Joint Identification Method of Extended Kalman Filter and Cascaded Flatness-Based Observer for Lateral Tire-Road Friction of Motorcycle

  • Yang Chen
  • , Ke Bao*
  • , Yang Deng*
  • , Yiyong Sun
  • , Bin Liang
  • , Weining Lu
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the realm of motorcycle extreme sports, wheel-ground friction significantly influences vehicle safety. This study presents a robust and precise method for identifying motorcycle tire friction by leveraging an advanced observation scheme. The proposed observer combines cascaded flatness-based observer and extended Kalman filter, employs a robust fixed-time exact differentiator to estimate the first- and second-order derivatives of the signal. This approach ensures adaptability to environmental parameter variations while effectively attenuating measurement noise and external disturbances. The robustness and accuracy of the proposed method are validated through simulations on the BikeSim platform, incorporating external shock disturbances and varying road conditions.

Original languageEnglish
Title of host publicationIECON 2025 - 51st Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
ISBN (Electronic)9798331596811
DOIs
Publication statusPublished - 2025
Externally publishedYes
Event51st Annual Conference of the IEEE Industrial Electronics Society, IECON 2025 - Madrid, Spain
Duration: 14 Oct 202517 Oct 2025

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
ISSN (Print)2162-4704
ISSN (Electronic)2577-1647

Conference

Conference51st Annual Conference of the IEEE Industrial Electronics Society, IECON 2025
Country/TerritorySpain
CityMadrid
Period14/10/2517/10/25

Keywords

  • Cascaded Flatness
  • Extended Kalman Filter
  • Lateral Tire Road Friction

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