Torque vectoring for high-performance electric vehicles: an efficient MPC calibration

In electric vehicles with in-wheel motors, torque vectoring is an effective technology to reach high-level performance in sport driving conditions. To vary the torque at each wheel while guaranteeing proper safety constraints, Model Predictive Control (MPC) has been shown to be the most suited strategy. However, MPC requires simple models and significant tuning effort to be really effective. In this paper, we propose a simple predictive greybox model of the vehicle dynamics and an efficient calibration strategy to tune the MPC cost with little additional experimental effort. Results on a full-fledged multi-body simulator complete the paper.