Real-Time nonlinear predictive controller design for drive-by-wire vehicle lateral stability with dynamic boundary conditions

Abstract

Due to flexible drive-by-wire technology, vehicle stability control can improve handling and lateral stability under extreme conditions. However, this technology can also increase the probability of random transmission delay. This paper proposes a nonlinear model predictive control (NMPC) strategy to improve vehicle stability and compensate for the random time delay. First, by combining the nonlinear dynamic characteristics and driver behavior, we obtain a stable region of the yaw rate and the sideslip angle under complex driving conditions. Second, an NMPC controller is designed to track the reference values in the identified stable region to improve the handling and lateral stability. Finally, the actuator receives the optimized control sequence and compensates for the random time delay of the transmission channel. CarSim/Simulink simulation and hardware-in-the-loop experiment results show that the proposed controller with dynamic boundary conditions can better track the expected value of the yaw rate and suppress the sideslip angle under low adhesion road conditions.