Predictive rear wheel torque vectoring control with terminal understeer mitigation using nonlinear estimation

In this paper we propose a fully implementable constrained optimal control architecture to stabilize a vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are employed to find reference steady-state cornering conditions and to design a linear Model Predictive Control strategy using the rear wheels' slip ratios as input. A Sliding Mode Slip Controller then calculates the necessary motor torques according to the requested wheel slip ratios. The controller is coupled with a continuous-discrete Unscented Kalman Filter and the combined solution is validated in a high fidelity simulation environment, assuming that no additional sensors than the ones found in standard vehicles are available.