A direct yaw moment controller for a four in-wheel motor drive electric vehicle using adaptive sliding mode control. (September 2019) - Asiabar, Aria Noori; Kazemi, Reza
In this paper, a direct yaw moment control algorithm is designed such that the corrective yaw moment is generated through direct control of driving and braking torques of four in-wheel brushless direct current motors located at the empty space of vehicle wheels. The proposed control system consists of a higher-level controller and a lower-level controller. In the upper level of proposed controller, a PID controller is designed to keep longitudinal velocity constant in manoeuvres. In addition, due to probable modelling error and parametric uncertainties as well as adaptation of unknown parameters in control law, an adaptive sliding mode control through adaptation of unknown parameters is presented to yield the corrective yaw moment such that the yaw rate tracks the desired value and the vehicle sideslip angle maintains limited so as to improve vehicle handling stability. The lower-level controller allocates the achieved control efforts (i.e. total longitudinal force and corrective yaw moment) to driving or regenerative braking torques of four in-wheel motors so as to generate the desired tyre longitudinal forces. The additional yaw moment applied by upper-lever controller may saturate the tyre forces. To this end, a novel longitudinal slip ratio controller which is designed based on fuzzy logic is included in the lower-level controller. A tyre dynamic weight transfer-based torque distribution algorithm is employed to distribute the motor driving torque or regenerative braking torque of each in-wheel motor for vehicle stability enhancement. A seven degree-of-freedom non-linear vehicle model with Magic Formula tyre model as well as the proposed control algorithm are simulated in Matlab/Simulink software. Three steering inputs including lane change, double lane change and step-steer manoeuvres in different roads are investigated in simulation environment. The simulation results show that the proposed control algorithm is capable of improving vehicle handling stability and maintaining vehicle yaw stability.