Integrated control of in-wheel-motored electric vehicles using a model predictive control method

A model predictive control (MPC) approach for the integrated control of active front steering (AFS), direct yaw moment control (DYC) and motor torque allocation in four in-wheel driving electric vehicles (EVs) is presented. A nonlinear vehicle model is formulated with nonlinear tire characteristic for MPC method, which can predict future system dynamics in predict horizon. And a cost function of the optimal control problem is defined over a receding horizon in order to meet the multiple control requirements taking hard constraints into account. The MPC scheme is composed of two parts: a high-level reference module related to driver steering commands, and a low-level MPC control allocation computing a sequence of control outputs to improve yaw stability performance at each sample time. The proposed controller is verified effectively on eight degrees of freedom (8DOF) nonlinear EVs model platform.