Robust road friction estimation during vehicle steering

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, the authors propose a framework to estimate the road friction coefficient with stability and robustness guarantee using total aligning torque in vehicle front axle during steering. They 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.

• Record URL:
  • https://doi.org/10.1080/00423114.2018.1475678
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00423114
• Supplemental Notes:
  • © 2018 Informa UK Limited, trading as Taylor & Francis Group. Abstract republished with permission of Taylor & Francis.
• Authors:
  • Shao, Liang
  • Jin, Chi
  • Lex, Cornelia
  • Eichberger, Arno
• Publication Date: 2019-4

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 493-519
• Serial:
  • Vehicle System Dynamics
  • Volume: 57
  • Issue Number: 4
  • Publisher: Taylor & Francis
  • ISSN: 0042-3114
  • EISSN: 1744-5159
  • Serial URL: https://www.tandfonline.com/toc/nvsd20/current

Subject/Index Terms

• TRT Terms: Active safety systems; Adaptive control; Axle loads; Friction; Intelligent vehicles; Kalman filtering; Rolling contact
• Uncontrolled Terms: Road conditions
• Subject Areas: Highways; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01699023
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 20 2019 10:39AM