System and method for virtual truck and physical component linkage in truck intelligent driving cabin control screen

Abstract

The application discloses a truck intelligent driving cabin central control screen virtual truck and entity component linkage system and method, relates to the technical field of vehicle control, and the linkage system comprises a high-precision virtual truck modeling module, a multi-dimensional data acquisition and transmission module, a virtual entity bidirectional linkage control module, an intelligent fault analysis and early warning module and a driving cabin adaptation optimization module. The application constructs a 1:1 proportion high-precision virtual truck model based on the three-dimensional design drawing of the whole vehicle of the target truck during actual operation. The application realizes a breakthrough innovation of the virtual linkage technology of the truck intelligent driving cabin, fills the technical blank of the precise linkage of virtual entity components in the field of commercial vehicles, manages, visualizes and stores the truck operation data and the corresponding linkage analysis results, helps to realize the unified management of the multi-truck linkage system through the cloud platform, and improves the intelligent management level of the truck fleet.

Description

Technical Field

[0001] This invention relates to the field of vehicle control technology, specifically to a system and method for linking a virtual truck with physical components in the central control screen of a truck's intelligent driver's cab. Background Technology

[0002] Currently, most truck cab control systems primarily focus on single data display and basic function operation. While some high-end trucks feature a central control screen with a visual interface, this only displays parameters of physical truck components and fails to achieve precise linkage between the virtual model and the physical components. As large commercial vehicles, trucks have numerous and widely distributed core components such as chassis, engine, brakes, hydraulics, and tires. Drivers find it difficult to comprehensively and intuitively grasp the real-time operating status of the vehicle through traditional instruments and fragmented data. Furthermore, troubleshooting requires offline testing with specialized equipment, resulting in low response efficiency.

[0003] In existing commercial vehicle intelligent driving cabin technologies, virtual simulation is mostly used in truck driver training and has not been implemented in actual driving scenarios. The monitoring and control of physical components are still in a state of "data separation and independent operation". There is a lack of two-way interactive linkage mechanism between the central control screen and physical components, which cannot meet the actual needs of real-time monitoring, precise control, rapid troubleshooting and intelligent early warning in long-distance truck transportation. The improvement of truck driving intelligence, safety and convenience is limited.

[0004] The above-mentioned problems still mainly have the following shortcomings: 1. Poor visualization: Traditional central control systems only display component parameters with numbers and icons, without a proportional virtual truck model. Drivers cannot intuitively perceive the location, operating status, and fault points of components, resulting in high information comprehension costs.

[0005] 2. Lack of two-way linkage mechanism: It can only realize one-way data transmission from physical components to the central control screen, and cannot accurately control physical components through the virtual model of the central control screen. The operation process is cumbersome and it is difficult to adapt to the complex operation requirements of trucks.

[0006] 3. Inefficient troubleshooting: When physical components malfunction, the central control system only displays fault codes, without virtual model fault location or component linkage anomaly analysis. Drivers need professional personnel to conduct on-site inspections, which delays transportation time.

[0007] 4. Weak component coordination: The operating data of each core component of the truck are independent of each other. The central control system lacks the collaborative analysis function of virtual model and cannot predict the linkage failure between components (such as abnormal coordination between the braking system and the hydraulic system), which poses a driving safety hazard.

[0008] 5. Insufficient adaptability: Existing in-vehicle virtual linkage technologies are mostly designed for passenger cars and have not been optimized for the large size, heavy load and multiple components of trucks. The accuracy of the virtual model and the real-time data transmission cannot meet the needs of truck driving, thus causing many inconveniences.

[0009] Therefore, this invention requires the design of a system and method for linking the virtual truck with physical components in the central control screen of a smart truck driver's cab to solve the aforementioned problems. Summary of the Invention

[0010] The purpose of this invention is to provide a system and method for linking a virtual truck with physical components in the central control screen of a smart truck driver's cabin, thereby solving the problems mentioned in the background art.

[0011] To address the above problems, the present invention provides a technical solution: The truck intelligent cab central control screen virtual truck and physical component linkage system includes a high-precision virtual truck modeling module, a multi-dimensional data acquisition and transmission module, a virtual entity bidirectional linkage control module, an intelligent fault analysis and early warning module, and a cab adaptation and optimization module. These modules are all installed on the truck's central control screen and the truck body. Real-time data communication and collaborative operation between the modules are maintained via a dual-link system of onboard CAN bus and 5G wireless transmission. Operators can access the linkage system by logging into the high-precision virtual truck modeling module and view the real-time operating data of each module.

[0012] In a preferred embodiment of the present invention, the high-precision virtual truck modeling module is used to construct a 1:1 scale high-precision virtual truck model based on the three-dimensional design drawings of the target truck. The virtual truck model completely restores all core components and auxiliary structures of the truck, including the cab, engine, chassis, braking system, hydraulic system, tires, fuel tank, and exhaust gas treatment system. Each virtual component is independently coded and its attributes are bound, and the model supports multi-view switching, zooming, and rotation operations on the central control screen. The multi-dimensional data acquisition and transmission module is used to deploy dedicated sensors on each core component of the physical truck to collect the operating parameter data of each core component in real time. The collected data is transmitted to the central control screen through a dual-link method of vehicle CAN bus and 5G wireless transmission, and the data transmission delay is controlled within 100ms. The virtual entity bidirectional linkage control module is used to construct the mapping logic between virtual model operation and physical component control, so as to realize bidirectional interaction between the virtual truck model on the central control screen and the physical truck components, including data uplink synchronization and command downlink control. The intelligent fault analysis and early warning module is used to embed AI fault analysis algorithms. When the operating data of physical components exceeds the threshold or anomalies occur, the module locates the fault point on the virtual model, analyzes the linkage effect, issues a graded early warning, and provides fault handling guidance. The cab adaptation and optimization module is used to comprehensively adapt and optimize the virtual model's interface display, operation method, key monitoring points, and offline transmission by combining the spatial characteristics of the truck cab, the driver's operating perspective, and the truck's driving conditions.

[0013] The method for linking the virtual truck with physical components in the central control screen of the intelligent truck driver's cabin includes the following specific steps: S1. Construct a high-precision virtual truck model and load it onto the central control screen. Based on the 3D design drawings of the target truck, use 3D modeling technology to construct a 1:1 scale high-precision virtual truck model. Encode and bind the attributes of each virtual component independently. Load the virtual truck model onto the central control screen and support multi-view switching, scaling and rotation operations. S2. Real-time acquisition of operating parameter data of each core component of the physical truck and transmission to the central control screen. The operating parameter data is collected by sensors deployed on each core component. After filtering, noise reduction and calibration preprocessing, the data is transmitted to the central control screen through a dual-link method of CAN bus and 5G wireless transmission. After receiving the data, the central control screen synchronously updates the operating status display of the corresponding virtual component in the virtual truck model. S3. Through the virtual model of the central control screen, the physical components are controlled in two directions and fault warnings are given. The operation commands are transmitted to the control unit of the physical component via the CAN bus and executed. At the same time, the AI ​​fault analysis algorithm is started to analyze the operating data. When the data exceeds the threshold or an anomaly occurs, the fault point is located on the virtual model, the linkage effect is analyzed, a graded warning is issued and a troubleshooting guide is generated.

[0014] The beneficial effects of this invention are as follows: By setting up a high-precision virtual truck modeling module, a multi-dimensional data acquisition and transmission module, a virtual entity bidirectional linkage control module, an intelligent fault analysis and early warning module, and a driver's cab adaptation and optimization module, a complete truck virtual entity linkage system is constructed. In actual operation, a 1:1 scale high-precision virtual truck model is constructed based on the target truck's full-vehicle 3D design drawings, and each virtual component is independently coded and attribute-bound. Operating parameter data is collected in real time by dedicated sensors deployed on each core component. After filtering, noise reduction, and calibration preprocessing, the data is transmitted to the central control screen via a dual-link method of CAN bus and 5G wireless transmission. After receiving the data, the central control screen synchronously updates the operating status display of the corresponding virtual component in the virtual truck model. It responds to the driver's touch operation or physical button operation on the virtual component, realizing precise control of the physical component with the virtual model as the operation entry point. Through AI fault analysis algorithms, it achieves virtual precise location of fault points, linkage impact analysis, and graded early warning. The system provides on-site troubleshooting guidance; automatically adjusts the monitoring focus of the virtual model according to different truck operating conditions and focuses on display; automatically switches to CAN bus local transmission when 5G signal is interrupted; transforms the abstract data of physical components into intuitive virtual visualization effects through 1:1 high-precision virtual truck modeling technology; breaks through the limitation of unidirectional data transmission in existing technologies through a two-way linkage mechanism of "data uplink + command downlink"; upgrades from "passive fault handling" to "active intelligent early warning" through AI fault analysis algorithms; and solves the compatibility difference problem between virtual linkage technology for commercial vehicles and passenger vehicles through dedicated driver's cab adaptation and optimization technology. This invention achieves a breakthrough innovation in truck intelligent driver's cab virtual linkage technology, fills the technical gap in precise linkage of virtual physical components in the commercial vehicle field, manages, visualizes, and stores truck operation data and corresponding linkage analysis results, and helps to achieve unified management of multi-vehicle linkage systems through a cloud platform, improving the level of intelligent management of truck fleets. Attached Figure Description

[0015] For ease of explanation, the present invention will be described in detail below with reference to specific embodiments and accompanying drawings.

[0016] Figure 1 This is a topological diagram of the overall structure of the truck intelligent cab central control screen virtual truck and physical component linkage system and method of the present invention; Figure 2 This is an overall flowchart of the truck intelligent cab central control screen virtual truck and physical component linkage system and method of the present invention; Figure 3 This is a flowchart illustrating the overall process of the truck intelligent cab central control screen virtual truck and physical component linkage system and method of the present invention; Figure 4 This is a flowchart of sub-step S1 of the truck intelligent cab central control screen virtual truck and physical component linkage system and method of the present invention; Figure 5 This is a flowchart of sub-step S2 of the present invention, which describes the linkage system and method between the virtual truck and physical components in the central control screen of the intelligent truck driver's cab. Detailed Implementation

[0017] like Figure 1 , Figure 2 , Figure 3 , Figure 4 and Figure 5 As shown, the specific implementation adopts the following technical solution: The truck intelligent cab central control screen virtual truck and physical component linkage system includes a high-precision virtual truck modeling module, a multi-dimensional data acquisition and transmission module, a virtual entity bidirectional linkage control module, an intelligent fault analysis and early warning module, and a cab adaptation and optimization module. These modules are all installed on the truck's central control screen and the truck body. Real-time data communication and collaborative operation between the modules are maintained via a dual-link system of onboard CAN bus and 5G wireless transmission. Operators can access the linkage system by logging into the high-precision virtual truck modeling module and view the real-time operating data of each module.

[0018] Data Acquisition and Modeling S101. The high-precision virtual truck modeling module is used to construct a 1:1 scale high-precision virtual truck model based on the three-dimensional design drawings of the target truck. The virtual truck model completely restores all core components and auxiliary structures of the truck, including the cab, engine, chassis, braking system, hydraulic system, tires, fuel tank, and exhaust gas treatment system. Each virtual component is independently coded and its attributes are bound. The module supports multi-view switching, zooming, and rotation operations on the central control screen.

[0019] S102. The high-precision virtual truck modeling module includes a 3D model building unit, an independent coding and binding unit, and a view interaction unit, and the output ends of the 3D model building unit and the independent coding and binding unit are connected to the input end of the view interaction unit.

[0020] S103, Intelligent Linkage System Control 3D Model Construction Unit: Based on the target truck's overall 3D design drawings, the unit uses 3D modeling technology to construct a 1:1 scale high-precision virtual truck model. The virtual truck model fully restores all core components and auxiliary structures of the truck, including the cab, engine, chassis, braking system, hydraulic system, tires, fuel tank, and exhaust gas treatment system.

[0021] S104. The intelligent linkage system control independent coding and binding unit independently codes and binds attributes to each virtual component. The bound attributes include the component's physical parameters, operating thresholds, linkage logic, and fault characteristics, so that the attributes of the virtual component correspond one-to-one with the attributes of the physical component.

[0022] S105, the intelligent linkage system control perspective interaction unit supports multi-view switching, zooming and rotation operations on the central control screen. The multi-view switching includes whole vehicle perspective, component local perspective and fault point focus perspective.

[0023] S106. The multi-dimensional data acquisition and transmission module is used to deploy dedicated sensors on each core component of the physical truck to collect the operating parameter data of each core component in real time. The collected data is transmitted to the central control screen through a dual-link method of vehicle CAN bus and 5G wireless transmission, and the data transmission delay is controlled within 100ms.

[0024] S107. The multi-dimensional data acquisition and transmission module includes a sensor deployment unit, a data preprocessing unit, and a dual-link transmission unit, maintaining a communication connection between the output end of the sensor deployment unit and the input end of the data preprocessing unit, and maintaining a bidirectional communication connection between the data preprocessing unit and the dual-link transmission unit.

[0025] S108, the intelligent linkage system control sensor deployment unit deploys a dedicated sensor group on each core component of the physical truck. The dedicated sensor group is selected from one or more of pressure sensors, speed sensors, temperature sensors, displacement sensors and vibration sensors, and all sensors have undergone waterproof, shockproof and high temperature resistance optimization treatment.

[0026] S109, the intelligent linkage system control data preprocessing unit filters, reduces noise, and calibrates the raw operating parameter data collected by the sensors, eliminating invalid data.

[0027] The S110 intelligent linkage system control dual-link transmission unit transmits pre-processed operating parameter data to the virtual truck modeling module on the central control screen through a dual-link method of vehicle CAN bus and 5G wireless transmission. The data transmission delay is controlled within 100ms, and it automatically switches to CAN bus local transmission when the 5G signal is interrupted.

[0028] Two-way linkage control S201. The virtual entity bidirectional linkage control module is used to construct the mapping logic between virtual model operation and physical component control, and realize bidirectional interaction between the virtual truck model on the central control screen and the physical truck component, including data uplink synchronization and command downlink control.

[0029] S202, the virtual entity bidirectional linkage control module includes a mapping logic construction unit, a virtual touch operation unit, and a physical button control unit, maintaining a bidirectional communication connection between the virtual touch operation unit and the physical button control unit, and maintaining a communication connection between the output terminals of the virtual touch operation unit and the physical button control unit and the input terminal of the mapping logic construction unit.

[0030] S203, the intelligent linkage system control mapping logic construction unit constructs the mapping logic between virtual model operation and physical component control, realizing two-way interaction between the virtual truck model on the central control screen and the physical truck components, including data uplink synchronization and command downlink control.

[0031] S204 The intelligent linkage system controls the virtual touch operation unit, allowing the driver to operate virtual components on the central control screen. The operation commands are transmitted to the control unit of the physical component in real time via the CAN bus, realizing precise control of the physical component with the virtual model as the operation entry point.

[0032] S205, the intelligent linkage system control physical button control unit retains the physical button control method, and together with the virtual touch operation unit, it forms a dual control system of virtual touch and physical buttons.

[0033] Intelligent Fault Analysis and Early Warning S301. The intelligent fault analysis and early warning module is used to embed an AI fault analysis algorithm. When the operating data of the physical component exceeds the threshold or an anomaly occurs, the module locates the fault point on the virtual model, analyzes the linkage effect, issues a graded early warning, and provides fault handling guidance.

[0034] S302. The intelligent fault analysis and early warning module includes an AI fault analysis algorithm unit and a fault handling guidance unit. The output of the AI ​​fault analysis algorithm unit is kept in communication connection with the input of the fault location display unit, the linkage impact analysis unit, and the hierarchical early warning execution unit, respectively. The fault handling guidance unit and the fault location display unit are kept in bidirectional communication connection.

[0035] S303, The intelligent linkage system control AI fault analysis algorithm unit embeds an AI fault analysis algorithm. The algorithm is trained based on the operating thresholds, linkage logic and historical fault data of each component of the truck. When the operating data of the physical component exceeds the threshold or an anomaly occurs, the faulty virtual component is highlighted on the virtual truck model, the fault type is marked and a local view of the faulty part is displayed. The linkage impact of the faulty component is analyzed and the linkage impact effect is displayed synchronously on the virtual model.

[0036] S304. The intelligent fault analysis and early warning module also includes an algorithm optimization unit. The output of the algorithm optimization unit is kept in communication with the input of the AI ​​fault analysis algorithm unit. The intelligent linkage system controls the algorithm optimization unit to continuously iterate and optimize the AI ​​fault analysis algorithm, including incremental training of the algorithm model based on newly collected truck component operating data and actual fault cases; adaptively adjusting the algorithm's judgment parameters and early warning thresholds according to the dynamic changes of the operating thresholds, linkage logic, and historical fault data of each component; calculating and analyzing errors by comparing the fault prediction results output by the algorithm with the actual fault situation, and backpropagating to optimize the algorithm model parameters, thereby gradually improving the accuracy of fault location and the timeliness of early warning.

[0037] Cockpit adaptation optimization S401, The cab adaptation and optimization module is used to comprehensively adapt and optimize the virtual model's interface display, operation mode, key points of working condition monitoring, and offline transmission by combining the spatial characteristics of the truck cab, the driver's operating perspective, and the truck's driving conditions.

[0038] S402, The cockpit adaptation and optimization module includes an interface adaptation unit, an operation adaptation unit, an operating condition adaptation unit, and an offline adaptation unit, and the output terminals of the interface adaptation unit, operation adaptation unit, operating condition adaptation unit, and offline adaptation unit are all communicatively connected to the input terminal of the cockpit adaptation and optimization module.

[0039] The S403 intelligent linkage system control interface adapter unit adopts a virtual model interface with large icons, high contrast, and a simple layout to meet the long-distance viewing needs of truck drivers.

[0040] S404 The intelligent linkage system control operation adapter unit is equipped with an anti-accidental touch mechanism, including long press confirmation and double-click operation, to adapt to the bumpy environment of truck driving.

[0041] The S405 intelligent linkage system control condition adaptation unit presets key monitoring components of virtual models for different operating conditions of trucks, such as high speed, heavy load, climbing, and turning, and automatically focuses and displays them on the central control screen. This includes key monitoring of the engine and hydraulic system when climbing, and key monitoring of the braking system and tires when turning.

[0042] S406, the intelligent linkage system controls the offline adaptation unit to build a local data storage unit. When the 5G signal is interrupted, it automatically switches to CAN bus local transmission to ensure the continuity of virtual entity linkage.

[0043] Complete linkage process S501. Construct a high-precision virtual truck model and load it onto the central control screen. Based on the 3D design drawings of the target truck, use 3D modeling technology to construct a 1:1 scale high-precision virtual truck model. Encode and bind the attributes of each virtual component independently. Load the virtual truck model onto the central control screen and support multi-view switching, scaling and rotation operations.

[0044] S502 collects real-time operating parameter data of each core component of the physical truck and transmits it to the central control screen. The operating parameter data is collected by sensors deployed on each core component. After filtering, noise reduction and calibration preprocessing, the data is transmitted to the central control screen through a dual-link method of CAN bus and 5G wireless transmission. After receiving the data, the central control screen synchronously updates the operating status display of the corresponding virtual component in the virtual truck model.

[0045] S503 uses a virtual model on the central control screen to perform bidirectional linkage control and fault warning for physical components. It responds to the driver's touch operation on the virtual components on the central control screen, transmits the operation command to the control unit of the physical component through the CAN bus for execution, and at the same time starts the AI ​​fault analysis algorithm to analyze the operating data. When the data exceeds the threshold or an anomaly occurs, it locates the fault point on the virtual model, analyzes the linkage effect, issues a graded warning and generates troubleshooting guidance.

[0046] S504. Repeat steps S502 to S503 until the truck is turned off and stopped.

[0047] Example 1 (Based on long-haul trunk logistics transportation scenario) System Configuration Virtual truck model: A 1:1 scale high-precision model containing eight core components, including the cab, engine, chassis, braking system, hydraulic system, tires, fuel tank, and exhaust treatment system. Sensor deployment: There are 5 types of sensors, including pressure sensors, speed sensors, temperature sensors, displacement sensors, and vibration sensors, with 6-8 sensors in each type, for a total of 32 sensor nodes; Data transmission: CAN bus + 5G dual link, latency ≤100ms, automatic switch to CAN bus local transmission when 5G signal is interrupted; AI fault analysis algorithm: trained based on operating thresholds, linkage logic, and historical fault data, including linkage logic graphs of 8 major components; Level-based warnings: Mild (flashing yellow + text), Moderate (flashing red + voice), Severe (full-screen warning + forced speed reduction suggestion); Cockpit adaptation: large icons and high-contrast interface, long press to confirm to prevent accidental touch, adaptive focus based on operating conditions, and offline local storage; Implementation data: This system was deployed in a logistics company's inter-provincial trunk transportation fleet, covering 12 tractor units and 24 trailers. The operating routes cover highways, national roads and mountainous sections, with an average one-way mileage of 1,200 kilometers.

[0048] Table 1: System Performance Test Data for Example 1

[0049] Specific implementation case: On May 12, 2026, a logistics company's trunk transportation fleet carried out an inter-provincial transportation task from Hangzhou to Chengdu. The vehicles were Jiefang J6P tractor trucks with a total weight of 49 tons. The route covered the G50 Shanghai-Chongqing Expressway and the G42 Shanghai-Chengdu Expressway, passing through plains, hills and mountainous sections.

[0050] Work process: 06:00:00: The driver starts the vehicle, and the linkage system of this invention is automatically activated. The high-precision virtual truck modeling module loads a 1:1 virtual truck model onto the central control screen.

[0051] 06:00:15: The multi-dimensional data acquisition and transmission module starts, and 32 sensor nodes begin to collect operating parameter data such as engine speed, braking system pressure, hydraulic oil temperature, tire pressure, and fuel tank level.

[0052] 06:00:30: The data preprocessing unit filters, reduces noise, and calibrates the raw data, removing invalid data.

[0053] 06:00:35: The dual-link transmission unit transmits pre-processed data to the central control screen via CAN bus + 5G dual link, with a delay of 78ms.

[0054] 06:00:40: The virtual truck model on the central control screen synchronously updates the operating status of all components, displaying engine speed at 650 rpm, braking system pressure at 8.5 bar, and tire pressure at 8.2 bar.

[0055] 07:30:00: When the vehicle reaches the Anhui section of the G50 expressway, the driver uses the virtual touch operation on the central control screen to click on the virtual tires, view the tire pressure details of each tire, and perform tire pressure calibration.

[0056] 10:15:00: The vehicle enters the uphill section of the western Hubei mountainous area, and the working condition adaptation unit automatically focuses the virtual model on the engine and hydraulic system.

[0057] 10:22:00: The engine temperature sensor detected that the coolant temperature rose to 112℃ (threshold 105℃), exceeding the minor fault threshold.

[0058] 10:22:05: The AI ​​fault analysis algorithm unit starts analysis, and the fault location display unit highlights the engine component on the virtual model and marks it as "coolant temperature too high".

[0059] 10:22:10: The analysis of the linkage effect unit shows that the high temperature of the engine will cause the oil temperature of the hydraulic system to rise and the power output to decrease. The linkage effect is displayed synchronously on the virtual model.

[0060] 10:22:15: The graded early warning execution unit issues a minor fault warning. The virtual engine flashes yellow and is accompanied by the text prompt "It is recommended to reduce the speed to below 60km / h and check the coolant".

[0061] 10:22:20: The fault handling guidance unit marks the fault handling steps on the virtual model.

[0062] 10:22:30: The driver followed the obstacle removal instructions on the virtual model, reduced the speed to 55km / h, shifted to a low gear, and turned on the auxiliary cooling system.

[0063] 10:25:00: The engine temperature gradually drops to 98℃, returning to the normal operating range, and the virtual model warning is lifted.

[0064] 14:30:00: The vehicle was traveling on the Yichang section of the G42 expressway, passing through a group of tunnels, when the 5G signal was interrupted.

[0065] 14:30:05: The dual-link transmission unit automatically switches to CAN bus local transmission, and the offline adapter unit enables local data storage.

[0066] 14:30:10: The virtual-physical linkage system continues to operate normally, and basic monitoring and control functions are unaffected.

[0067] At 02:00:00 the following day: The vehicle arrived safely in Chengdu, having traveled 1260 kilometers in 20 hours. The system recorded and stored operational data throughout the entire journey, accumulating approximately 2.3 million valid data points, and no driving safety issues occurred due to system malfunctions.

[0068] Results: In long-haul logistics transportation scenarios, the system of this invention achieves real-time two-way linkage between virtual trucks and physical components. The engine high temperature fault takes only 15 seconds from the occurrence of the abnormality to the warning response. The driver can complete the fault handling within 3 minutes according to the troubleshooting guidance of the virtual model. When the 5G signal is interrupted, the system automatically completes offline switching within 5 seconds, with no data loss throughout the process. Compared with the traditional dashboard + fault code prompt method, the fault detection time is shortened from an average of 8 minutes to 15 seconds, and the fault handling time is shortened from an average of 25 minutes to 3 minutes.

[0069] Example 2 (Based on heavy-load short-distance transportation scenario in mining areas) System Configuration Virtual truck model: 1:1 scale high-precision mining dump truck model, including 7 major core components: cab, engine, chassis, braking system, hydraulic system, tires, and fuel tank; Sensor deployment: There are 5 types of sensors, including pressure sensors, speed sensors, temperature sensors, displacement sensors, and vibration sensors, with 4-6 sensors in each type. The sensors are waterproof, shockproof, and high-temperature resistant, for a total of 26 sensor nodes. Data transmission: CAN bus as the main link + 5G auxiliary link, latency ≤95ms, priority is given to local transmission of CAN bus to ensure the signal stability of the mining area. AI fault analysis algorithm: trained based on operating threshold + linkage logic + historical fault data of mining area, including linkage logic diagrams of 7 major components, to enhance the identification of vibration and shock conditions. Level-based warnings: Mild (flashing yellow + text), Moderate (flashing red + voice), Severe (full-screen warning + forced speed reduction suggestion); Cockpit adaptation: extra-large icons and high-contrast interface, double-tap confirmation to prevent accidental touch, adaptive focus for heavy load / climbing conditions, and priority for offline local storage; Implementation data: This system was deployed in a large open-pit iron mine, covering 8 mining dump trucks. The operating route is from the mining face to the crushing station and back, with an average one-way mileage of 3.5 kilometers and 80-120 round trips per day. The road conditions are poor (gravel, potholes, steep slopes).

[0070] Table 2: System Performance Test Data for Example 2

[0071] Specific implementation case: On June 18, 2026, a large open-pit iron mine was carrying out mining operations. A mining dump truck was performing the task of transporting ore from the mining face to the crushing station. The full load weight was 130 tons. The route included a heavy-load uphill section with a 12% gradient and a bumpy road surface with gravel.

[0072] Work process: 07:00:00: The driver starts the mining dump truck, and the linkage system of this invention is automatically activated. The high-precision virtual truck modeling module loads a 1:1 virtual mining dump truck model onto the central control screen.

[0073] 07:00:10: The multi-dimensional data acquisition and transmission module starts, and 26 enhanced sensor nodes begin collecting data.

[0074] 07:00:25: The data preprocessing unit performs filtering, noise reduction, and calibration on the raw data, and enhances the filtering algorithm for the high-vibration environment of the mining area.

[0075] 07:00:30: The dual-link transmission unit transmits data to the central control screen via CAN bus (priority) + 5G auxiliary dual-link, with a delay of 85ms.

[0076] 07:00:40: The virtual mining dump truck model on the central control screen synchronously updates the operating status of all components: engine speed 1250rpm, braking system pressure 12.5bar, hydraulic lifting system pressure 18.0MPa, and tire pressure 9.5bar.

[0077] 07:30:00: The vehicle, fully loaded, enters the 12% uphill section. The working condition adaptation unit automatically focuses the virtual model on the engine, hydraulic system, and braking system.

[0078] 08:45:00: The vehicle completed its 7th transport trip, covering a total distance of 24.5 kilometers. The system operated stably throughout the entire process.

[0079] 10:30:00: During the 12th transport trip, the right rear tire temperature sensor detected a temperature rise to 78℃ (threshold 70℃), exceeding the minor fault threshold.

[0080] 10:30:03: The AI ​​fault analysis algorithm unit starts analysis, and the fault location display unit highlights the right rear tire on the virtual model and marks it as "Tire temperature too high".

[0081] 10:30:08: The analysis of the linkage effect unit shows that the high temperature of the right rear tire will lead to an abnormal increase in tire pressure and an increase in braking distance. The linkage effect is displayed synchronously on the virtual model.

[0082] 10:30:12: The graded early warning execution unit issues a moderate fault warning, the virtual tire flashes red and is accompanied by a voice reminder: "The right rear tire temperature is too high, it is recommended to stop and check."

[0083] 10:30:15: The fault handling guidance unit marks the fault handling steps on the virtual model.

[0084] 10:30:20: Following instructions, the driver parked the vehicle in a safe area for inspection and found that the tire had a minor puncture, which caused friction and increased temperature.

[0085] 10:35:00: After completing tire replacement and fault confirmation, the system automatically records the fault handling results and the warning is lifted.

[0086] 14:00:00: Heavy rain hit the mining area, causing unstable 5G signal.

[0087] 14:00:05: The dual-link transmission unit automatically switches to pure CAN bus local transmission, and the offline adapter unit enables local data storage.

[0088] 14:00:15: The virtual entity linkage system continues to operate normally, and the monitoring and control functions are completely unaffected.

[0089] 17:30:00: The day's work has ended. The vehicles have completed a total of 86 transport missions, and the system is running stably throughout the entire process.

[0090] Results: In the scenario of heavy-duty short-distance transportation in mining areas, the system of this invention achieved real-time two-way linkage between virtual trucks and physical components. The time from the occurrence of a tire high-temperature fault to the warning response was only 12 seconds. The driver completed the fault diagnosis and handling within 5 minutes according to the troubleshooting guidance of the virtual model. When heavy rainfall in the mining area caused unstable 5G signals, the system automatically completed the local transmission switch of pure CAN bus within 10 seconds. After running for 10.5 hours under continuous high vibration and heavy load conditions, the system did not experience any faults. Compared with the traditional instrument panel + manual inspection method, the fault detection time was shortened from an average of 15 minutes to 12 seconds, and the fault handling time was shortened from an average of 40 minutes to 5 minutes.

[0091] The specific operating mode of the working condition adaptation unit includes: (1) High-speed working condition adaptation: When the vehicle speed is ≥80km / h, the virtual model automatically focuses on the tires, braking system and engine, and focuses on monitoring tire pressure, brake pad temperature and engine speed; (2) Heavy load condition adaptation: When the vehicle load is ≥80% of the rated load, the virtual model automatically focuses on the engine, braking system and hydraulic system, and focuses on monitoring engine torque, braking pressure and hydraulic oil temperature; (3) Adaptation to climbing conditions: When the vehicle is on an uphill section with a gradient of ≥5%, the virtual model automatically focuses on the engine and hydraulic system, and focuses on monitoring the engine coolant temperature, oil pressure and hydraulic system pressure; (4) Adaptation to turning conditions: When the vehicle's turning angle is ≥15°, the virtual model automatically focuses on the braking system and tires, and focuses on monitoring the distribution of braking pressure on each wheel and the lateral force on the tires.

[0092] The specific working method of the AI ​​fault analysis algorithm includes: (1) Single-point fault judgment is performed based on the operating threshold of each component of the truck. When the data of any sensor exceeds the preset threshold range, the fault analysis process is triggered. (2) Based on the linkage logic between truck components, perform correlation analysis. When a component malfunctions, automatically retrieve the operating data of other components that are linked to it, and comprehensively judge the scope of the fault's impact. (3) Based on historical fault data, perform pattern matching, compare the current fault characteristics with historical fault cases, identify similar fault patterns and provide reference handling solutions; (4) The algorithm optimization unit continuously iterates and optimizes the above judgment logic, linkage logic and pattern matching parameters based on the newly collected actual fault data.

[0093] The specific working mode of the hierarchical early warning execution unit includes: Minor malfunction: The virtual component flashes yellow, and the lower left corner of the central control screen displays the text "Suggested attention: [Component Name] [Abnormal Parameter]", which does not affect normal driving; Moderate fault: The virtual component flashes red, a prompt box pops up in the center of the control screen and a voice broadcast "Please note: [Component Name] [Abnormal Parameter], [Recommendation]", suggesting that the driver slow down or stop to check; Severe malfunction: The virtual component flashes red and is accompanied by a full-screen red border warning. The voice continuously announces "Immediately reduce speed: [Component Name] [Serious Abnormality], it is recommended to stop immediately." At the same time, the central control screen displays a forced speed reduction suggestion to remind the driver to take emergency measures.

[0094] Specifically, in practical applications, multiple sets of virtual truck and physical component linkage systems with central control screens in intelligent truck cabs are deployed on trucks of different brands and models. These systems share data and synchronize models via a cloud platform. This invention constructs a complete truck virtual-physical linkage system by setting up a high-precision virtual truck modeling module, a multi-dimensional data acquisition and transmission module, a virtual-physical bidirectional linkage control module, an intelligent fault analysis and early warning module, and a cab adaptation and optimization module. In actual operation, a 1:1 scale high-precision virtual truck model is constructed based on the target truck's 3D design drawings, and each virtual component is independently coded and attribute-bound. Dedicated sensors deployed on each core component collect real-time operating parameter data, which, after filtering, noise reduction, and calibration preprocessing, is transmitted to the central control screen via a dual-link method of CAN bus and 5G wireless transmission. Upon receiving the data, the central control screen synchronously updates the operating status display of the corresponding virtual component in the virtual truck model. It responds to the driver's touch or physical button operations on the virtual components, enabling precise operation of physical components with the virtual model as the operating entry point. This invention achieves breakthrough innovation in truck intelligent cockpit virtual linkage technology through AI fault analysis algorithms, enabling precise virtual location of fault points, linkage impact analysis, and graded early warning, while providing on-site troubleshooting guidance. It automatically adjusts the monitoring focus of the virtual model and displays it according to different truck operating conditions, automatically switching to CAN bus local transmission when 5G signal is interrupted. Using 1:1 high-precision virtual truck modeling technology, it transforms the abstract data of physical components into intuitive virtual visualization effects. Through a two-way linkage mechanism of "data uplink + command downlink," it breaks through the limitations of unidirectional data transmission in existing technologies. AI fault analysis algorithms upgrade the system from "passive fault handling" to "proactive intelligent early warning." Through dedicated cockpit adaptation and optimization technology, it solves the compatibility differences between virtual linkage technologies for commercial vehicles and passenger vehicles. This invention achieves a breakthrough innovation in truck intelligent cockpit virtual linkage technology, filling the technological gap in precise linkage of virtual physical components in the commercial vehicle field. It manages, visualizes, and stores truck operating data and corresponding linkage analysis results, facilitating unified management of multi-vehicle linkage systems through a cloud platform and improving the level of intelligent management of truck fleets.

[0095] The beneficial effects of this invention are: Visualization and intuitiveness are greatly improved: For the first time, a 1:1 high-precision virtual truck model is built for the truck cab, transforming the abstract data of physical components into intuitive virtual visualization effects. Drivers can fully grasp the vehicle's operating status through multiple perspectives, zooming, and rotation operations, greatly reducing the cost of information understanding and adapting to the characteristics of trucks with multiple components and complex structures.

[0096] Achieving precise two-way linkage between virtual entities: Breaking through the limitations of unidirectional data transmission in existing technologies, a two-way linkage mechanism of "data uplink + command downlink" has been constructed. Drivers can directly control physical components through the virtual model on the central control screen, simplifying the complex operation process of trucks and improving the convenience and accuracy of operation.

[0097] Significantly improved fault diagnosis and handling efficiency: Through AI fault analysis algorithms, the fault point is virtually and accurately located, and the linkage impact analysis is performed. It also provides graded early warning and on-site troubleshooting guidance, which changes the inefficient traditional "fault code prompts + offline professional testing" model. This greatly shortens the fault handling time and reduces transportation time loss.

[0098] Enhancing the safety and reliability of truck driving: Through real-time monitoring and coordinated analysis of the core components of the truck, it is possible to predict the linkage failure between components and issue early warnings, upgrading from "passive fault handling" to "proactive safety warning", effectively avoiding driving safety accidents caused by component abnormalities, and adapting to the safety requirements of heavy-duty and long-distance truck transportation.

[0099] Specifically designed for commercial vehicles, this system is highly practical: Targeting the large size, heavy load, multiple operating conditions, and high vibration characteristics of trucks, it comprehensively optimizes sensors, data transmission, virtual interfaces, and operating methods. This solves the problem of insufficient adaptability of existing passenger car virtual linkage technology to commercial vehicles, and can be directly implemented in the intelligent driving cabin transformation and mass production of various mainstream trucks.

[0100] The dual control system offers greater adaptability: it retains physical button controls while adding virtual touch controls, taking into account both the traditional operating habits of truck drivers and the needs for intelligent upgrades, reducing the learning cost for drivers and facilitating rapid promotion and application.

[0101] Offline linkage ensures strong continuity: Through CAN bus + 5G dual-link transmission + local data storage, basic virtual-physical linkage is realized in the absence of network environment, ensuring that trucks can still achieve real-time monitoring and control of components in remote areas, highway sections and other signal-free scenarios, ensuring an intelligent experience throughout the driving process.

[0102] Those skilled in the art will recognize that the modules and method steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0103] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, equipment, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0104] In the embodiments provided in this application, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or units may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or equipment, and may be electrical, mechanical, or other forms.

[0105] The modules used for high-precision virtual truck modeling, multi-dimensional data acquisition and transmission, bidirectional linkage control of virtual entities, intelligent fault analysis and early warning, and driver's cab adaptation and optimization may or may not be physically separate. The components displayed as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0106] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0107] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program instructions, such as USB flash drives, portable hard drives, read-only storage servers, random access storage servers, magnetic disks, or optical disks.

[0108] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A truck intelligent driver's cab central control screen virtual truck and physical component linkage system, characterized in that, The linkage system includes a high-precision virtual truck modeling module, a multi-dimensional data acquisition and transmission module, a virtual entity bidirectional linkage control module, an intelligent fault analysis and early warning module, and a driver's cab adaptation and optimization module. These modules are all located on the truck's central control screen and the truck itself. The modules maintain real-time data communication and collaborative operation through a dual-link system of onboard CAN bus and 5G wireless transmission. Operators can access the linkage system by logging into the high-precision virtual truck modeling module and view the real-time operating data of each module.

2. The truck intelligent cab central control screen virtual truck and physical component linkage system according to claim 1, characterized in that: The high-precision virtual truck modeling module is used to construct a 1:1 scale high-precision virtual truck model based on the three-dimensional design drawings of the target truck. The virtual truck model completely restores all core components and auxiliary structures of the truck, including the cab, engine, chassis, braking system, hydraulic system, tires, fuel tank, and exhaust gas treatment system. Each virtual component is independently coded and its attributes are bound, and the module supports multi-view switching, zooming, and rotation operations on the central control screen. The multi-dimensional data acquisition and transmission module is used to deploy dedicated sensors on each core component of the physical truck to collect the operating parameter data of each core component in real time. The collected data is transmitted to the central control screen through a dual-link method of vehicle CAN bus and 5G wireless transmission, and the data transmission delay is controlled within 100ms. The virtual entity bidirectional linkage control module is used to construct the mapping logic between virtual model operation and physical component control, so as to realize bidirectional interaction between the virtual truck model on the central control screen and the physical truck components, including data uplink synchronization and command downlink control. The intelligent fault analysis and early warning module is used to embed AI fault analysis algorithms. When the operating data of physical components exceeds the threshold or anomalies occur, the module locates the fault point on the virtual model, analyzes the linkage effect, issues a graded early warning, and provides fault handling guidance. The cab adaptation and optimization module is used to comprehensively adapt and optimize the virtual model's interface display, operation method, key monitoring points, and offline transmission by combining the spatial characteristics of the truck cab, the driver's operating perspective, and the truck's driving conditions.

3. The truck intelligent cab central control screen virtual truck and physical component linkage system according to claim 1, characterized in that: The high-precision virtual truck modeling module includes a high-precision virtual truck model, an independent coding and binding unit, and a multi-view switching unit. The outputs of the high-precision virtual truck model and the independent coding and binding unit are both communicatively connected to the input of the multi-view switching unit. The three-dimensional model building unit is used to construct a 1:1 scale high-precision virtual truck model based on the three-dimensional design drawings of the target truck. The virtual truck model completely restores all the core components and auxiliary structures of the truck, including the cab, engine, chassis, braking system, hydraulic system, tires, fuel tank and exhaust gas treatment system. The independent coding and binding unit is used to independently code and bind attributes to each virtual component. The bound attributes include the component's physical parameters, operating thresholds, linkage logic, and fault characteristics. The perspective interaction unit is used to support multi-view switching, zooming and rotation operations on the central control screen.

4. The truck intelligent cab central control screen virtual truck and physical component linkage system according to claim 1, characterized in that: The multi-dimensional data acquisition and transmission module includes a sensor acquisition and transmission unit, a data preprocessing unit, and a real-time synchronization unit. The output end of the sensor acquisition and transmission unit is communicatively connected to the input end of the data preprocessing unit, and the data preprocessing unit and the real-time synchronization unit are bidirectionally communicatively connected. The sensor deployment unit is used to deploy dedicated sensor groups on each core component of the physical truck; The data preprocessing unit is used to filter, reduce noise, and calibrate the raw operating parameter data collected by the sensor, and to remove invalid data. The dual-link transmission unit is used to transmit preprocessed operating parameter data to the virtual truck modeling module on the central control screen via a dual-link method of vehicle CAN bus and 5G wireless transmission.

5. The truck intelligent cab central control screen virtual truck and physical component linkage system according to claim 1, characterized in that: The virtual entity bidirectional linkage control module includes a mapping logic construction unit, a virtual touch operation unit, and a physical button control unit. The virtual touch operation unit and the physical button control unit are bidirectionally connected, and the output terminals of the virtual touch operation unit and the physical button control unit are both connected to the input terminal of the mapping logic construction unit. The mapping logic construction unit is used to construct the mapping logic between virtual model operation and physical component control, so as to realize the two-way interaction between the virtual truck model on the central control screen and the physical truck components. The virtual touch operation unit is used for the driver to perform touch operations on virtual components on the central control screen. The operation commands are transmitted to the control unit of the physical component in real time via the CAN bus. The physical button control unit is used to retain the physical button control method, and together with the virtual touch operation unit, it forms a dual control system of virtual touch and physical buttons.

6. The truck intelligent cab central control screen virtual truck and physical component linkage system according to claim 5, characterized in that: The intelligent fault analysis and early warning module includes an AI fault analysis algorithm, a fault handling guidance unit, and an algorithm optimization unit. The output of the algorithm optimization unit is communicatively connected to the input of the AI ​​fault analysis algorithm, and the AI ​​fault analysis algorithm and the fault handling guidance unit are bidirectionally communicatively connected. The AI ​​fault analysis algorithm is used to embed an AI fault analysis algorithm, which is trained based on the operating thresholds, linkage logic and historical fault data of various truck components; The fault handling guidance unit is used to mark fault handling steps on the virtual model; The algorithm optimization unit is used to continuously iterate and optimize the AI ​​fault analysis algorithm, and to incrementally train the algorithm model based on newly collected truck component operation data and actual fault cases; and to adaptively adjust the algorithm's judgment parameters and warning thresholds according to the dynamic changes of the operation thresholds, linkage logic and historical fault data of each component.

7. The truck intelligent cab central control screen virtual truck and physical component linkage system according to claim 1, characterized in that: The cockpit adaptation and optimization module includes an interface adaptation unit, an operation adaptation unit, a working condition adaptation unit, and an offline adaptation unit. The outputs of the interface adaptation unit, the operation adaptation unit, the working condition adaptation unit, and the offline adaptation unit are all communicatively connected to the input of the cockpit adaptation and optimization module. The interface adaptation unit is used for virtual model interfaces with large icons, high contrast, and a simple layout. The operation adaptation unit is used to set up an anti-accidental touch mechanism, including long press confirmation and double-click operation; The working condition adaptation unit is used to preset key monitoring components of the virtual model for different working conditions of trucks, such as high speed, heavy load, climbing and turning, and automatically focus on display them on the central control screen. The offline adaptation unit is used to build a local data storage unit, which automatically switches to CAN bus local transmission when the 5G signal is interrupted.

8. A method for linking a virtual truck with physical components in a truck intelligent cockpit central control screen, used to implement the truck intelligent cockpit central control screen virtual truck with physical components linkage system as described in any one of claims 1-7, characterized in that: The specific steps include the following: S1. Construct a high-precision virtual truck model and load it onto the central control screen. Based on the 3D design drawings of the target truck, use 3D modeling technology to construct a 1:1 scale high-precision virtual truck model. Encode and bind the attributes of each virtual component independently. Load the virtual truck model onto the central control screen and support multi-view switching, scaling and rotation operations. S2. Real-time acquisition of operating parameter data of each core component of the physical truck and transmission to the central control screen. The operating parameter data is collected by sensors deployed on each core component. After filtering, noise reduction and calibration preprocessing, the data is transmitted to the central control screen through a dual-link method of CAN bus and 5G wireless transmission. After receiving the data, the central control screen synchronously updates the operating status display of the corresponding virtual component in the virtual truck model. S3. Through the virtual model of the central control screen, the physical components are controlled in two directions and fault warnings are given. The system responds to the driver's touch operation on the virtual components on the central control screen and transmits the operation instructions to the control unit of the physical components via the CAN bus for execution. At the same time, the AI ​​fault analysis algorithm is activated to analyze the operating data. When the data exceeds the threshold or an anomaly occurs, the fault point is located on the virtual model, the linkage effect is analyzed, a graded warning is issued, and troubleshooting guidance is generated.

9. The method for linking the virtual truck and physical components in the central control screen of the intelligent truck driver's cab according to claim 8, characterized in that: Step S1 specifically includes the following steps: S101. Obtain the full-vehicle three-dimensional design drawings of the target truck, and use 3D modeling technology to construct a 1:1 scale high-precision virtual truck model. The virtual truck model fully restores all core components and auxiliary structures of the truck's cab, engine, chassis, braking system, hydraulic system, tires, fuel tank and exhaust gas treatment system. S102. Encode each virtual component independently and bind its physical parameters, operating thresholds, linkage logic, and fault characteristic attributes so that the attributes of the virtual components correspond one-to-one with the attributes of the physical components. S103. Load the completed virtual truck model onto the central control screen and configure visual interactive functions such as multi-view switching, zooming, and rotation.

10. The method for linking the virtual truck and physical components in the central control screen of the intelligent truck driver's cab according to claim 9, characterized in that: Step S2 specifically includes the following steps: S201. Real-time acquisition of operating parameter data through a dedicated sensor group deployed on each core component of the physical truck, wherein the dedicated sensor group is selected from one or more of pressure sensors, speed sensors, temperature sensors, displacement sensors and vibration sensors; S202. Perform filtering, noise reduction, and calibration preprocessing on the raw operating parameter data collected by the sensor to remove invalid data; S203. The pre-processed operating parameter data is transmitted to the central control screen via a dual-link method of vehicle CAN bus and 5G wireless transmission. S204. After receiving the operating parameter data of the physical components, the central control screen synchronously updates the operating status display of the corresponding virtual components in the virtual truck model.

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