Predictive and Bounded Reference Generation of the Actuators of Four-wheel Drive and Four-wheel Steer Vehicles

Abstract

Vehicles with four-wheel drive and four-wheel steer technology represent an innovative approach tackling upcoming issues of urban societies. With the need for a higher maneuverability, due to less parking space and increasing traffic, together with continuous development of autonomous driving, such vehicles are promising concepts. In order to contribute towards this progression, an optimal, predictive and bounded non heuristic reference generation of the wheels rotational speeds and steering angles maintaining the degrees of freedom is posed. Within a cascaded motion control structure, this reference generation implicitly considers the optimal force distribution given by the implemented control allocation and the vehicles velocity control reference signals. Hereby, the optimal reference generation takes the actuator dynamics as well as box constraints, due to limited construction space of the mechatronic suspension system, of the steering angles into account. Dependent on the vehicle's propulsion, the wheel's rotational speed can be considered bounded as well. Compared with a state of the art setpoint generation, the posed model predictive feed forward structure is tested in simulation with the double lane change and an unconventional parking maneuver. The presented algorithm is applicable for similar multi wheeled dynamic systems like robots.