Data-Driven Adaptive Torque Allocation for Electric Vehicles

This paper presents a preliminary study considering the design of an adaptive torque allocation policy for electric vehicles combining optimal control with data-driven techniques. The vehicle is equipped with four independent actuated wheels driven by electric motors. The policy aims to control the vehicle powertrain by allocating available power among motors to satisfy the driver control torque request and adjust torque allocated to different motors according to estimated wheels slip ratio change due to terrain varying conditions. A constrained optimal torque allocation algorithm is designed to distribute available power among wheels. In order to adjust the power allocation result, a data-driven adaptive policy is designed to adjust the control allocation parameters and the torque distribution reflecting wheel's operating conditions. The combination of torque allocation and data-driven adaptation policies permits the adjustment of the allocated power according to the wheel/road contact conditions. The algorithm has been tested and validated in simulation, showing the improvement given by the proposed approach compared with respect to the control system neglecting the data-driven adaptation of the torque allocation policy.