Intelligent driving automobile offline detection method and system based on Ethernet communication

Abstract

The invention relates to the technical field of intelligent driving automobile offline detection, and particularly discloses an intelligent driving automobile offline detection method and system based on Ethernet communication. The invention discloses an intelligent driving automobile offline detection method based on Ethernet communication, and the method comprises the steps: S01, receiving a user instruction sent by a user through a user-side intelligent device for accessing a front-end detection module, and enabling the user-side intelligent device to access an intelligent driving automobile local area network through the Ethernet; the user instruction comprises an EOL detection request; s02, acquiring related equipment information of the intelligent driving automobile according to the user instruction; s03, the information of the related equipment of the intelligent driving automobile is transmitted to a rear-end processing module through HTTPS encryption communication; and step S04, the back-end processing module encapsulates the user instruction and related equipment information of the intelligent driving automobile through a protocol, and performs data interaction with an intelligent driving automobile domain controller to complete intelligent driving automobile offline detection.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent driving car offline detection, and in particular to an intelligent driving car offline detection method and system based on Ethernet communication. Background Art

[0002] Automotive EOL testing is a series of processes for comprehensive testing of automotive products off the production line, with the aim of ensuring the quality of automotive products. The test covers many aspects, such as battery charging and discharging performance, safety specification testing, parameter testing, and testing of BMS systems and auxiliary functions. Through highly integrated testing equipment combined with barcode recognition technology, the test process can be automatically started and the results can be intelligently judged, thus realizing the intelligence and automation of the entire process, which not only reduces manpower investment, but also significantly improves test efficiency.

[0003] EOL testing can generate the excitation signals required by the cockpit system and perform diagnosis of the vehicle module. At the same time, EOL testing can accurately evaluate the condition of the electrical connections in the cockpit by measuring a variety of physical parameters. In addition, it can also provide an efficient connection method between the connector and the vehicle cockpit wiring harness. Its software can clearly display the test process and give the judgment results for each test link.

[0004] In the field of smart driving vehicle manufacturing, EOL end-of-line testing is specially designed and developed for smart driving vehicles, and is part of the end-of-line testing phase of smart driving vehicles. This test is the final quality control checkpoint before smart driving vehicles are delivered to customers, and is also an indispensable test step in the end-of-line process of smart driving vehicles. These testing processes cover multiple links such as equipotential testing, comprehensive vehicle testing, AC / DC charging testing, and insulation testing.

[0005] EOL testing is widely used in various automotive products, including cars, trucks and buses. It not only helps to accurately diagnose vehicle faults, but also enables fast download of test data, thereby further optimizing the test process, reducing the workload of operators, and improving overall test efficiency. In addition, EOL testing can also read, decode and scan vehicle data, comprehensively check the status of the vehicle, accurately locate the fault point, and conduct comprehensive testing and configuration of the entire vehicle.

[0006] However, in the prior art, the end-of-line operation (EOL) and after-sales fault diagnosis of smart driving vehicles are mostly implemented by CAN communication, and the physical entity diagnostic instrument is connected to the vehicle's OBD port for use. The diagnostic instrument based on CAN communication has the problems of long development cycle, difficulty in reusing different projects due to factors such as different OBD interfaces, CAN protocols, and dedicated software development, and the need to manually connect the physical entity diagnostic instrument to the vehicle's OBD port, which is complicated to operate. In addition, the information provided by the method provided in the prior art is limited and the transmission rate is low. Summary of the invention

[0007] In view of the above problems, the first purpose of the present invention is to provide a method for offline detection of smart driving cars based on Ethernet communication. The present invention adopts technology based on Ethernet communication to develop a set of tools specifically used for offline detection and after-sales fault diagnosis of smart cars. The interface has strong reusability and rapid development. At the same time, it does not need to connect to OBD, has a high transmission rate, and can be operated by simply connecting to the smart car network. The interface used by the method provided by the present invention is convenient and easy to understand, and the UI design is simple and clear, which solves the problems existing in the prior art.

[0008] The second object of the present invention is to provide an intelligent driving car offline detection system based on Ethernet communication.

[0009] To achieve the first objective, the first technical solution of the present invention is: a method for detecting an offline intelligent driving vehicle based on Ethernet communication, comprising:

[0010] Step S01: receiving a user instruction sent by a user through a user-side smart device accessing a front-end detection module, wherein the user-side smart device is connected to a smart driving vehicle local area network via Ethernet; the user instruction includes an EOL detection request;

[0011] Step S02: Acquire relevant device information of the smart driving car according to the user instruction;

[0012] Step S03: Transmitting the relevant device information of the smart driving car to the back-end processing module via HTTPS encrypted communication;

[0013] Step S04: the back-end processing module encapsulates the user instruction and the relevant device information of the smart driving car through a protocol, and exchanges data with the smart driving car domain controller to complete the offline detection of the smart driving car.

[0014] Preferably, the step S04 further includes: a back-end processing module analyzes the result of the offline detection of the smart driving car through a protocol, and sends it to the user-end smart device.

[0015] Preferably, the EOL detection request includes an EOL static process, which is used for the static inspection stage of the offline process, including EPS clearing, ADU self-test, actuator testing, and sensor factory calibration.

[0016] Preferably, the EOL detection request includes an EOL dynamic process, which is used in the dynamic inspection phase of the offline process, including GIST dynamic calibration and vehicle chassis testing.

[0017] Preferably, in step S01, the front-end detection module is provided with permission protection, and the permission protection includes a static password, a dynamic password or identity verification.

[0018] Preferably, the user-side smart device includes a movable smart device and a vehicle-mounted fixed smart device.

[0019] Preferably, in step S01, the user instruction also includes a configuration query or modification request, and the configuration information is output or modified according to the request.

[0020] Preferably, in step S01, the user instructions also include after-sales service instructions for after-sales activation of automatic calibration, vehicle status query or fault diagnosis.

[0021] Preferably, the protocol in step S04 includes ROS, UDS protocol, DoIP protocol, and user-defined protocol.

[0022] To achieve the second purpose, the second technical solution of the present invention is: an intelligent driving car offline detection system based on Ethernet communication,

[0023] Front-end access module: receiving a user instruction sent by a user through a user-side smart device, the user-side smart device being connected to the local area network of the smart driving car through Ethernet; the user instruction including an EOL detection request; obtaining relevant device information of the smart driving car according to the user instruction; and transmitting the relevant device information of the smart driving car to the back-end server through HTTPS encrypted communication;

[0024] Back-end processing module: used to encapsulate the user instructions and the relevant device information of the smart driving car through the protocol, and transmit information with the smart driving car domain controller to complete the offline detection of the smart driving car;

[0025] The system is deployed in the smart driving car domain controller in SDK mode.

[0026] Beneficial effects of the above technical solution:

[0027] The present invention provides an offline detection method for smart driving cars based on Ethernet communication. Based on the technology of Ethernet communication, a set of tools specially applied to offline detection and after-sales fault diagnosis of smart cars is developed. The interface has strong reusability and rapid development. At the same time, there is no need to connect to OBD, the transmission rate is high, and the operation can be performed by simply connecting to the smart car network. The interface used by the method provided by the present invention is convenient and easy to understand, and the UI design is simple and clear. Compared with the offline solution of smart driving cars based on CAN and physical diagnostic instruments in the prior art, a large amount of development cost and material cost are saved, it is convenient to use, easy to migrate, and new functions can be added quickly. At the same time, the transmission rate based on Ethernet is also much higher than the transmission rate based on CAN, and more functions can be added later. It can be quickly adapted in the early stage of the smart driving car project, reduce the development difficulty, and shorten the project cycle. In the after-sales maintenance stage of smart driving cars, the training cost of after-sales employees can be reduced, and the cost of distributing physical diagnostic instruments can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0029] Figure 1 A flow chart of a method for detecting an offline smart driving vehicle based on Ethernet communication is provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0030] The following is a further detailed description of the implementation methods of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than an exhaustive list of all the embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0031] The terms "first", "second", etc. (if any) in the specification and claims are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way are interchangeable where appropriate so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0032] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0033] Embodiment 1

[0034] An embodiment of the present invention provides a method for detecting an offline intelligent driving vehicle based on Ethernet communication. The method flow chart is as follows: Figure 1 As shown, the specific steps include:

[0035] Step S01: receiving a user instruction sent by a user through a user-side smart device to access the front-end detection module, and the user-side smart device is connected to the smart driving car local area network through Ethernet; the user instruction includes an EOL detection request. In this embodiment, the user accesses the network associated with the whole vehicle based on Ethernet, and accesses the front-end interface through the user-side smart device. The user can directly use the browser to facilitate the user to directly operate on different devices, as long as the vehicle network is connected, including access through mobile phones, laptops and other smart devices. Preferably, if the smart car with in-car entertainment equipment is installed, the vehicle screen can also be connected to the vehicle network and accessed through the vehicle screen. The front-end interface access is set with permission protection to ensure that only internal maintenance personnel can use this function. The permission protection method includes many methods, and in this embodiment, it is preferably a static password, a dynamic password or identity authentication. The user instruction also includes after-sales service instructions for after-sales activation of automatic calibration, vehicle status query or fault diagnosis. In step S01, the user instruction also includes a configuration query or modification request, and outputs or modifies the configuration information according to the request.

[0036] Step S02: Obtain relevant device information of the smart driving car according to the user instruction. The accessed content includes version and configuration, EOL static process, EOL dynamic process after-sales function, etc. The accessed content is selected according to the needs of the user, and the accessed content is not limited to the above content. Functions developed according to user needs can be accessed from the front-end interface after permission configuration.

[0037] Among them, access to version and configuration is used to query the version or modify the configuration; the EOL static process is used for the static inspection stage of the offline process, including EPS clearing, ADU self-test, actuator test, and sensor factory calibration; the EOL dynamic process is used for the dynamic inspection stage of the offline process, including GIST dynamic calibration and vehicle chassis test; access to after-sales functions is used for after-sales activation of automatic calibration and vehicle status query.

[0038] Step S03: Transmitting the relevant device information of the smart driving car to the back-end processing module via HTTPS encrypted communication. Preferably, the back-end processing module is a back-end server, which adopts a lightweight framework design, performs encrypted communication with the front end via HTTPS, and uses a process authentication based on challenge confirmation to avoid malicious attacks.

[0039] Step S04: The back-end processing module encapsulates the user instructions and the relevant device information of the smart driving car through the protocol, and exchanges data with the smart driving car domain controller to complete the offline detection of the smart driving car. In this embodiment, the back-end server transmits information with the smart car domain controller through the protocol to complete the offline detection of the smart driving car. The back-end server and the smart car domain controller directly use general protocols and interfaces for data transmission, which is very helpful for agile development and migration between different projects, ensuring the timeliness of research and development. Protocols include ROS, UDS protocol, DoIP protocol, and user-defined protocol.

[0040] The domain controller of smart cars mainly includes NVIDIA Orin, Horizon J6 and other devices. The domain controller communicates with vehicle components, such as sensors, body systems including anti-lock braking systems, four-wheel start systems, active suspension systems, airbag systems, air conditioning systems, instrument systems, etc. The present invention is based on the data exchange between the domain controller of smart cars and vehicle components through a preset protocol, and then feeds back to the application end device for result reading.

[0041] The present invention can be deployed in the domain controller of a smart car in the form of SDK. Most of the mainstream operating systems currently used in the domain controller of a smart car are Linux or QNX systems. The SDK deployment method of the present invention can adapt to both systems at the same time. It only needs to be compiled to run normally in the domain controller, so it has better compatibility, adaptability and portability. Compared with the offline solution of smart driving cars based on CAN and physical diagnostic instruments in the prior art, the present invention saves a lot of development costs and material costs, is easy to use, easy to migrate, and can quickly add new functions. At the same time, the transmission rate based on Ethernet used in the present invention is also much higher than the transmission rate based on CAN in the prior art, and more functions can be added later. Using the method or system of the present invention, on the one hand, in the early stage of the smart driving car project, it can be quickly adapted, reduce the difficulty of development, and shorten the project cycle; on the other hand, in the after-sales maintenance stage of the smart driving car, it can also reduce the cost of after-sales employee training and reduce the cost of distributing physical diagnostic instruments.

[0042] The present invention provides an offline detection system for intelligent driving vehicles based on Ethernet communication, including a front-end access module and a back-end server module. Among them, the front-end access module: the user accesses the network associated with the whole vehicle based on Ethernet, and accesses the front-end interface through the user-side smart device; accesses the EOL static process and / or the EOL dynamic process to obtain relevant equipment information in the whole vehicle. The EOL static process includes EPS clearing, ADU self-test, actuator test, and sensor factory calibration. The EOL dynamic process includes GIST dynamic calibration and vehicle chassis test.

[0043] Back-end server module: used to transmit the relevant equipment information in the whole vehicle to the back-end server through HTTPS encrypted communication; and to transmit information with the smart car domain controller through the protocol to complete the offline detection of smart driving vehicles.

[0044] In the embodiment, the front-end access module is preferably a front-end UI interface, which can be directly operated on the browser, convenient for users to directly operate on different devices. As long as the vehicle network is connected, it can be used on network devices such as mobile phones and laptops. At the same time, dynamic passwords and identity authentication are used to ensure that only internal maintenance personnel can use this function. In addition, smart cars equipped with in-car entertainment equipment can also connect the in-car screen to the vehicle network and access it through the in-car screen.

[0045] In this embodiment, the back-end server module adopts a lightweight framework design, communicates with the front-end through HTTPS, and uses a challenge-based process authentication to avoid malicious attacks. The back-end server and the smart car domain controller directly use common protocols and interfaces for data transmission, which is very helpful for agile development and migration between different projects, ensuring R&D timeliness.

[0046] The present invention is developed using C, C++ and Vue languages, does not rely on complex libraries, is simple to compile, and is easy to deploy, and can be applied to domain controllers of different architectures.

[0047] In one embodiment, if the user wants to write the vehicle SN code during the EOL process, the front-end page of the present invention is opened on the browser of the application-end device, the SN code (for example, customized as 1234567) is entered, and the write button is clicked. The SN code data (1234567) can be sent to the back-end server of the present invention through https. The back-end server encapsulates the SN code data (0x11 0x33 0x01 0x02 0x03 0x04 0x05 0x06 0x07 0x33 0x11 checksum verification) according to the protocol defined by the smart car domain controller (0x11 0x33 data 0x33 0x11 checksum verification), and sends it to the relevant module in the domain controller, so as to complete the writing of the SN code. After completion, the relevant modules in the domain controller use the same protocol to send the write result successfully (0x11 0x33 0x01 0x33 0x11 checksum verification, 0x01 represents success) to the back-end server, and the back-end server decodes the result and returns it to the front-end for display to the user.

[0048] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made on the basis of the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present invention are still within the protection scope of the present invention.

[0049] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

Claims

1. A method for detecting the offline status of an intelligent driving vehicle based on Ethernet communication, characterized in that: include: Step S01: receiving a user instruction sent by a user through a user-side smart device accessing a front-end detection module, wherein the user-side smart device is connected to a smart driving vehicle local area network via Ethernet; the user instruction includes an EOL detection request; Step S02: Acquire relevant device information of the smart driving car according to the user instruction; Step S03: Transmitting the relevant device information of the smart driving car to the back-end processing module via HTTPS encrypted communication; Step S04: the back-end processing module encapsulates the user instruction and the relevant device information of the smart driving car through a protocol, and exchanges data with the smart driving car domain controller to complete the offline detection of the smart driving car.

2. The method for detecting the offline status of an intelligent driving vehicle based on Ethernet communication according to claim 1, characterized in that: The step S04 also includes: the back-end processing module analyzes the result of the offline detection of the smart driving car through a protocol and sends it to the user-end smart device.

3. The method for detecting the offline status of an intelligent driving vehicle based on Ethernet communication according to claim 1, characterized in that: The EOL detection request includes an EOL static process, which is used for the static inspection phase of the offline process, including EPS clearing, ADU self-test, actuator test, and sensor factory calibration.

4. The method for detecting the offline status of an intelligent driving vehicle based on Ethernet communication according to claim 1, characterized in that: The EOL detection request includes an EOL dynamic process, which is used in the dynamic inspection phase of the offline process, including GIST dynamic calibration and vehicle chassis testing.

5. The method for detecting offline intelligent driving vehicles based on Ethernet communication according to claim 1, characterized in that: In step S01, the front-end detection module is provided with permission protection, and the permission protection includes a static password, a dynamic password or identity verification.

6. The method for detecting the offline status of an intelligent driving vehicle based on Ethernet communication according to claim 1, characterized in that: The user-side smart device includes a movable smart device and a vehicle-mounted fixed smart device.

7. The method for detecting offline intelligent driving vehicles based on Ethernet communication according to claim 1, characterized in that: In step S01, the user instruction also includes a configuration query or modification request, and the configuration information is output or modified according to the request.

8. The method for detecting the offline status of an intelligent driving vehicle based on Ethernet communication according to claim 1, characterized in that: In step S01, the user instructions also include after-sales service instructions for after-sales activation of automatic calibration, vehicle status query or fault diagnosis.

9. The method for detecting the offline status of an intelligent driving vehicle based on Ethernet communication according to claim 1, characterized in that: The protocols described in step S04 include ROS, UDS protocol, DoIP protocol, and user-defined protocol.

10. An intelligent driving car offline detection system based on Ethernet communication, characterized in that: Front-end access module: receiving a user instruction sent by a user through a user-side smart device, the user-side smart device being connected to the local area network of the smart driving car through Ethernet; the user instruction including an EOL detection request; obtaining relevant device information of the smart driving car according to the user instruction; and transmitting the relevant device information of the smart driving car to the back-end server through HTTPS encrypted communication; Back-end processing module: used to encapsulate the user instructions and the relevant device information of the smart driving car through the protocol, and transmit information with the smart driving car domain controller to complete the offline detection of the smart driving car; The system is deployed in the smart driving car domain controller in SDK mode.

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