A comparative study on Optimal Control based torque vectoring systems

Electric vehicles (EVs) allow the implementation of multi-motor powertrains. These topologies allow to control the torque exerted in each active wheel of the vehicle, and thus, can naturally implement yaw moment control approaches such as Torque Vectoring, which improve vehicle stability and cornering response. Among the different control techniques proposed for this purpose, due to the recent improvement in computation power of embedded devices, optimal control based solutions have become one of the most promising alternatives. Hence, in this paper the performance of three different optimal based torque vectoring algorithms (Linear Quadratic Regulator, Linear Time-Variant Model-based Predictive Control and Nonlinear Model-based Predictive Control) are proposed, studied and comprehensively compared.