Parameter and state estimation for articulated heavy vehicles

Abstract

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.

Keywords:

• parameter estimation
• state estimation
• Kalman filter
• dual extended Kalman filter
• articulated vehicle

Acknowledgements

The authors would like to acknowledge the members of the Cambridge Vehicle Dynamics Consortium, who supported the work in this article. At the time of writing the members were: ArvinMeritor, Camcon, Denby Transport, Firestone Industrial Products, Fluid Power Design, FM Engineering, Fruehauf, Goodyear Tires, Haldex Brake Products, Intec Dynamics, Mektronika Systems, MIRA Limited, Qinetiq, Shell UK Ltd, Tinsley Bridge Ltd, and Volvo Global Trucks. Thanks also to Dr Richard Roebuck, Dr Andrew Odhams, and Mr Jonathan Miller for their assistance with the project.