Energy-Optimal Trajectory Planning for Electric Vehicles using Model Predictive Control

Paper i proceeding, 2024

This paper proposes a space-sampled Economic Model Predictive Control (EMPC) approach to jointly minimize total energy consumption of an electric vehicle (EV) and track both longitudinal velocity and path curvature reference trajectories. We consider a single-track vehicle model constrained to the range of accelerations ± 3 m/s2, and energy consumption is modelled explicitly including power losses of electric machines. Simulations with the high-fidelity simulator IPG CarMaker show the trade-off between energy consumption and reference tracking. Namely, results show how longitudinal velocity and acceleration control significantly impact energy consumption, whereas deviating from the path centerline mainly allows better velocity tracking.