S103: If the data file is the first data file, send each data packet sequentially according to the packet ID and packet period of each parsed data packet.

[0045] In a specific example, if the data file is the first data file, sending each data packet sequentially according to the packet ID and packet period of each parsed data packet includes: determining the sending time of each data packet according to the packet ID and packet period of each parsed data packet; sending each data packet sequentially according to the sending time of each data packet.

[0046] S104: If the data packet is not the first data packet, send the data packet sequentially according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet.

[0047] In a specific example, if the data packet is not the first data packet, sending the data packet sequentially according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet includes: determining the sending time of each data packet according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet; sending each data packet sequentially according to the sending time of each data packet.

[0048] A method for cloud parsing of vehicle-mounted data, after sequentially sending data packets, further includes: replaying the data packets according to the sending order and sending interval of the data packets.

[0049] Taking CAN packets or LIN packets as examples of data packets, as Figure 2 shown, after in-vehicle CAN / LIN communication data (usually each packet length is within 13 bytes) is received by the controller, when a certain amount of data is accumulated (for example, a large data file of about 1400 bytes can contain at least 100 CAN / LIN packets) or a certain upload period is reached, this group of data will be packed into a large data file and uploaded to the cloud. After that, the system will continue to collect new CAN / LIN data, form another large data file and upload it again, and cycle in turn.

[0050] In order to ensure as much as possible that the data can be accurately reproduced in the cloud according to the data sending order at the vehicle end, in the embodiments of the present application, by adding timestamps to the large data files and sending the data collected from the vehicle end according to the periodic information of each packet in the file. The result of data replay is basically consistent with the order of the original data at the vehicle end, so as to support engineers to quickly locate faults in CAN / LIN packets. At the same time, it also supports data analysis using a graphical interface, greatly improving the intuitiveness and efficiency of data parsing. Thus, not only can fault diagnosis be performed more accurately, but also the analysis problems caused by data density can be effectively overcome, further enhancing the ability to remotely monitor and maintain vehicles.

[0051] For example, by packing the CAN ID received and sent by the vehicle end controller and its corresponding data field into the large data file, without recording the timestamps of each individual CAN ID (saving 4 bytes), the capacity of the large data file is effectively increased, and the traffic required for uploading data packets is reduced.

[0052] To ensure that the sending time interval of in-vehicle data can be accurately reproduced in the cloud, the embodiments of the present application process the data received from the vehicle end as follows. First, the cycle tolerance of vehicle end data sending is strictly controlled within 10%. When the cloud server receives the large data file, it will distinguish and sort according to the cycles of different packet IDs in the database to ensure that packets with different IDs can be sent according to their original cycles. For example, in the first large data file received:

[0053] The first frame ID: 0x123 (cycle 10ms) is sent at time T1 (ms); the second frame 0x123 is sent 10ms later based on the first frame;

[0054] The first frame ID: 0x456 (period 50 ms) is sent at the (T1 + 1) moment (ms); the second frame 0x456 is sent 50 ms after the first frame.

[0055] The first frame ID: 0x789 (period 100 ms) is sent at the (T1 + 5) moment (ms); the second frame 0x789 is sent 100 ms after the first frame.

[0056] Since the acquisition time of the large data file is uniformly controlled by the in-vehicle single controller clock (such as the TBOX controller), this ensures that all acquired timestamps have the same absolute time reference. Therefore, if the acquisition time of the second large data file is delayed by T3 - T1 relative to the first large data file, the data sending moment in the second large data file will be adjusted as follows:

[0057] The first frame ID: 0x123 (period 10 ms) will be sent at the moment of T3 + (10 - (T3 - T1) % 10), and will continue to be sent sequentially at a 10-ms period;

[0058] The first frame ID: 0x456 (period 50 ms) will be sent at the moment of T3 + (50 - (T3 - (T1 + 1)) % 50), and will continue to be sent sequentially at a 50-ms period;

[0059] The first frame ID: 0x789 (period 100 ms) will be sent at the moment of T3 + (100 - (T3 - (T1 + 5)) % 100), and will continue to be sent sequentially at a 100-ms period.

[0060] As Figure 3 shown, it not only ensures the sequentiality of data during cloud playback and the consistency of time intervals, but also makes data analysis more accurate and intuitive, greatly improving the efficiency and accuracy of remote fault diagnosis.

[0061] According to the cloud parsing method of vehicle-mounted data in an embodiment of the present application, without changing the existing data packaging method and the content of the data file, by accurately calculating the timestamp of message collection and the period of the message in the big data file, the data transmission situation at the vehicle end can be accurately reproduced in the cloud, ensuring the consistency between the data played back in the cloud and the actual data transmission time at the vehicle end. Through the embodiments of the present application, not only the integrity and transmission efficiency of the original data structure are maintained, but also the accuracy and reliability of remote data analysis are greatly improved. The faults in the message can be more accurately located, and efficient data analysis can be carried out using graphical tools. It effectively overcomes the problem of clustered data transmission caused by the lack of time interval information and realizes a smoother and more realistic data playback experience. In this way, even in the face of complex or sporadic faults, strong support can be provided, significantly improving the speed and accuracy of fault diagnosis and solution.

[0062] In summary, through optimizing the data upload content and adopting targeted data processing technologies in the cloud, the present application realizes efficient data transmission and accurate data playback, thus greatly improving the ability of remote monitoring and fault diagnosis. This method not only ensures the integrity and consistency of the data, but also significantly enhances the flexibility and accuracy of data analysis.

[0063] Figure 4 It is a structural block diagram of a cloud parsing system for vehicle-mounted data according to an embodiment of the present application. As Figure 4 shown, the cloud parsing system for vehicle-mounted data according to an embodiment of the present application includes: a receiving module 410 and an analysis module 420, wherein:

[0064] The receiving module 410 is used to receive the data file sent from the vehicle end in the cloud, wherein the data file includes a plurality of data messages;

[0065] The parsing module 420 is used to parse a plurality of the data messages from the data file. When the data file is the first data file, each data message is sequentially sent according to the message ID and message period of each parsed data message. When the data message is not the first data message, the data message is sequentially sent according to the message collection timestamp of the data message, the message collection timestamp of the previous data message, the message ID and message period of each parsed data message.

[0066] The cloud parsing method for vehicle-mounted data according to the embodiments of the present application, without changing the existing data packaging method and the content of the data file, accurately calculates the timestamps of message collection and the periods of message packets in the large data file, enabling the accurate reproduction of the data transmission situation at the vehicle end in the cloud and ensuring the consistency between the data played back in the cloud and the actual data transmission moments at the vehicle end. Through the embodiments of the present application, not only the integrity of the original data structure and the transmission efficiency are maintained, but also the accuracy and reliability of remote data analysis are greatly improved. Faults in the message packets can be located more accurately, and graphical tools can be used for efficient data analysis. It effectively overcomes the problem of clustered data transmission caused by the lack of time interval information and realizes a smoother and more realistic data playback experience. In this way, even in the face of complex or sporadic faults, strong support can be provided, significantly improving the speed and accuracy of fault diagnosis and solution.

[0067] For the specific limitations of the cloud parsing system for vehicle-mounted data, reference can be made to the limitations of the cloud parsing method for vehicle-mounted data described above, which will not be elaborated here. Each module of the above cloud parsing system for vehicle-mounted data can be implemented in whole or in part by software, hardware, and their combinations. The above-mentioned each module can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above each module.

[0068] In one embodiment, a computer device is provided. Figure 5 It is the structural block diagram of the computer device provided in the embodiments of the present application. Refer to Figure 5 . The computer device includes a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, it implements the embodiments of the cloud parsing method for vehicle-mounted data described above. For example, execute: the cloud receives a data file sent by the vehicle end, where the data file includes multiple data packets;

[0069] Parse out multiple data packets from the data file;

[0070] If the data file is the first data file, then send each data packet sequentially according to the packet ID and packet period of each parsed data packet;

[0071] If the data packet is not the first data packet, then send it to the data packet sequentially according to the message collection timestamp of the data packet, the message collection timestamp of the previous data packet, the packet ID and packet period of each parsed data packet.

[0072] An embodiment of the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the processor executes the computer program, the foregoing embodiments of the cloud parsing method for vehicle data are implemented. For example, execute: The cloud receives a data file sent by the vehicle end, where the data file includes a plurality of data packets;

[0073] Parse out a plurality of the data packets from the data file;

[0074] If the data file is the first data file, then sequentially send each data packet according to the packet ID and packet period of each parsed data packet;

[0075] If the data packet is not the first data packet, then sequentially send the data packet according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet.

[0076] An embodiment of the present application provides a computer program product. The computer program product includes instructions that, when run, cause the method described in the embodiments of the present application to be executed. For example, the following steps of the cloud parsing method for vehicle data as shown can be executed. For example, execute: The cloud receives a data file sent by the vehicle end, where the data file includes a plurality of data packets; Figure 1 Parse out a plurality of the data packets from the data file;

[0077] If the data file is the first data file, then sequentially send each data packet according to the packet ID and packet period of each parsed data packet;

[0078] If the data packet is not the first data packet, then sequentially send the data packet according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet.

[0079] If the data packet is not the first data packet, then sequentially send the data packet according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet.

[0080] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above various methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0081] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0082] The above embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for cloud parsing of vehicle data, characterized in that Including: The cloud receives the data file sent by the vehicle end, where the data file includes multiple data packets; Parse multiple data packets from the data file; If the data file is the first data file, send each data packet sequentially according to the packet ID and packet period of each parsed data packet; If the data packet is not the first data packet, send it to the data packet sequentially according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet.

2. The cloud parsing method for in-vehicle data according to claim 1, wherein The step of, if the data file is the first data file, sending each data packet sequentially according to the packet ID and packet period of each parsed data packet, includes: Determine the sending time of each data packet according to the packet ID and packet period of each parsed data packet; Send each data packet sequentially according to the sending time of each data packet.

3. The cloud parsing method for in-vehicle data according to claim 1, wherein If the data packet is not the first data packet, the step of sending it to the data packet sequentially according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet, includes: Determine the sending time of each data packet according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet; Send each data packet sequentially according to the sending time of each data packet.

4. The cloud parsing method for in-vehicle data according to any one of claims 1-3, characterized in that Before the cloud receives the data file sent by the vehicle end, it further includes: The vehicle collects data packets; When the number of data packets reaches a predetermined quantity, pack the collected data packets to obtain the data file, and send the data file to the cloud.

5. The method for cloud parsing of in-vehicle data according to any one of claims 1-3, characterized in that Before the cloud receives the data file sent by the vehicle end, it further includes: The vehicle collects data packets; When the upload period arrives, pack the collected data packets to obtain the data file, and send the data file to the cloud.

6. The cloud parsing method for in-vehicle data according to claim 1, wherein After sequentially sending to the data packet, it further includes: Perform playback of the data packet according to the sending order and sending interval of the data packet.

7. A cloud parsing system for vehicle data, characterized in that, Including: A receiving module, used for the cloud to receive the data file sent by the vehicle end, where the data file includes multiple data packets; A parsing module, used to parse multiple data packets from the data file. When the data file is the first data file, send each data packet sequentially according to the packet ID and packet period of each parsed data packet. When the data packet is not the first data packet, send it to the data packet sequentially according to the message acquisition timestamp of the data packet, the message acquisition timestamp of the previous data packet, the packet ID and packet period of each parsed data packet.

8. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the cloud parsing method of vehicle-mounted data according to any one of claims 1-6.

9. A computer-readable storage medium, comprising a memory and a computer program stored on the memory and executable on a processor, characterized in that, When the program is executed by the processor, it implements the cloud parsing method of vehicle-mounted data according to any one of claims 1-6.

10. A computer program product, comprising a memory and a computer program stored on the memory and executable on a processor, characterized in that, When the program is executed by a processor, it implements the method for cloud parsing of vehicle-mounted data according to any one of claims 1-6.

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