A robust real-time estimation of the dynamic normal reaction for an open-link locomotion module with an E-drive

Real-time information on the wheel static and dynamic normal reaction on various road and terrain conditions is extremely important for agile tyre dynamics to improve vehicle mobility. This article proposes a novel approach for reliable and real-time estimation of the dynamic normal reaction of an open-link locomotion module, as an essential constituent of electric vehicles. Nonlinear normal dynamics, including stochastic behaviour of suspension and nonlinearity of damping force caused by the terrain profile and damper design is considered. Robustness performance of the proposed approach is proved based on input-to-state stability theory. As demonstrated, the proposed approach is robust against model parameter uncertainties, and can keep the estimation error within the assigned boundaries. The proposed approach is indifferent to variation of the stiffness and damping coefficients of the tyre-surface patch and thus is applicable to different terrains. The approach was implemented in a new design of a sliding mode observer. A design method of the observer gains is also presented and numerical values of the gains are determined with application to the locomotion module. The estimation accuracy of the wheel normal reaction on different terrains and the robustness against parameter uncertainties are validated. Computational results confirm the real-time performance and effectiveness of the proposed observer design.

• Record URL:
  https://doi.org/10.1080/00423114.2019.1627468
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00423114
• Supplemental Notes:
  • © 2019 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Zhao, Linhui
  • 0000-0003-3385-9340
  • Vantsevich, Vladimir V
• Publication Date: 2020-9

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 1451-1476
• Serial:
  • Vehicle System Dynamics
  • Volume: 58
  • Issue Number: 9
  • Publisher: Taylor & Francis
  • ISSN: 0042-3114
  • EISSN: 1744-5159
  • Serial URL: https://www.tandfonline.com/toc/nvsd20/current

Subject/Index Terms

• TRT Terms: Electric drives; Electric vehicles; Motor vehicle dynamics; Real time information; Rolling contact; Sliding mode control; Stability analysis; Terrain; Wheels
• Subject Areas: Energy; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01751017
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 31 2020 5:41PM