Robust road friction estimation during vehicle steering

Liang Shao, Chi Jin, Cornelia Lex, Arno Eichberger

Publikation: Beitrag in einer FachzeitschriftArtikelForschungBegutachtung

Abstract

Automated vehicles require information on the current road condition, i.e. the tyre–road friction coefficient for trajectory planning, braking or steering interventions. In this work, we propose a framework to estimate the road friction coefficient with stability and robustness guarantee using total aligning torque in vehicle front axle during steering. We first adopt a novel strategy to estimate the front axle lateral force which performs better than the classical unknown input observer. Then, combined with an indirect measurement based on estimated total aligning torque and front axle lateral force, a non-linear adaptive observer is designed to estimate road friction coefficient with stability guarantee. To increase the robustness of the estimation result, criteria are proposed to decide when to update the estimated road conditions. Simulations and experiments under various road conditions validate the proposed framework and demonstrate its advantage in stability by comparing it with the method utilising the wide-spread Extended Kalman Filter.
Originalspracheenglisch
Aufsatznummerhttps://doi.org/10.1080/00423114.2018.1475678
Seitenumfang27
FachzeitschriftVehicle system dynamics
DOIs
PublikationsstatusVeröffentlicht - 22 Mai 2018

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Front axles
Friction
Torque
Extended Kalman filters
Braking
Trajectories
Planning
Experiments

Schlagwörter

    ASJC Scopus subject areas

    • !!Engineering(all)

    Fields of Expertise

    • Mobility & Production

    Dies zitieren

    Robust road friction estimation during vehicle steering. / Shao, Liang; Jin, Chi; Lex, Cornelia; Eichberger, Arno.

    in: Vehicle system dynamics, 22.05.2018.

    Publikation: Beitrag in einer FachzeitschriftArtikelForschungBegutachtung

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    abstract = "Automated vehicles require information on the current road condition, i.e. the tyre–road friction coefficient for trajectory planning, braking or steering interventions. In this work, we propose a framework to estimate the road friction coefficient with stability and robustness guarantee using total aligning torque in vehicle front axle during steering. We first adopt a novel strategy to estimate the front axle lateral force which performs better than the classical unknown input observer. Then, combined with an indirect measurement based on estimated total aligning torque and front axle lateral force, a non-linear adaptive observer is designed to estimate road friction coefficient with stability guarantee. To increase the robustness of the estimation result, criteria are proposed to decide when to update the estimated road conditions. Simulations and experiments under various road conditions validate the proposed framework and demonstrate its advantage in stability by comparing it with the method utilising the wide-spread Extended Kalman Filter.",
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