ABSTRACT For four-wheel independently driven in-wheel motors electric vehicle, an integrated control algorithm of active front steering and direct yaw moment control based on model predictive control is proposed in this paper. The algorithm adopts hierarchical integrated control structure. The model predictive controller is designed and the driving force allocation is controlled by rules. The algorithm is verified by the simulation at last. The results show that the algorithm can make the vehicle track the desired response effectively and enhance the vehicle stability in critical running condition. INTRODUCTION Four-wheel independently driven in-wheel motors electric vehicle is easy to achieve direct yaw moment control (DYC) through controlling motor torque. In-wheel motors can generate driving torque quickly, accurately and independently. Motor drive DYC is achieved more directly and easier compare to the active brake DYC [ 1]. There was some research on four-wheel independently driven electric vehicle DYC in recent years [ 2,3,4,5]. Vehicle active front steering (AFS) generates compensated yaw moment to ensure the stability of the vehicle by changing the tires' lateral forces and it has certain advantages compare to the DYC in ride comfort. It is very good to play the respective advantages and eliminate the interference when the AFS and DYC are all in the vehicle. AFS and DYC integrated control of four-wheel independently driven in-wheel motors electric vehicle has become one of the important integrated chassis control research. For traditional vehicle, some methods have solved the integration control of AFS and DYC well and the DYC is achieved mainly by the active brake. The feed forwardcontroller and robust sub-optimal state feedback controller are designed for AFS and DYC coordination control [ 6]. Fuzzy control is adopted for active steering and active brake control integration [ 7]. The optimal guaranteed cost control is proposed for the vehicle AFS and DYC coordination stability control [ 8]. In this paper, for four-wheel independently driven in-wheel motors electric vehicle, an integrated control algorithm based on model predictive control is proposed for AFS and DYC integrated control and the DYC is achieved by the active drive. Both the vehicle yaw rate and slip angle are considered in the algorithm by adjusting the weight of the control variables and input variables to achieve on-line real- time future process prediction and optimization. The algorithm can make the vehicle track the desired response effectively and enhance the vehicle stability in critical running condition. The hierarchical integrated control structure is adopted in this paper. The model predictive controller is designed and the driving force allocation is controlled by rules. At last, the algorithm is verified by the simulation. HIERARCHICAL INTEGRATED CONTROL STRUCTURE The hierarchical integrated control structure is adopted in this algorithm as shown in Figure 1. It includes signal processing layer, integrated control layer, control allocation layer and execution layer. The driver maneuvering signal and the vehicle speed signal are processed in the signal processing layer. The desired response of the vehicle yaw rate γd and slip angle βd are calculated based on the reference model. The target vehicle speed Vd is calculated based on the driver maneuvering signal. The 2-DOF linear vehicle model is used as the reference model. The desired yaw rate boundary and slip angle boundary can be expressed as follows, respectively [9]: Four-Wheel Independently Driven In-Wheel Motors Electric Vehicle AFS and DYC Integrated Control2012-01-0258 Published 04/16/2012 Gang Li, Wei Hong and Heqi Liang Jilin University of China Copyright © 2012 SAE International doi:10.4271/2012-01-0258Downloaded from SAE International by Univ of California Berkeley, Saturday, August 04, 2018Where μ is the road surface friction coefficient; g is the gravity acceleration; Vx i