Abstract

In this paper a hierarchically structured framework is proposed for the time-optimal trajectory planning and control of autonomous electric vehicles with state and input constraints for fixed test paths. The time-optimal reference signals are obtained by solving a dynamic nonlinear optimal control problem associated with the kinematic model of the vehicle using direct discretization and multiple shooting method. The high-level control ensures that the deviations from the reference trajectories are minimized, while the low-level control computes the necessary torques required for the electric motors to produce the optimal motion. The efficiency of the control system is verified by simulation under realistic performance characteristics and accurate 16 degree-of-freedom nonlinear model of the electric vehicle.

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