Experimental determination of tire forces and road friction

Author

Ray, Laura R.

Author_Institution

Thayer Sch. of Eng., Dartmouth Coll., Hanover, NH, USA

Volume

3

fYear

1998

fDate

21-26 Jun 1998

Firstpage

1843

Abstract

This paper presents experimental results of using extended Kalman-Bucy filtering (EKBF) and Bayesian model selection to extract tire force characteristics and road friction coefficient from measured motion of ground vehicles on smooth surfaces. The filter estimates wheel slip and slip angles, along with longitudinal and per axle lateral tire forces. Force estimates are based on vehicle-mounted sensors and are derived without knowing road conditions and without a tire force model. Force estimates are compared statistically with those that result from a nominal tire model to select the most likely friction coefficient from hypothesized values. This paper verifies tire force estimation and road friction identification using off-line processing of field test data. Results confirm applicability of the EKBF and Bayesian selection approaches

Keywords

Bayes methods; filtering theory; friction; parameter estimation; road vehicles; Bayesian model selection; extended Kalman-Bucy filtering; force estimates; identification; road friction; road vehicles; slip angles; tire forces; tire model; wheel slip; Bayesian methods; Filtering; Filters; Force measurement; Force sensors; Friction; Land vehicles; Motion measurement; Roads; Tires;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 1998. Proceedings of the 1998

Conference_Location

Philadelphia, PA

ISSN

0743-1619

Print_ISBN

0-7803-4530-4

Type

conf

DOI

10.1109/ACC.1998.707336

Filename

707336