Anti-lock braking control design using a nonlinear model predictive approach and wheel information

Since several decades anti-lock braking systems rely on rule-based control strategies. Extensive literature review highlighted the possibility that significant improvements could be achieved if ABS controllers were redesigned taking advantage of the technological improvements achieved in the last decade. This work aims to verify this statement and quantifying the potential improvement by design of a novel ABS algorithm. The controller, based on state-of-the-art hardware, uses a Model Predictive Control (MPC) approach and potentially available wheel information as the pillars of its design. The newly proposed ABS is then tested on Toyota's high-end vehicle simulator and benchmarked against its industrial counterpart. A comprehensive set of manoeuvres, including friction jumps and rough road braking scenarios, is deployed to assess performance and robustness of the presented design. The analysis showed substantial reduction of the braking distance and improved steering-ability. Furthermore, robustness against external factors is demonstrated to be comparable with the industrial benchmark.