Survey on Wheel Slip Control Design Strategies, Evaluation and Application to Antilock Braking Systems

Journal article (2020)

Authors

L. Ferranti Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
Giovanni Berardo Toyota Motor Europe
Valentin Ivanov Ilmenau University of Technology
B. Shyrokau Intelligent Vehicles - Mechanical, Maritime and Materials Engineering
Research Group
Learning & Autonomous Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2020 Francesco Pretagostini, L. Ferranti, Giovanni Berardo, Valentin Ivanov, B. Shyrokau
DOI: https://doi.org/10.1109/ACCESS.2020.2965644
Model predictive control Vehicle safety Road vehicles Antilock braking system Wheel slip control
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Published Date

2020

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Learning & Autonomous Control

Abstract

Since their introduction, anti-lock braking systems (ABS) have mostly relied on heuristic, rule-based control strategies. ABS performance, however, can be significantly improved thanks to many recent technological developments. This work presents an extensive review of the state of the art to verify such a statement and quantify the benefits of a new generation of wheel slip control (WSC) systems. Motivated by the state of the art, as a case study, a nonlinear model predictive control (NMPC) design based on a new load-sensing technology was developed. The proposed ABS was tested on Toyota's high-end vehicle simulator and was benchmarked against currently applied industrial controller. Additionally, a comprehensive set of manoeuvres were deployed to assess the performance and robustness of the proposed NMPC design. The analysis showed substantial reduction of the braking distance and better steerability with the proposed approach. Furthermore, the proposed design showed comparable robustness against external factors to the industrial benchmark.