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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
  • *此作品的通讯作者
  • Tsinghua University
  • China North Vehicle Research Institute
  • Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

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.

源语言英语
主期刊名IECON 2025 - 51st Annual Conference of the IEEE Industrial Electronics Society
出版商IEEE Computer Society
ISBN(电子版)9798331596811
DOI
出版状态已出版 - 2025
已对外发布是
活动51st Annual Conference of the IEEE Industrial Electronics Society, IECON 2025 - Madrid, 西班牙
期限: 14 10月 2025 → 17 10月 2025

丛书

姓名IECON Proceedings (Industrial Electronics Conference)
ISSN(印刷版)2162-4704
ISSN(电子版)2577-1647

会议

会议51st Annual Conference of the IEEE Industrial Electronics Society, IECON 2025
国家/地区西班牙
市Madrid
时期14/10/25 → 17/10/25

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