Yaw Moment Control via Emotional Adaptive Neuro-Fuzzy Controller for Independent Rear Wheel Drives of an Electric Vehicle

Abstract

This paper, investigates the traction control of an electric vehicle (EV) that is equipped with two electric drives. A new yaw moment control scheme via an Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed. The ANFIS is an attractive compromise between the adaptability of a neural network and interpretability of a fuzzy inference system. In a 2WD EV because of independent torque control of the motors, simultaneous torque control of several drive motors is the main objective.  So due to nonlinear vehicle model and parameters variations, an intelligent controller on base ANFIS, using emotional learning is presented and is used for tracking the reference yaw rate. The designed controller calculates the reference torque of electric drives. By this way, mechanical differential is eliminated and its operation is done electronically. Because of large magnitude of control effort, assistance brake control also is applied to limit the control effort value. Various simulations with a full nonlinear and uncertain 7-DOF vehicle model show that the proposed controller enhances the vehicle performance and stability.