Optimization of active yaw control in an autonomous electric racing car

This paper shows the advantage of autonomous driving systems from testing point of view in order to enhance the performance of a racing car with respect to the use of driver assistant systems (DAS). Specifically, for the development of such systems it is necessary to perform parameter studies based on repeatable driving maneuvers. Even well trained test drivers have limited ability to achieve the required repeatability of the vehicle behavior, especially when driving at the stability limit of the vehicle. The autonomous vehicle guarantees the required position accuracy for the driving maneuvers even at high lateral acceleration with different controller settings of Active Yaw Control under real conditions. Such parameter studies are usually done using simulation tools that need very precise nonlinear tire characteristics. In this research study the Active Yaw Control was optimized using the autonomous test mode and it enhances the driving behavior in a way that a 20% higher lateral acceleration can be reached. Under-or oversteering is avoided by different wheel torques on the rear axle without compromising longitudinal dynamics.