Parameter and state estimation for articulated heavy vehicles

This article discusses algorithms to estimate parameters and states of articulated heavy vehicles. First, 3- and 5-degrees-of-freedom linear vehicle models of a tractor semitrailer are presented. Vehicle parameter estimation methods based on the dual extended Kalman filter and state estimation based on the Kalman filter are presented. A program of experimental tests on an instrumental heavy goods vehicle is described. Simulation and experimental results showed that the algorithms generate accurate estimates of vehicle parameters and states under most circumstances.

• Record URL:
  • https://doi.org/10.1080/00423110903406656
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00423114
• Supplemental Notes:
  • © 2011 Taylor and Francis Group, LLC. Abstract republished with permission of Taylor & Francis.
• Authors:
  • Cheng, Caizhen
  • Cebon, David
• Publication Date: 2011-2

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 399-418
• Serial:
  • Vehicle System Dynamics
  • Volume: 49
  • Issue Number: 1-2
  • Publisher: Taylor & Francis
  • ISSN: 0042-3114
  • EISSN: 1744-5159
  • Serial URL: https://www.tandfonline.com/toc/nvsd20/current

Subject/Index Terms

• TRT Terms: Algorithms; Degrees of freedom; Estimating; Heavy duty vehicles; Kalman filtering; Mathematical models; Tractor trailer combinations
• Uncontrolled Terms: Articulated vehicles; Parameter estimation
• Subject Areas: Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01676756
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 26 2018 2:42PM