Vehicle Side Slip Angle Observation with Road Friction Adaptation

Chi Jin, Liang Shao, Cornelia Lex, Arno Eichberger

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung


Side-slip angle is an important variable indispensable for some advanced automotive vehicle control systems. However, due to technical and economic reasons, this variable is often estimated rather than directly measured. In this paper we address the observer design problem for estimating the side-slip angle and the unknown road friction coefficient, based on measured signals from sensors common to modern series-production automobiles. We formulate state and parameter estimation as a non-convex optimization problem. By interweaving discrete time solution of the optimization and continuous integration of sensor data, our scheme allows for sufficient time for finding the global optima approximately through a grid-search. Consequently, despite the non-convex optimization we are facing, our observation scheme is able to run in real time. We show some desirable properties of the proposed scheme concerning the stability and convergence of estimation error. One advantage of our observer is that for the nominal model the estimation error does not grow even when the system lacks observability. Simulation shows that the proposed observer provides very accurate estimation in challenging scenarios where the vehicle executes extreme maneuvers and measured signals are corrupted by noise.
Titel20th IFAC World Congress
Herausgeber (Verlag)Elsevier B.V.
ISBN (elektronisch)2405-8963
PublikationsstatusVeröffentlicht - 2017
VeranstaltungThe 20th World Congress of the International Federation of Automatic Control - Pierre Baudis Congress Center, Toulouse, Frankreich
Dauer: 9 Juli 201714 Juli 2017




KonferenzThe 20th World Congress of the International Federation of Automatic Control
KurztitelIFAC World Congress 2017

ASJC Scopus subject areas

  • Fahrzeugbau

Fields of Expertise

  • Mobility & Production

Treatment code (Nähere Zuordnung)

  • Basic - Fundamental (Grundlagenforschung)


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