A lateral control method for the vehicle controller hub in intelligent driving of heavy-duty trucks

Abstract

This invention discloses a lateral control method for the central control unit of a vehicle controller for intelligent driving of heavy-duty trucks, belonging to the field of lateral control in intelligent vehicle driving. The method pre-calibrates and stores front and rear wheel steering angle basic allocation maps, global friction compensation maps, and damping compensation maps covering multiple driving scenarios for heavy-duty trucks in the VCU; it acquires target trajectory and vehicle status information in the intelligent driving domain in real time; the VCU calculates the target steering angle and steering phase difference of the front and rear wheels according to the current scenario, and simultaneously calculates the friction compensation and damping compensation amounts, superimposing them to generate steering execution commands for the front and rear wheels; it achieves rapid response with a dedicated hardware channel and the highest priority during emergency obstacle avoidance, and implements hierarchical redundancy fault tolerance in the event of steering system failure; and it introduces trailer attitude constraints and vehicle energy management linkage. This invention overcomes the communication delay and high energy consumption problems caused by the decentralized control of multiple controllers in the steering system of heavy-duty trucks, significantly reducing steering energy consumption and CAN bus load while ensuring lateral tracking accuracy, and improving the lateral stability and safety of heavy-duty trucks under extreme conditions such as low-adhesion roads and emergency obstacle avoidance.

Description

Technical Field

[0001] This invention relates to the field of intelligent driving technology for commercial vehicles, and in particular to a lateral control method for the central control unit of a vehicle for intelligent driving of heavy-duty trucks. Background Technology

[0002] With the advancement of intelligent driving in commercial vehicles, the requirements for intelligent driving control performance of heavy-duty trucks are increasing. Due to the characteristics of heavy-duty trucks, such as large vehicle mass, long wheelbase, drastic changes in center of gravity with load, and strong motion coupling when with trailers, their lateral control is far more complex than that of passenger cars.

[0003] Currently, the lateral control of intelligent driving in heavy-duty trucks generally follows the passenger car solution, which has many shortcomings. First, the front and rear wheel steering control mostly adopts a multi-node distributed architecture of steering ECU + rear wheel steering controller + vehicle controller VCU. The controllers need to frequently exchange intermediate data, synchronize status, and verify commands, resulting in a high load on the CAN bus communication, which can easily cause data transmission delays and signal distortion, making it difficult to meet the real-time steering response requirements of intelligent driving. Second, the friction compensation and damping compensation of the steering system usually only adjust the steering column at a single point, without considering the differences in the friction characteristics of the entire front and rear wheel steering system. In particular, it ignores the static friction lag, increased wear, and friction drift caused by temperature changes due to the large load and high steering torque of heavy-duty trucks. Third, the existing front and rear wheel coordinated steering mostly only uses the vehicle body yaw rate and center of gravity sideslip angle as control targets, without incorporating the energy consumption of the steering system into the optimization, resulting in frequent ineffective work by the steering actuator motor and increased vehicle power consumption. Furthermore, for heavy-duty trucks with trailers, existing technologies rarely incorporate trailer stability constraints into lateral control, which can easily lead to hazards such as trailer folding and fishtailing during low-traction road surfaces or emergency obstacle avoidance. Finally, traditional solutions rely solely on localized redundant hardware for fault tolerance, failing to achieve low-cost, high-reliability fault-tolerant control through vehicle-level coordination.

[0004] The aforementioned shortcomings have led to long-term pain points for the lateral control of intelligent driving of heavy-duty trucks, such as high communication latency, high steering energy consumption, prominent risk of trailer instability, and poor adaptability to all working conditions. Therefore, the industry urgently needs a lateral control solution for intelligent driving of heavy-duty trucks that can be optimized from the perspective of the whole vehicle. Summary of the Invention

[0005] This invention aims to provide a lateral control method for the vehicle controller central axis of intelligent driving of heavy-duty trucks. The method uses the vehicle controller (VCU) as the sole computing and decision-making core, and deeply integrates front and rear wheel steering coordination, friction damping dual compensation, trailer stability control and vehicle energy management, thereby improving lateral control performance while significantly reducing communication load and system energy consumption.

[0006] To achieve the above objectives, the method proposed in this invention includes:

[0007] In the VCU, construct a MAP for the basic distribution of front and rear wheel steering angles, a MAP for the global friction compensation of the steering system, and a MAP for damping compensation, covering typical driving scenarios of heavy trucks.

[0008] It receives the target trajectory sent by the intelligent driving domain in real time and collects vehicle status signals such as vehicle speed, tractor yaw rate, trailer yaw rate, steering actuator status, and road adhesion coefficient.

[0009] The VCU identifies the current driving scenario, calls the corresponding basic allocation MAP, and calculates the target steering angle and steering phase difference of the front and rear wheels in real time in combination with the vehicle status. Additional constraints are introduced when the road surface is low or the trailer is unstable.

[0010] Friction compensation is calculated based on the full-link friction model of the steering system and the current steering angular velocity and displacement velocity. Damping compensation for the front and rear wheels is calculated according to vehicle speed and steering requirements. The compensation parameters are adaptively corrected under special working conditions.

[0011] The target steering angle, friction compensation, and damping compensation are superimposed to generate the final steering execution command for the front and rear wheels, which is then output to the actuator via the CAN bus or a dedicated channel.

[0012] The actual steering angle and vehicle yaw response are collected to obtain the lateral deviation, and the steering angle allocation and compensation parameters are iteratively optimized.

[0013] In other possible implementations, when in a low-adhesion road surface scenario, the vehicle controller, when calculating the target steering angle and steering phase difference of the front and rear wheels, uses the optimal tire lateral force as a constraint to limit the sum of the steering angles of the front and rear wheels, and actively reduces the steering angle of the rear wheels when the difference in yaw rate between the tractor and the trailer exceeds a predetermined threshold.

[0014] Among other possible implementation methods, the friction compensation calculation method includes: the vehicle controller calls the friction compensation MAP in real time to obtain the basic friction compensation value based on the steering angular velocity and rack displacement velocity, and superimposes the positive or negative vibration parameters of the preset frequency to drive the front wheel and rear wheel steering mechanisms to overcome static friction synchronously.

[0015] In other possible implementations, when a heavy truck is detected to be braking on a long downhill slope, the VCU increases the friction compensation response speed to compensate for the drift in friction characteristics caused by temperature changes.

[0016] In other possible implementations, the lateral control method further includes an emergency obstacle avoidance response step: when the vehicle controller receives an emergency obstacle avoidance command, it immediately interrupts the control logic for calculating the target steering angle and steering phase difference of the front and rear wheels, calculating the friction compensation amount, and calculating the damping compensation amount, and starts a preset hardware channel and the highest interrupt priority task.

[0017] The vehicle controller directly acquires steering sensor signals through a dedicated ADC interface and directly drives the steering actuator through a dedicated PWM channel to instantly complete the calculation and distribution of obstacle avoidance steering commands.

[0018] In other possible implementations, the lateral control method further includes a fault-level tolerance step: the vehicle controller monitors the status of the front wheel steering system, rear wheel steering system, friction compensation unit, and damping compensation unit in real time, and executes a fault-tolerance strategy according to a predetermined fault level when any system or unit fails; including: if the rear wheel steering fails, the vehicle controller increases the front wheel steering angle and links the trailer braking system to perform differential braking in order to maintain lateral tracking capability.

[0019] In other possible implementations, when the vehicle controller generates the rear wheel steering execution command, it introduces a trailer stability constraint: based on the difference between the trailer's yaw rate and the tractor's yaw rate, it corrects the rear wheel steering phase. When the difference exceeds a safety threshold, the rear wheel steering is forced into a small-angle mode in the same direction to suppress trailer sway.

[0020] Compared to existing technologies, this invention's integrated approach, centered on the VCU, eliminates redundant communication between multiple controllers, reducing the load on the steering-related CAN bus by over 60% and shortening control command response latency by over 30%. The full-domain friction damping dual-compensation linkage control eliminates static friction hysteresis and overshoot under heavy-duty truck steering torque, reducing overall steering system energy consumption by over 20%. Furthermore, the introduction of trailer yaw monitoring and active rear wheel restraint significantly reduces the risk of trailer folding on low-adhesion surfaces and during emergency obstacle avoidance. Moreover, through vehicle energy management linkage, it can automatically favor low-energy steering angle allocation schemes under low SOC conditions, achieving improved overall vehicle energy efficiency. Attached Figure Description

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described below with reference to the accompanying drawings, wherein:

[0022] Figure 1 This is a flowchart illustrating the lateral control method of the vehicle controller for intelligent driving of heavy-duty trucks provided in an embodiment of the present invention. Detailed Implementation

[0023] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0024] This embodiment provides a lateral control method for the central control unit of a vehicle controller for intelligent driving of heavy-duty trucks, relying on a highly integrated vehicle controller (VCU). In the following embodiments, the VCU instance preferably uses a localized automotive-grade main control chip, such as one with a dual-core lockstep Cortex-M7 core, a main frequency of not less than 200MHz, and integrating large-capacity Flash and RAM, multi-channel high-precision ADC, multi-channel independent CAN FD controllers, a high-precision PWM generator, and a hardware safety module, supporting a 1ms-level real-time control cycle and ASIL-D functional safety level. All these hardware resources provide the foundation for real-time calculation, direct signal acquisition, and ultra-fast command output in the subsequent method flow.

[0025] Therefore, as Figure 1 The diagram shows the flow steps of the lateral control method for the vehicle controller hub used in intelligent driving of heavy-duty trucks, which specifically include the following:

[0026] Step S1: Preset three types of MAPs in the VCU: front and rear wheel steering angle distribution, global friction compensation, and damping compensation for multiple scenarios;

[0027] Specifically, during the VCU software development phase, the following three types of core MAP databases can be established through bench testing and vehicle calibration, and then burned into the VCU's Flash memory.

[0028] (1) Front and rear wheel steering angle basic allocation MAP: According to the typical driving scenarios of heavy trucks, it preferably covers low speed (such as vehicle speed <10km / h, the value is only for implementation illustration and not a limitation, the same applies below, and will not be repeated), medium speed urban lane keeping (10-60km / h), high speed cruise (>60km / h), emergency obstacle avoidance and low adhesion road surface (adhesion coefficient ≤0.3); each MAP includes the front and rear wheel steering angle transmission ratio, same-direction / reverse phase relationship and the maximum allowable steering angle rate with vehicle speed and road adhesion coefficient as the axis. In particular, considering the influence of heavy truck trailer load changes on yaw response, the MAP stores the correction coefficients for three typical load states: unloaded, half-loaded and fully loaded. Among them, the load state can be estimated by the VCU from the vehicle height sensor or drive torque.

[0029] (2) Steering system global friction compensation MAP: covers the rack-and-pinion friction pair and steering drive shaft universal joint friction pair of the front wheel steer-by-wire system, as well as the motor reducer friction pair and trapezoidal mechanism friction pair of the rear wheel active steering system; MAP records static friction starting torque, dynamic friction coefficient and static-dynamic friction conversion characteristic curves under different temperatures, speeds and loads.

[0030] (3) Damping compensation MAP: Record the matching values ​​of the front wheel basic damping coefficient and the rear wheel dynamic damping coefficient under different vehicle speeds, steering angular velocities and road surface adhesion coefficients, as well as the solenoid valve duty cycle mapping, etc.

[0031] All of the above MAPs are stored internally in the VCU, eliminating the need for transmission between multiple controllers and thus removing the MAP data sharing latency of traditional solutions from an architectural perspective.

[0032] Step S2: Real-time acquisition of the target trajectory in the intelligent driving domain, and collection of signals such as the yaw rate, vehicle speed, steering status and road adhesion coefficient of the tractor and trailer;

[0033] After the vehicle is powered on and enters intelligent driving mode, the VCU receives target driving trajectory information from the intelligent driving domain controller via the CAN FD bus, including the target lane centerline equation, target yaw rate, target lateral acceleration, and the predicted road curvature. Simultaneously, the VCU directly collects signals from the steering torque sensor, steering angle sensor, and steering system pressure sensor using its own ADC module. It also receives road adhesion coefficient estimates, wheel speeds, yaw rates of the tractor and trailer, and vehicle speed from the ESP system via the CAN bus. Ideally, the VCU also provides independent yaw rate sensors for the rear wheel steering and trailer, directly connected to a dedicated ADC channel via hard wiring to avoid the impact of bus transmission delays on trailer attitude monitoring.

[0034] Step S3: The VCU identifies the current scene, calls the basic MAP to calculate the target steering angle and phase difference of the front and rear wheels, and applies additional constraints when the adhesion is low or the trailer is unstable.

[0035] In practice, the VCU first identifies the current driving scenario based on vehicle speed, intelligent driving domain function status, and road adhesion coefficient. Scenario switching employs hysteresis logic to avoid frequent jumps near critical speeds.

[0036] After identifying the scene, the VCU retrieves the corresponding front and rear wheel steering angle baseline allocation maps from Flash memory and interpolates the target steering angles of the front and rear wheels, along with the baseline phase difference, based on the current trailer load status. On this basis, the VCU runs a nonlinear model predictive control lightweight algorithm, using a two-degree-of-freedom vehicle model as a foundation, combined with the tire lateral force characteristic map, and targeting ideal yaw rate and center-of-gravity sideslip angle, while incorporating the total energy consumption of the steering system into the cost function. In actual calculations, the VCU's hardware floating-point unit accelerates the process, solving for the optimal front and rear wheel steering angle corrections within 1ms, yielding the final target front and rear wheel steering angles.

[0037] In particular, it is necessary to add the following specific constraints for heavy-duty carpenter-specific scenarios:

[0038] On the one hand, for low-adhesion road surface scenarios, if the road surface adhesion coefficient is ≤0.3, the tire lateral force is guaranteed to be unsaturated first; the VCU limits the sum of the front and rear wheel steering angles and prohibits large-angle counter-steering; when the difference in yaw rate Δω between the tractor and trailer is detected to exceed the preset threshold (e.g., 3° / s), the target steering angle of the rear wheel is actively reduced at a gradual rate and the rate of change of the rear wheel steering angle is limited to prevent the trailer from skidding or folding due to excessive steering of the rear wheels.

[0039] On the other hand, for high-speed cruising and anticipation of curves, if the intelligent driving domain sends out information on the curvature of the road ahead, the VCU adjusts the target steering angle phase of the rear wheels in advance, so that a slight pre-steering in the same direction is generated before entering the curve, reducing yaw overshoot at the moment of entering the curve and improving the cornering tracking stability of the trailer-mounted heavy truck.

[0040] Emergency obstacle avoidance commands will not be processed in this step; they will be handled by a dedicated process later. Please refer to the following text for details.

[0041] Step S4: Calculate the friction compensation amount based on the full-link friction model and steering conditions, and simultaneously generate the front and rear wheel damping compensation amounts according to vehicle speed and steering requirements, and adaptively correct them under special conditions.

[0042] Specifically, regarding the calculation of friction compensation, the VCU can obtain the basic friction compensation torque for the front and rear wheels by querying the friction compensation MAP based on the current steering angular velocity of the front and rear wheels and the corresponding rack displacement velocity. Based on this, the VCU generates a vibration compensation signal with a frequency of 10-15Hz. Positive vibration parameters are superimposed on the front wheels, and negative vibration parameters with matching phase are superimposed on the rear wheels. This signal is output to the steering motor via PWM, enabling the friction pairs of the front and rear wheel steering mechanisms to synchronously complete the conversion from static to dynamic friction, effectively overcoming the peak starting torque caused by the large steering torque of heavy trucks. The vibration amplitude mentioned here can be adaptively corrected based on temperature and wear: the VCU estimates the actual friction loss by real-time acquisition of steering torque and motor current signals, compares it with the MAP reference value, iteratively updates the friction compensation amount, and automatically compensates for calibration parameter deviations caused by long-term wear or temperature changes.

[0043] For heavy trucks that frequently face long downhill continuous braking conditions, the friction compensation response speed is dynamically improved: for example, when the VCU detects that the brake pedal is continuously applied and the estimated brake disc temperature exceeds 200°C, it determines that the heat radiation of the steering system may cause changes in lubrication characteristics and an abnormal increase in static friction. At this time, the VCU can temporarily increase the vibration frequency to 15Hz (which can be adjusted as needed) and increase the vibration amplitude to shorten the static-dynamic friction conversion time and ensure that the steering response does not become stuck during the downhill process.

[0044] Following on from the previous section regarding the calculation of damping compensation, the VCU can run a preset coupled model of front and rear wheel coordinated damping requirements. Inputting vehicle speed, target steering angle, steering angular velocity, yaw rate, and road adhesion coefficient, it outputs the basic front wheel damping and the dynamic rear wheel damping based on different driving scenarios. Tests show that in high-speed cruising scenarios, the damping coefficient is increased by 200% to 300% compared to low- and medium-speed conditions to suppress steering system free play and road disturbances, maintaining the stability of the heavy truck in the lane. When the intelligent driving domain initiates a lane change command, the VCU can also appropriately reduce damping at the beginning of the lane change to accelerate the response, and rapidly increase damping during the lane change recovery phase to suppress trailer yaw overshoot and oscillation. Furthermore, if an abnormal increase in the vehicle's center of gravity sideslip angle or a trailer yaw rate fluctuation exceeding a threshold is detected, the damping safety gain mode is immediately triggered, instantly increasing the damping compensation coefficient to 300% of the baseline value and simultaneously adjusting the rear wheel steering angle to quickly converge the trailer sway.

[0045] Step S5: Superimpose the target steering angle, friction compensation and damping compensation to generate the final steering command for the front and rear wheels, and output it to the actuator via bus or dedicated channel;

[0046] The VCU superimposes the target steering angle obtained in step S3 with the friction compensation torque and damping compensation torque obtained in step S4 to generate the target torque command for the front wheel steering motor and the target torque command for the rear wheel steering motor, and at the same time generates the target duty cycle signal for the damping solenoid valve.

[0047] Subsequently, the front wheel steering command is sent to the front wheel steering actuator via the CAN FD bus, while the rear wheel steering command is sent to the rear wheel active steering controller via another independent CAN FD. The friction compensation vibration signal is generated by the VCU's eTPU peripheral, producing a high-precision PWM waveform that directly drives the motor. The damping solenoid valve is controlled by GPIO combined with a high-side drive chip to ensure the real-time performance of the compensation control.

[0048] During this process, the VCU can also use trailer stability constraints to perform a final check on the rear wheel commands: if the difference between the current trailer yaw rate and the tractor yaw rate exceeds the safety threshold, then regardless of the upper-level strategy, the rear wheel steering command is forcibly corrected to a small angle mode in the same direction, while maximizing damping compensation to prevent the trailer from becoming further unstable.

[0049] Step S6: Collect the actual rotation angle and yaw response, obtain the lateral deviation, and iteratively optimize the rotation angle allocation and compensation parameters.

[0050] Finally, the VCU can collect the actual steering angles of the front and rear wheels, the actual motor current, the actual yaw rate of the tractor and trailer, and the lateral position deviation via the ADC and CAN bus. By comparing the actual lateral deviation and yaw response with the target values, an error vector is formed. Thus, the VCU performs online iterative correction of the interpolation factor in the steering angle allocation MAP and the adaptive parameters in the dual compensation model within a 1ms cycle. For example, if the actual yaw rate is detected to be higher than the target value and the trailer swaying intensifies in several consecutive control cycles, the attenuation coefficient of the target steering angle of the rear wheels is fine-tuned in the next control cycle, and the damping compensation reference value is increased, forming a closed-loop self-learning optimization.

[0051] Regarding the emergency obstacle avoidance mentioned above, this invention proposes an ultra-fast response process. When the VCU receives an emergency obstacle avoidance command from the intelligent driving domain, it immediately interrupts the conventional logic of steps S3 and S4 and enters a dedicated obstacle avoidance control process: The VCU pre-allocates an independent Cortex-M7 core partition, RAM area, and dedicated ADC and PWM channels for emergency obstacle avoidance at the hardware level; the raw sensor signals directly enter this core partition through the dedicated ADC, without being transmitted via the CAN bus; the VCU runs the obstacle avoidance algorithm with the highest interrupt priority, and simultaneously outputs commands to the front and rear wheel steering actuators through the dedicated PWM channels. According to actual tests, the total delay from the obstacle avoidance command to the issuance of the execution command can be controlled within 5ms. Moreover, during the obstacle avoidance process, the front wheels perform emergency steering, while the rear wheels dynamically limit the steering angle based on the trailer's stability boundary. If necessary, it can also be linked with ESP to provide single-side differential braking assistance to the trailer, so as to complete obstacle avoidance and maintain vehicle stability in a very short time.

[0052] Finally, it can be added that in some other preferred embodiments of the present invention, a fault classification and fault tolerance mechanism is also provided. Specifically, the VCU monitors the working status and fault codes of the front wheel steering system, rear wheel steering system, friction compensation unit, and damping compensation unit in real time, and then classifies them into four levels according to the degree of fault impact: minor faults are only recorded and not downgraded; moderate faults, such as the failure of a single-channel compensation unit, are compensated by adjusting the front and rear wheel steering angle distribution, and the function remains normal; severe faults, such as the failure of the rear wheel steering, are addressed by increasing the front wheel steering angle and calling the differential braking function to apply selective braking torque on the trailer side to generate yaw moment to assist steering, while limiting vehicle speed; and, in the case of fatal faults, such as complete rear wheel steering jamming, the VCU immediately triggers the highest safety strategy, limits the front wheel steering angle rate, maximizes damping to suppress oscillation, and links the power system to reduce torque and control the vehicle to slow down and stop.

[0053] In summary, the lateral control for intelligent driving of heavy-duty trucks proposed in this invention achieves the organic unity of front and rear wheel coordination, dual compensation linkage, trailer posture control and vehicle energy optimization under unified timing and task scheduling, significantly improving the safety, economy and reliability of lateral control for intelligent driving of heavy-duty trucks.

[0054] In this invention, when directional terms are mentioned, they are relative concepts based on the embodiments. Furthermore, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects have an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0055] The above description of the structure, features, and effects of the present invention is based on the embodiments shown in the figures. However, the above are only preferred embodiments of the present invention. It should be noted that the technical features involved in the above embodiments and their preferred methods can be reasonably combined and matched by those skilled in the art to form a variety of equivalent solutions without departing from or changing the design concept and technical effects of the present invention. Therefore, the present invention is not limited to the scope of implementation shown in the figures. Any changes made in accordance with the concept of the present invention, or modifications to equivalent embodiments, that do not exceed the spirit covered by the specification and figures, should be within the protection scope of the present invention.

Claims

1. A lateral control method for the central control unit of a vehicle controller for intelligent driving of heavy-duty trucks, characterized in that, include: In the vehicle controller, build and store the front and rear wheel steering angle basic distribution MAP, the steering system global friction compensation MAP, and the damping compensation MAP for heavy trucks under different driving scenarios. The system acquires target driving trajectory information issued by the intelligent driving domain controller in real time and collects vehicle status signals, which include at least vehicle speed, tractor yaw rate, trailer yaw rate, steering actuator status, and road surface adhesion coefficient. The vehicle controller acquires the intelligent driving domain function status and vehicle speed signal, and after identifying the current driving scenario by combining the road adhesion coefficient, it calls the corresponding front and rear wheel steering angle basic allocation MAP, and calculates the front and rear wheel target steering angle and steering phase difference by combining the vehicle status signal; The vehicle controller calls the steering system's full-domain friction compensation MAP and damping compensation MAP, and calculates the friction compensation amount based on the current steering conditions, as well as the damping compensation amount based on vehicle speed and steering requirements. The vehicle controller superimposes the target steering angle, friction compensation amount, and damping compensation amount to generate front wheel steering execution commands and rear wheel steering execution commands, and outputs them to the front wheel steering actuator and the rear wheel steering actuator respectively; The vehicle controller collects the actual steering angle and vehicle yaw response after execution, and iteratively corrects the steering angle allocation and compensation amount based on the target trajectory and the actual lateral deviation.

2. The lateral control method for the vehicle controller hub of the intelligent driving system for heavy-duty trucks according to claim 1, characterized in that, When in a low-adhesion road surface scenario, the vehicle controller calculates the target steering angle and steering phase difference between the front and rear wheels, using the optimal tire lateral force as a constraint to limit the sum of the steering angles of the front and rear wheels, and actively reduces the steering angle of the rear wheels when the difference in yaw rate between the tractor and the trailer exceeds a predetermined threshold.

3. The lateral control method for the vehicle controller hub of the intelligent driving system for heavy-duty trucks according to claim 1, characterized in that, The friction compensation calculation method includes: the vehicle controller calls the friction compensation MAP in real time to obtain the basic friction compensation value based on the steering angular velocity and rack displacement velocity, and superimposes the positive or negative vibration parameters of the preset frequency to drive the front wheel and rear wheel steering mechanisms to overcome static friction synchronously.

4. The lateral control method for the vehicle controller center of the intelligent driving system for heavy-duty trucks according to claim 3, characterized in that, When a heavy truck is detected to be braking on a long downhill slope, the VCU increases the friction compensation response speed to compensate for the drift in friction characteristics caused by temperature changes.

5. The lateral control method for the central control unit of a vehicle controller for intelligent driving of heavy-duty trucks according to any one of claims 1 to 4, characterized in that, The lateral control method also includes an emergency obstacle avoidance response step: when the vehicle controller receives an emergency obstacle avoidance command, it immediately interrupts the control logic that calculates the target steering angle and steering phase difference of the front and rear wheels, calculates the friction compensation amount, and calculates the damping compensation amount, and starts the preset hardware channel and the highest interrupt priority task: The vehicle controller directly acquires steering sensor signals through a dedicated ADC interface and directly drives the steering actuator through a dedicated PWM channel to instantly complete the calculation and distribution of obstacle avoidance steering commands.

6. The lateral control method for the central control unit of a vehicle controller for intelligent driving of heavy-duty trucks according to any one of claims 1 to 4, characterized in that, The lateral control method also includes a fault-level tolerance step: the vehicle controller monitors the status of the front wheel steering system, rear wheel steering system, friction compensation unit and damping compensation unit in real time. When any system or unit fails, a fault-tolerance strategy is executed according to the predetermined fault level. This includes: if the rear wheel steering fails, the vehicle controller increases the front wheel steering angle and links the trailer braking system to perform differential braking in order to maintain lateral tracking capability.

7. The lateral control method for the central control unit of a vehicle controller for intelligent driving of heavy-duty trucks according to any one of claims 1 to 4, characterized in that, When the vehicle controller generates the rear wheel steering command, it introduces trailer stability constraints: based on the difference between the trailer's yaw rate and the tractor's yaw rate, it corrects the rear wheel steering phase. When the difference exceeds the safety threshold, the rear wheel steering is forced into a small-angle mode in the same direction to suppress trailer sway.

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