Enhanced Traction Control on Irregular Roads through Preview-based Nonlinear Model Predictive Control

Upcoming V2X technologies and on-board perception systems will provide real-time information from multiple sources, such as other vehicles and the surrounding environment, and thus enable the implementation of innovative active safety control functions. This paper investigates the benefit of the preview on the road irregularities on the tire slip control performance of a traction control system for electric vehicles. To this purpose, a nonlinear model predictive controller (NMPC) for traction control is presented, which concurrently uses the information on the tire-road friction factor and upcoming road profile. The simulation results across multiple road scenarios-including comparisons with state-of-the-art benchmarking controllers-highlight the significant improvements brought by the proposed preview-based NMPC, including its robustness with respect to model uncertainties and inaccuracies in the preview information. Preliminary proof-of-concept experiments on an electric vehicle prototype with an on-board powertrain demonstrate the real-time implementability of the algorithm, and confirm the potential of the proposed control solution.