关键词: 智能汽车, 主动前轮转向, 直接横摆力矩控制, 预瞄时间自适应, 协调控制, 路径跟 踪控制

Abstract: The continuous development of vehicle intelligence and electronic technology has greatly promoted the vigorous development of the automotive industry. How to improve path tracking accuracy, driving safety and stability of intelligent vehicles has become a focus of research for many automotive companies. Both Active Front-wheel Steering (AFS) and Direct Yaw-moment Control (DYC) can greatly assist in the stability performance of intelligent vehicles. AFS controls a vehicle in the yaw direction by changing the front wheel angle, while DYC applies additional longitudinal force (braking or driving force) to the wheels to improve the stability of a vehicle’s motion. However, both AFS and DYC have their limitations when controlled separately. Therefore, compared with individual control, coordinated control of AFS and DYC can fully consider the interactions between various subsystems, and has the advantages of high flexibility, good fault tolerance and high control accuracy. In this paper, a coordinated control method for intelligent vehicle path tracking based on AFS and DYC is proposed to improve the path tracking ability and driving stability of intelligent vehicles under complex road conditions. Based on a two-degree-of-freedom vehicle model and a single point preview model, the preview time is controlled to change adaptively, aiming to ensure the tracking accuracy and driving stability of the vehicle under complex road conditions; in the design of DYC controller, considering different dimensions of yaw rate and sideslip angle, a dimensionless sliding mode controller for the addition yaw moment is designed and a single wheel braking method is used to distribute the additional yaw moment to the corresponding wheel; at the same time, in order to fully utilize the working effects of AFS and DYC, the critical steering angle of the front wheels at the edge of the vehicle’s losing stability is calculated, and a weighted distribution function is used to ensure stability and smoothness of the coordinated control, while also taking ride comfort into account. Experimental simulations based on Carsim-Simulink are carried out under Fishhook and double line change conditions and compared with those under AFS and DYC control. The experimental results show that coordinated control can effectively improve the handling stability of intelligent vehicles while simultaneously meeting the accuracy of path tracking under complex road conditions, and has better robustness.