No abstract

No abstract

The real-time change of tire-road friction coefficient is one of the important factors that influence vehicle safety performance. Besides, the vehicle wheels' locking up has become an important issue. In order to solve these problems, this paper comes up with a novel slip control of electric vehicle (EV) based on tire-road friction coefficient estimation. First and foremost, a novel method is proposed to estimate the tire-road friction coefficient, and then the reference slip ratio is determined based on the estimation results. Finally, with the reference slip ratio, a slip control based on model predictive control (MPC) is designed to prevent the vehicle wheels from locking up. In this regard, the proposed controller guarantees the optimal braking torque on each wheel by individually controlling the slip ratio of each tire within the stable zone. Theoretical analyses and simulation show that the proposed controller is effective for better braking performance.

No abstract

No abstract

No abstract

No abstract

This study proposes a linear time-varying model predictive control method based on tire state stiffness prediction for the path tracking using a steering decision sequence in a prediction horizon. A nonlinear UniTire model is employed to represent the nonlinear features of vehicle dynamics in critical situations. And the changing trend of tire state stiffness over the prediction horizon is constructed based on the steering decision sequence, which is the optimized solution of the previous execution step by the controller. Moreover, a method of adjusting the tire state stiffness is proposed to address the jittering in the process of linearization. Meanwhile, a nonlinear model predictive controller and a traditional linear timevarying model predictive controller are designed to verify the effectiveness of the proposed linearization method. Experimental results clearly show that this linearization method can considerably improve vehicle stability under extreme conditions.INDEX TERMS path tracking, tire state stiffness, model predictive control, vehicle dynamics.