A layered roll stability control strategy for commercial vehicles based on adaptive model predictive control
Chenyu Zhou, Liangyao Yu, Yong Li, Zheng‐Hong Lu, Jian Song
Abstract
Due to the high centre of mass, commercial vehicles are prone to ultimate rollover under extreme steering conditions. The rollover of commercial vehicles leads to serious traffic accidents and poses a threat to road traffic. In this paper, the mechanism of vehicle rollover is revealed by static equilibrium and phase plane analysis. Meanwhile, a robust roll angle observer is designed by combining Kalman filter and sliding mode observation. Considering the influence of wheel lifting on roll dynamics, a novel layered control strategy is proposed by employing engine torque limit, differential braking and active front-wheel steering. Moreover, the layered control of roll stability is realised by adaptive model predictive control with time-varying weights and constraints. To verify the validity and reliability of the proposed algorithm, the hardware-in-loop tests under typical driving conditions have been carried out. The results show that the proposed method can effectively restrain the divergence of roll state and prevent vehicle rollover.