Model Predictive torque vectoring control for electric vehicles near the limits of handling

摘要

In this paper we propose a 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 is employed to find reference steady-state cornering conditions as well as to design a linear Model Predictive Control (MPC) 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. After analysing the relative trade-offs between performance and computational effort for the MPC strategy, we validate the controller and compare it against a simpler unconstrained optimal control strategy in a high fidelity simulation environment.