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Autonomous new energy heavy-duty trucks are a crucial component of the future logistics and transportation industry. However, their dynamic control becomes more challenging due to characteristics such as complex operating environments, response delays, and large inertia—yet autonomous driving systems still demand precise dynamic control performance. Addressing the issue of steering resistance with unknown and time-varying dynamics coefficients caused by complex road conditions and terrains, this study decomposes the motion control problem of new energy heavy-duty trucks by utilizing two key motion variables: longitudinal velocity and yaw rate. This paper presents an adaptive feedback control architecture for vehicle speed and steering angular velocity, based on the Model Reference Adaptive Control (MRAC) method. The strategy refers to the vehicle dynamics model, and uses the proposed adaptive control law to adjust the motor output torque in real time, so that the actual vehicle speed and angular speed can accurately track the corresponding output of the reference model. The simulation results show that the tracking performance is improved by 10% compared with the traditional PID control strategy.

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Heavy-Duty Truck Vehicle Motion Control Based on MRAC

  • 会议论文

  • 发表日期：

    2026年

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  • Yingzhe Liu,
  • Qi Zhan,
  • Shida Liu,
  • Li Wang

摘要

Autonomous new energy heavy-duty trucks are a crucial component of the future logistics and transportation industry. However, their dynamic control becomes more challenging due to characteristics such as complex operating environments, response delays, and large inertia—yet autonomous driving systems still demand precise dynamic control performance. Addressing the issue of steering resistance with unknown and time-varying dynamics coefficients caused by complex road conditions and terrains, this study decomposes the motion control problem of new energy heavy-duty trucks by utilizing two key motion variables: longitudinal velocity and yaw rate. This paper presents an adaptive feedback control architecture for vehicle speed and steering angular velocity, based on the Model Reference Adaptive Control (MRAC) method. The strategy refers to the vehicle dynamics model, and uses the proposed adaptive control law to adjust the motor output torque in real time, so that the actual vehicle speed and angular speed can accurately track the corresponding output of the reference model. The simulation results show that the tracking performance is improved by 10% compared with the traditional PID control strategy.