Optimal Yaw Rate Control for Over-Actuated Vehicles

As we are heading towards autonomous vehicles, additional driver assistance systems are being added. The vehicle motion is automated step by step to ensure passengers' safety and comfort, while still preserving vehicle performance. However, simultaneous activations of concurrent systems may conflict, and non-suitable behavior may emerge. Our research work consists in proving that with the right coordination approach, simultaneous operation of different systems improve the vehicle's performance and avoid the emergence of unwanted conflicts. To prove this, we gathered different control architectures implemented in commercial passenger cars, and we compared them with our control architecture using a unified reference vehicle model. The high-fidelity vehicle model is developed in Simcenter Amesim in a modular and extensible manner. This enables adding systems in a plug-and-play way. Not only different control architectures can be tested on the same vehicle, but also different systems combinations can be evaluated. In this research, the vehicle can steer at the front and at the rear, and each wheel can be braked independently. Each of the actuators concerned can influence the vehicle's yaw rate leading in some cases in system conflicts. More complex control strategies are then implemented in Matlab/Simulink, and co-simulations are carried between both softwares in order to provide realistic results. It has been shown that optimal control allocation algorithms are more suitable to coordinate systems in an over-actuated vehicle. Moreover, if the optimization objectives are well formalized, performance, safety and comfort can be improved since the vehicle can benefit from the systems' synergies.