Multi-configuration automobile data acquisition system and method based on extended T-BOX

Abstract

The invention discloses a multi-configuration automobile data acquisition system and method based on an extended T-BOX, and the method comprises the steps: obtaining a VIN code of a vehicle through a CAN bus after the extended T-BOX detects that the vehicle is powered on; the cloud management platform matches corresponding vehicle configuration information according to the vehicle VIN code; the extended T-BOX loads a corresponding differential acquisition strategy according to the vehicle configuration information, performs fine adjustment on the differential acquisition strategy according to the real-time working condition, and performs multi-source data acquisition through the extended communication interface module based on the fine-adjusted acquisition strategy; and the extended T-BOX optimizes the fine-tuned acquisition strategy through the edge calculation module according to the acquired multi-source data so as to perform multi-source data acquisition. According to the invention, through interaction between the cloud management platform and the T-BOX extension hardware, intelligence, differentiation and flexibility of automobile data acquisition are realized.

Description

Technical Field

[0001] This invention relates to the field of data acquisition technology, and in particular to a multi-configuration vehicle data acquisition system and method based on an extended T-BOX. Background Technology

[0002] With the rapid development of automotive intelligence and connectivity technologies, in-vehicle data acquisition has become a key technological foundation for realizing functions such as intelligent driving, remote monitoring, and fault diagnosis. Currently, automotive performance data acquisition systems on the market mainly collect vehicle data through the acquisition function in the firmware of in-vehicle data acquisition terminals (T-BOX) or through self-written acquisition programs.

[0003] Traditional fixed data acquisition programs have three core problems: First, the acquired data is fixed and cannot be flexibly changed; second, the data acquisition parsing configuration is fixed and cannot be matched with new vehicle models or changes in bus data; third, expansion is not easy, and new sensors or bus protocols need to be redeveloped.

[0004] With the rapid development of vehicle-to-everything (V2X) hardware and software technologies, traditional fixed data collection solutions are struggling to meet the ever-increasing collection demands. Meanwhile, T-BOX functionality is relatively limited and cannot effectively address the analysis and processing needs of vehicle-side data. Therefore, achieving intelligent, differentiated, and flexible vehicle data collection management has become an urgent problem to solve.

[0005] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention The main objective of this invention is to provide a multi-configuration vehicle data acquisition system and method based on an extended T-BOX, aiming to address the technical challenges of achieving intelligent, differentiated, and flexible vehicle data acquisition.

[0006] To achieve the above objectives, the present invention provides a multi-configuration vehicle data acquisition system based on an extended T-BOX. The extended T-BOX system includes an extended T-BOX and a cloud management platform. The extended T-BOX includes a main control module, an extended communication interface module, and an edge computing module. The extended T-BOX is used to obtain the vehicle VIN code via the CAN bus after detecting that the vehicle is powered on, and to send the vehicle VIN code to the cloud management platform. The cloud management platform is used to match the corresponding vehicle configuration information according to the vehicle VIN code, and send the vehicle configuration information to the extended T-BOX; The extended T-BOX is also used to load the corresponding differentiated acquisition strategy according to the vehicle configuration information, fine-tune the differentiated acquisition strategy according to the real-time operating conditions, and perform multi-source data acquisition through the extended communication interface module based on the fine-tuned acquisition strategy. The extended T-BOX is also used to optimize the fine-tuned acquisition strategy based on the collected multi-source data through the edge computing module, and to collect multi-source data based on the optimized acquisition strategy.

[0007] Optionally, fine-tuning the differentiated acquisition strategy based on real-time operating conditions includes: Determine vehicle speed parameters, environmental parameters, network parameters, and equipment status parameters based on real-time operating conditions; The differentiated data acquisition strategy is fine-tuned based on the vehicle speed parameters, environmental parameters, network parameters, and device status parameters according to preset strategy adjustment rules.

[0008] Optionally, the extended communication interface module includes two high-speed CAN interfaces, an Ethernet interface, a Lin interface, an RS485 interface, and a USB interface; The acquisition strategy based on the fine-tuned acquisition strategy performs multi-source data acquisition through the extended communication interface module, including: The external sensor information is determined based on the fine-tuned acquisition strategy, and at least one connection interface is selected from the two high-speed CAN interfaces, the Ethernet interface, the Lin interface, the RS485 interface, and the USB interface based on the external sensor information. Based on the fine-tuned acquisition strategy, multi-source data is acquired through at least one connection interface.

[0009] Optionally, the edge computing module incorporates an improved decision tree model; The optimization of the fine-tuned acquisition strategy based on the collected multi-source data through the edge computing module includes: The collected multi-source data is input into the improved decision tree model, and the collection strategy parameters are output. The fine-tuned acquisition strategy is optimized based on the acquisition strategy parameters.

[0010] Optionally, the multi-source data acquisition based on the optimized acquisition strategy includes: The optimized acquisition strategy is sent to the cloud management platform for updating, so that the cloud management platform sends the updated acquisition strategy to the main control module; The main control module is used to collect data through the extended communication interface module based on the updated acquisition strategy.

[0011] Optionally, after performing multi-source data acquisition based on the optimized acquisition strategy, the method further includes: Extract the optimal compression algorithm for each type of data from the optimized acquisition strategy; A data transmission strategy is generated based on the optimal compression algorithm corresponding to each type of data, and data transmission is performed according to the data transmission strategy.

[0012] Optionally, the data transmission strategy generated based on the optimal compression algorithm corresponding to various types of data includes: Analyze the collected multi-source data to determine the data transmission level; A data transmission strategy is generated based on the data transmission level and the optimal compression algorithm corresponding to each type of data.

[0013] Optionally, the extended T-BOX also includes a multi-mode communication module, which has multiple built-in communication modes, including cellular network mode, wireless LAN mode and Bluetooth mode. The step of transmitting data according to the data transmission strategy includes: Select a target communication mode from the cellular network mode, the wireless LAN mode, and the Bluetooth mode; According to the data transmission strategy, the multi-mode communication module is controlled to transmit data in accordance with the target communication mode.

[0014] Optionally, the extended T-BOX also includes a storage module; After the multi-source data acquisition based on the optimized acquisition strategy, the process also includes: According to the preset storage rules, the collected multi-source data is stored through the storage module.

[0015] Furthermore, to achieve the above objectives, this invention also proposes a multi-configuration vehicle data acquisition method based on an extended T-BOX, the method comprising the following steps: After detecting that the vehicle is powered on, the extended T-BOX obtains the vehicle VIN code via the CAN bus and sends the vehicle VIN code to the cloud management platform. The cloud management platform matches the corresponding vehicle configuration information based on the vehicle VIN code and sends the vehicle configuration information to the extended T-BOX; The extended T-BOX loads the corresponding differentiated acquisition strategy according to the vehicle configuration information, fine-tunes the differentiated acquisition strategy according to real-time operating conditions, and performs multi-source data acquisition through the extended communication interface module based on the fine-tuned acquisition strategy. The extended T-BOX optimizes the fine-tuned acquisition strategy based on the collected multi-source data through the edge computing module, and performs multi-source data acquisition based on the optimized acquisition strategy.

[0016] Furthermore, to achieve the above objectives, the present invention also proposes a multi-configuration vehicle data acquisition device based on an extended T-BOX. The device includes: a memory, a processor, and a multi-configuration vehicle data acquisition program based on an extended T-BOX stored in the memory and executable on the processor. The multi-configuration vehicle data acquisition program based on an extended T-BOX is configured to implement the steps of the multi-configuration vehicle data acquisition method based on an extended T-BOX as described above.

[0017] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing a multi-configuration vehicle data acquisition program based on an extended T-BOX. When the multi-configuration vehicle data acquisition program based on an extended T-BOX is executed by a processor, it implements the steps of the multi-configuration vehicle data acquisition method based on an extended T-BOX as described above.

[0018] This invention discloses a multi-configuration vehicle data acquisition system based on an extended T-BOX. The system includes an extended T-BOX and a cloud management platform. The extended T-BOX comprises a main control module, an extended communication interface module, and an edge computing module. First, upon detecting vehicle power-on, the extended T-BOX acquires the vehicle's VIN code via the CAN bus and sends it to the cloud management platform. Then, the cloud management platform matches the corresponding vehicle configuration information based on the VIN code and sends this information back to the extended T-BOX. Next, the extended T-BOX loads a corresponding differentiated acquisition strategy based on the vehicle configuration information and fine-tunes the strategy according to real-time operating conditions. Based on the fine-tuned strategy, it performs multi-source data acquisition through the extended communication interface module. Finally, the extended T-BOX optimizes the fine-tuned acquisition strategy using the edge computing module based on the acquired multi-source data and performs multi-source data acquisition based on the optimized strategy. This invention achieves intelligent, differentiated, and flexible vehicle data acquisition through data interaction between the cloud management platform and the T-BOX extended hardware, employing differentiated acquisition strategies for vehicles with different configurations. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the structure of a multi-configuration automotive data acquisition device based on an extended T-BOX, which is part of the hardware operating environment involved in the embodiments of the present invention. Figure 2 This is a structural block diagram of the first embodiment of the multi-configuration vehicle data acquisition system based on the extended T-BOX of the present invention; Figure 3 This is a flowchart illustrating the first embodiment of the multi-configuration vehicle data acquisition method based on extended T-BOX of the present invention.

[0020] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0022] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a multi-configuration vehicle data acquisition device based on an extended T-BOX, which is part of the hardware operating environment of the embodiment of the present invention.

[0023] like Figure 1 As shown, the multi-configuration automotive data acquisition device based on the extended T-BOX may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be high-speed random access memory (RAM) or stable non-volatile memory (NVM), such as a disk storage device. The memory 1005 may also optionally be a storage system independent of the aforementioned processor 1001.

[0024] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on multi-configuration automotive data acquisition equipment based on extended T-BOX, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0025] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and a multi-configuration vehicle data acquisition program based on an extended T-BOX.

[0026] exist Figure 1In the multi-configuration vehicle data acquisition device based on extended T-BOX shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and memory 1005 in the multi-configuration vehicle data acquisition device based on extended T-BOX of the present invention can be set in the multi-configuration vehicle data acquisition device based on extended T-BOX. The multi-configuration vehicle data acquisition device based on extended T-BOX calls the multi-configuration vehicle data acquisition program based on extended T-BOX stored in memory 1005 through processor 1001 and executes the multi-configuration vehicle data acquisition method based on extended T-BOX provided in the embodiment of the present invention.

[0027] This invention provides a multi-configuration vehicle data acquisition system based on an extended T-BOX, referring to... Figure 2 , Figure 2 This is a structural block diagram of the first embodiment of the multi-configuration vehicle data acquisition system based on the extended T-BOX of the present invention.

[0028] In this embodiment, the multi-configuration vehicle data acquisition system based on the extended T-BOX includes an extended T-BOX 2001 and a cloud management platform 2002. The extended T-BOX includes a main control module, an extended communication interface module, an edge computing module, a multi-mode communication module, and a storage module. It should be noted that the main control module, extended communication interface module, edge computing module, multi-mode communication module, and storage module are all independent modules.

[0029] The main control module includes a main processor (MPU) and a coprocessor (MCU). The MPU is responsible for complex data processing and communication functions, while the MCU is responsible for real-time data acquisition and hardware control. The main processor (MPU) is connected to the edge computing module, the multi-mode communication module, and the storage module through standardized interfaces. The coprocessor (MCU) is connected to the extended communication interface module, which in turn connects to external sensors through interfaces.

[0030] The extended communication interface module breaks through the limitations of the traditional T-BOX's single CAN interface. It includes two high-speed CAN interfaces, an Ethernet interface, a LIN interface, an RS485 interface, and a USB interface. The two high-speed CAN interfaces support CAN 2.0A, CAN 2.0B, and CAN FD protocols, covering the powertrain, chassis, and body CAN networks. The Ethernet interface is compatible with automotive Ethernet protocols, collecting data from the intelligent driving domain. Through the interfaces within the extended communication interface module, different types of sensors such as cameras, LiDAR, and millimeter-wave radar can be directly connected, meeting multi-source data acquisition needs.

[0031] The multi-mode communication module has multiple built-in communication modes, including cellular network mode (i.e., 4G / 5G network), wireless LAN mode (i.e., WiFi) and Bluetooth mode.

[0032] The storage module is equipped with 128GB of eMMC storage, supporting local data caching and offline storage to alleviate the pressure of real-time transmission.

[0033] The extended T-BOX2001 is used to obtain the vehicle VIN code via the CAN bus after detecting that the vehicle is powered on, and send the vehicle VIN code to the cloud management platform 2002.

[0034] The cloud management platform 2002 is used to match the corresponding vehicle configuration information according to the vehicle VIN code and send the vehicle configuration information to the extended T-BOX 2001.

[0035] In practice, the cloud management platform extracts a preset configuration identifier code from the vehicle's VIN code; based on the preset configuration identifier code, it matches the corresponding vehicle configuration information from the cloud configuration database. The identifier code, vehicle model configuration level, and vehicle configuration information in the cloud configuration database correspond one-to-one.

[0036] It should be understood that the preset bit configuration identifier code can be customized by the user, for example, the 10th to 17th bits of the VIN code can be configured as an identifier code.

[0037] In the specific implementation, the configuration identification code of the 10th to 17th digits of the VIN code is extracted, and the corresponding vehicle configuration level of the 12th to 14th digits is obtained from the configuration identification code of the 10th to 17th digits (such as "L35" representing the low-end vision solution and "H68" representing the high-end LiDAR solution). The vehicle configuration level is compared with the cloud configuration database (i.e., a mapping table that stores the full vehicle VIN identification code - vehicle configuration level - vehicle configuration information) to determine the vehicle configuration information.

[0038] Vehicle configuration information includes hardware configuration (sensor type and quantity, computing platform specifications, etc.), software configuration (intelligent driving function level, algorithm version, etc.), and default data collection strategy template.

[0039] The extended T-BOX2001 is also used to load a corresponding differentiated acquisition strategy according to the vehicle configuration information, fine-tune the differentiated acquisition strategy according to real-time operating conditions, and control the main control module to perform multi-source data acquisition through the extended communication interface module based on the fine-tuned acquisition strategy.

[0040] Furthermore, the process of fine-tuning the differentiated acquisition strategy based on real-time operating conditions is as follows: determine vehicle speed parameters, environmental parameters, network parameters, and equipment status parameters based on real-time operating conditions; and fine-tune the differentiated acquisition strategy according to preset strategy adjustment rules based on vehicle speed parameters, environmental parameters, network parameters, and equipment status parameters.

[0041] The preset strategy adjustment rules allow users to customize settings such as sensor acquisition frequency, acquisition method, or transmission method.

[0042] In the specific implementation, the T-BOX is extended to collect four types of core operating condition parameters in real time, triggering corresponding policy fine-tuning rules: ① Vehicle speed parameters: When the vehicle speed is >100km / h (high-speed conditions), the collection frequency of LiDAR and millimeter-wave radar is increased from the default 10Hz to 20Hz; when the vehicle speed is <5km / h (low-speed congestion / parking conditions), the collection frequency is reduced to 5Hz; ② Environmental parameters: At night or in rainy or snowy weather, the collection priority of camera data is increased, while the collection frequency is reduced (to avoid invalid data under low light / severe weather conditions); ③ Network parameters: When the 5G network signal strength is <-100dBm (signal weakness), the collection of non-critical data (such as entertainment system status data) is reduced, and only safety-related data is retained; ④ Device status parameters: When the remaining local storage space of the extended T-BOX is <10%, it switches to the "collect only, do not cache locally" mode, prioritizing the transmission of critical data.

[0043] All fine-tuning is achieved through an engine that adjusts rules based on preset strategies, with the fine-tuning range not exceeding 50% of the default strategy to ensure strategy stability.

[0044] The processing method for multi-source data acquisition based on the fine-tuned acquisition strategy through the extended communication interface module is as follows: determine the external sensor information to be connected according to the fine-tuned acquisition strategy, and select at least one connection interface from two high-speed CAN interfaces, Ethernet interface, Lin interface, RS485 interface and USB interface according to the external sensor information to be connected; and perform multi-source data acquisition through at least one connection interface based on the fine-tuned acquisition strategy.

[0045] It should also be noted that for CAN bus data, the system supports protocols such as CAN 2.0A, CAN 2.0B, and CAN FD, enabling the acquisition of data from various ECUs, including those in the engine, transmission, chassis, and body. For Ethernet data, the system supports the in-vehicle Ethernet protocol, allowing the acquisition of data from devices such as the intelligent driving domain controller and central computing platform. For other protocol data, such as LIN bus and FlexRay, the system acquires data through the corresponding interfaces. All acquired data is timestamped and includes a data source identifier for easy subsequent processing and analysis.

[0046] The extended T-BOX2001 is also used to optimize the fine-tuned acquisition strategy based on the acquired multi-source data through the edge computing module, and to acquire multi-source data based on the optimized acquisition strategy.

[0047] It should be noted that the coprocessor sends the collected multi-source data to the main processor, and the main processor forwards the collected multi-source data to the edge computing module, which has a built-in improved decision tree model.

[0048] The process of building an improved decision tree model: (1) Data preparation: Collect historical vehicle operation data (including vehicle speed, braking status, steering angle, sensor type, acquisition frequency, network bandwidth usage, data storage, etc.) and real-time operating data (including current vehicle speed, road conditions, weather, lighting, network signal strength, etc.). After removing abnormal data (such as sensor failure data, invalid data when the network is interrupted), divide the data into training set and test set in a 7:3 ratio.

[0049] (2) Feature engineering: Extract core features, including operating condition features (vehicle speed level, road condition type: urban road / highway / congestion / parking lot, environmental parameters: sunny / rainy / snowy / night / daytime), data features (data type, data size, real-time requirements), resource features (network bandwidth, remaining local storage space), and business features (currently enabled intelligent driving function level).

[0050] (3) Model selection and training: A lightweight improved decision tree model (CART tree improved version) was selected to adapt to the limited computing resources on the vehicle. The model was trained with the training set with the "collection strategy parameters (collection frequency, data type selection, compression algorithm selection)" as the output target, and the model accuracy was verified with the test set to ensure that the model prediction accuracy was ≥95%.

[0051] (4) Model deployment: The trained model is embedded into the edge computing module of the extended T-BOX, supporting OTA remote update of model parameters.

[0052] It should also be noted that the model employs a "pruning optimization + real-time update" improvement strategy. Pruning optimization involves removing branches in the decision tree that have minimal impact on the prediction results, reducing the model's computational load and improving vehicle-side operating speed. Real-time updates involve incrementally training the model every 24 hours of collected data to correct model parameters and adapt to different users' driving habits and road condition changes. Compared to traditional decision trees, this improved algorithm offers a 60% increase in computational efficiency and a 40% improvement in adaptability.

[0053] Furthermore, the collected multi-source data is sent to the improved decision tree model, which outputs the data collection strategy parameters; the fine-tuned data collection strategy is then optimized based on these parameters.

[0054] The processing method for multi-source data acquisition based on the optimized acquisition strategy is as follows: The optimized acquisition strategy is sent to the cloud management platform for updating, so that the cloud management platform sends the updated acquisition strategy to the main control module of the extended T-BOX via OTA; The main control module is used to acquire data through the extended communication interface module based on the updated acquisition strategy, and then extracts the optimal compression algorithm corresponding to each type of data from the optimized acquisition strategy; The acquired multi-source data is analyzed to determine the data transmission level; A data transmission strategy is generated according to the data transmission level and the optimal compression algorithm corresponding to each type of data, and data transmission is carried out according to the data transmission strategy.

[0055] Furthermore, the extended T-BOX also includes a multi-mode communication module, which has multiple built-in communication modes, including cellular network mode, wireless LAN mode, and Bluetooth mode. The data transmission processing method according to the data transmission strategy is to select the target communication mode from the cellular network mode, wireless LAN mode, and Bluetooth mode. The multi-mode communication module is controlled to transmit data according to the target communication mode according to the data transmission strategy.

[0056] The extended T-BOX also includes a storage module; the storage module can store the collected multi-source data according to preset storage rules (user-defined storage rules).

[0057] The data types are LiDAR data, vision data, and CAN bus data.

[0058] For example, the system uses a voxel compression algorithm for LiDAR data; a content-based adaptive compression algorithm for visual data; and a differential coding compression algorithm for CAN bus data. The processed data stream size can be reduced by 70%-90%, effectively lowering the transmission bandwidth requirements.

[0059] It should be noted that the voxel compression algorithm (applicable to LiDAR data) is as follows: Steps: ① Grid division: Divide the 3D spatial point cloud (composed of a large number of three-dimensional coordinate points) collected by the LiDAR into multiple small cubic grids of the same size. These small grids are called "voxels"; ② Feature preservation: For all point cloud data in each voxel, calculate a representative point (e.g., take the average coordinates of all points); ③ Redundancy removal: Only retain the representative point of each voxel and delete other duplicate or similar points in the voxel.

[0060] Content-based adaptive compression algorithms (suitable for visual data, such as camera images): Steps: ① Content analysis: Identify the importance of different regions in the image (e.g., road markings, pedestrians, and vehicles are important regions, while the sky and ground are secondary regions); ② Differentiated compression: Use a low compression rate for important regions (preserving more details) and a high compression rate for secondary regions (appropriately discarding details); ③ Dynamic adjustment: Automatically adjust compression parameters based on image sharpness and lighting conditions.

[0061] Differential coding compression algorithm (applicable to CAN bus data): Steps: ① Record the reference: Save the first CAN data frame (complete raw data) as the reference; ② Calculate the difference: For each subsequent CAN data frame, only record the difference value between it and the previous data frame (for example, if the previous frame data is 100 and the current frame is 102, only record "+2"); ③ Restore the data: Once the receiving end obtains the reference value and the difference value, it can reverse the process to calculate the complete raw data.

[0062] The processed data stream size can be reduced by 70%-90%, effectively lowering transmission bandwidth requirements. Sensitive data is encrypted and anonymized during the security processing phase. Processed data can be stored locally, transmitted in real-time, or cached according to data transmission strategies, effectively reducing network bandwidth requirements and cloud processing pressure.

[0063] In practice, data transmission levels are categorized into high, medium, and low levels. High levels correspond to data with high real-time requirements, medium levels correspond to routine operational data, and low levels correspond to important but non-real-time data.

[0064] Highly real-time data: latency requirement <100ms, importance level "extremely high", business purpose "safety warning / emergency control", the basis for judgment is that the corresponding signal of the data comes from safety-related ECUs (such as brake ECU, airbag ECU, intelligent driving warning module); Regular operation data: latency requirement 1-10s, importance level "medium", business purpose "status monitoring / routine analysis", the basis for judgment is that the corresponding signal of the data is the normal operating status of the vehicle (such as vehicle speed, engine speed, fuel level), and there is no need for emergency processing; Important but not real-time data: latency requirement >10s, importance level "high", business purpose "fault tracing / compliance archiving", the basis for judgment is that the data needs to be stored for a long time for subsequent fault analysis or to meet regulatory requirements (such as driving records need to be stored for 6 months), but does not require real-time processing.

[0065] For data with high real-time requirements (such as emergency braking signals and collision warning data), the system adopts a real-time transmission mode, directly uploading to the cloud via the 5G network; for routine operational data, the system adopts a cached transmission mode, uploading in batches when network conditions are good; for important but non-real-time data (such as driving records and fault logs), the system adopts a local storage + cloud backup mode. Encryption protocols are used during transmission to ensure data security.

[0066] The storage policy supports cyclic storage and incremental storage, and can automatically adjust the storage policy based on the storage space available.

[0067] It should also be noted that the cloud platform also provides data management, analysis, and visualization functions, supporting users to query and analyze historical data and providing data support for business decisions.

[0068] In this embodiment, after the extended T-BOX detects that the vehicle is powered on, it first obtains the vehicle VIN code via the CAN bus and sends the vehicle VIN code to the cloud management platform. Then, the cloud management platform matches the corresponding vehicle configuration information based on the vehicle VIN code and sends the vehicle configuration information to the extended T-BOX. After that, the extended T-BOX loads the corresponding differentiated acquisition strategy based on the vehicle configuration information, and fine-tunes the differentiated acquisition strategy according to the real-time operating conditions. Based on the fine-tuned acquisition strategy, it performs multi-source data acquisition through the extended communication interface module. Finally, the extended T-BOX optimizes the fine-tuned acquisition strategy based on the acquired multi-source data through the edge computing module, and performs multi-source data acquisition based on the optimized acquisition strategy. This invention extends the flexible data acquisition technology of T-BOX, enabling the system to support multiple vehicle network protocols, including CAN, ETH, and LIN, breaking through the limitation of traditional T-BOX which can only acquire CAN signals. This flexibility allows the same system to be adapted to all models from low-end to high-end, significantly reducing R&D and maintenance costs. Through data interaction between the cloud management platform and the T-BOX extension hardware, the system can intelligently identify vehicle configurations and automatically adjust acquisition strategies. Intelligent strategy optimization makes data acquisition more accurate and efficient.

[0069] Reference Figure 3 , Figure 3 This is a flowchart illustrating the first embodiment of the multi-configuration vehicle data acquisition method based on extended T-BOX of the present invention.

[0070] like Figure 3 As shown, the multi-configuration vehicle data acquisition method based on extended T-BOX proposed in this embodiment of the invention includes: S10, after the extended T-BOX detects that the vehicle is powered on, it obtains the vehicle VIN code through the CAN bus and sends the vehicle VIN code to the cloud management platform; S20, the cloud management platform matches the corresponding vehicle configuration information according to the vehicle VIN code, and sends the vehicle configuration information to the extended T-BOX; S30, the extended T-BOX loads the corresponding differentiated acquisition strategy according to the vehicle configuration information, fine-tunes the differentiated acquisition strategy according to the real-time operating conditions, and performs multi-source data acquisition through the extended communication interface module based on the fine-tuned acquisition strategy. S40, the extended T-BOX optimizes the fine-tuned acquisition strategy based on the collected multi-source data through the edge computing module, and performs multi-source data acquisition based on the optimized acquisition strategy.

[0071] Other embodiments or specific implementations of the multi-configuration vehicle data acquisition method based on extended T-BOX of the present invention can be referred to the above-described method embodiments, and will not be repeated here.

[0072] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0073] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0074] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0075] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A multi-configuration vehicle data acquisition system based on an extended T-BOX, characterized in that, The system includes an extended T-BOX and a cloud management platform. The extended T-BOX includes a main control module, an extended communication interface module, and an edge computing module. The extended T-BOX is used to obtain the vehicle VIN code via the CAN bus after detecting that the vehicle is powered on, and to send the vehicle VIN code to the cloud management platform. The cloud management platform is used to match the corresponding vehicle configuration information according to the vehicle VIN code, and send the vehicle configuration information to the extended T-BOX; The extended T-BOX is also used to load a corresponding differentiated acquisition strategy according to the vehicle configuration information, fine-tune the differentiated acquisition strategy according to real-time operating conditions, and control the main control module to perform multi-source data acquisition through the extended communication interface module based on the fine-tuned acquisition strategy. The extended T-BOX is also used to optimize the fine-tuned acquisition strategy based on the collected multi-source data through the edge computing module, and to collect multi-source data based on the optimized acquisition strategy.

2. The system as described in claim 1, characterized in that, The step of fine-tuning the differentiated data acquisition strategy based on real-time operating conditions includes: Determine vehicle speed parameters, environmental parameters, network parameters, and equipment status parameters based on real-time operating conditions; The differentiated data acquisition strategy is fine-tuned based on the vehicle speed parameters, environmental parameters, network parameters, and device status parameters according to preset strategy adjustment rules.

3. The system as described in claim 1, characterized in that, The extended communication interface module includes two high-speed CAN interfaces, an Ethernet interface, a Lin interface, an RS485 interface, and a USB interface. The acquisition strategy based on the fine-tuned acquisition method performs multi-source data acquisition through the extended communication interface module, including: The external sensor information is determined based on the fine-tuned acquisition strategy, and at least one connection interface is selected from the two high-speed CAN interfaces, the Ethernet interface, the Lin interface, the RS485 interface, and the USB interface based on the external sensor information. Based on the fine-tuned acquisition strategy, multi-source data is acquired through at least one connection interface.

4. The system as described in claim 1, characterized in that, The edge computing module incorporates an improved decision tree model; The optimization of the fine-tuned acquisition strategy based on the collected multi-source data through the edge computing module includes: The collected multi-source data is input into the improved decision tree model, and the collection strategy parameters are output. The fine-tuned acquisition strategy is optimized based on the acquisition strategy parameters.

5. The system as described in claim 1, characterized in that, The multi-source data acquisition based on the optimized acquisition strategy includes: The optimized acquisition strategy is sent to the cloud management platform for updating, so that the cloud management platform sends the updated acquisition strategy to the main control module; The main control module is used to collect data through the extended communication interface module based on the updated acquisition strategy.

6. The system as described in claim 1, characterized in that, After the multi-source data acquisition based on the optimized acquisition strategy, the process also includes: Extract the optimal compression algorithm for each type of data from the optimized acquisition strategy; A data transmission strategy is generated based on the optimal compression algorithm corresponding to each type of data, and data transmission is performed according to the data transmission strategy.

7. The system as described in claim 6, characterized in that, The data transmission strategy generated based on the optimal compression algorithm corresponding to various types of data includes: Analyze the collected multi-source data to determine the data transmission level; A data transmission strategy is generated based on the data transmission level and the optimal compression algorithm corresponding to each type of data.

8. The system as described in claim 6, characterized in that, The extended T-BOX also includes a multi-mode communication module, which has multiple built-in communication modes, including cellular network mode, wireless LAN mode and Bluetooth mode. The step of transmitting data according to the data transmission strategy includes: Select a target communication mode from the cellular network mode, the wireless LAN mode, and the Bluetooth mode; According to the data transmission strategy, the multi-mode communication module is controlled to transmit data in accordance with the target communication mode.

9. The system as described in claim 1, characterized in that, The extended T-BOX also includes a storage module; After the multi-source data acquisition based on the optimized acquisition strategy, the process also includes: According to the preset storage rules, the collected multi-source data is stored through the storage module.

10. A multi-configuration vehicle data acquisition method based on extended T-BOX, characterized in that, The method includes the following steps: After detecting that the vehicle is powered on, the extended T-BOX obtains the vehicle VIN code via the CAN bus and sends the vehicle VIN code to the cloud management platform. The cloud management platform matches the corresponding vehicle configuration information based on the vehicle VIN code and sends the vehicle configuration information to the extended T-BOX; The extended T-BOX loads the corresponding differentiated acquisition strategy according to the vehicle configuration information, fine-tunes the differentiated acquisition strategy according to real-time operating conditions, and performs multi-source data acquisition through the extended communication interface module based on the fine-tuned acquisition strategy. The extended T-BOX optimizes the fine-tuned acquisition strategy based on the collected multi-source data through the edge computing module, and performs multi-source data acquisition based on the optimized acquisition strategy.

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