A Direct Yaw-Moment Control (DYC) logic for a rear-wheel-drive electric-powered vehicle is proposed. The vehicle is a Formula SAE (FSAE) type race car, with two electric motors powering each rear wheel. Vehicle baseline balance is neutral at low speeds, for increased maneuverability, and increases understeering at high speeds (due to the aerodynamic configuration) for stability. A controller that can deal with these yaw response variations, modelling uncertainties, and vehicle nonlinear behavior at limit handling is proposed. A two-level control strategy is considered. For the upper level, yaw rate and sideslip angle are considered as feedback control variables and a cubic-error Proportional Derivative (PD) controller is proposed for the feedback control. For the lower level, a traction control algorithm is used, together with the yaw moment requirement, for torque allocation. Performance of the controller was evaluated using the Sine with Dwell maneuver and also a lap time simulation around a racetrack. A physically existing go-kart track is modelled for this purpose. Track and vehicle models are built using IPG CarMaker, and a control algorithm is implemented in MATLAB Simulink. Simulations are performed using IPG Racing Driver, varying the learning rate toward aggressive driving and increasing the combined acceleration target, to achieve the best lap times. Simulations results demonstrate the proposed DYC logic using the PD cubic controller substantially improves the simulated vehicle stability on the Sine with Dwell test and around the racetrack. Furthermore, the implementation of the controllers enables a gain of approximately 2 s over a 37 s lap time on the racetrack and allows a more aggressive driving style. As simulations are performed using a driver model, this gain in stability and speed might apply to either a human-operated or autonomous race car. Moreover, the controller could be used in a passenger vehicle, enhancing its safety and maneuverability.
