Parameter Identification of LuGre Tire Model for the Simplified Motion Dynamics of a Quarter-vehicle Model Based on Ant Colony Algorithm

Author

Han, Jiapeng ; Sun, Yongli ; Wang, Yanyang

Author_Institution

Shandong Univ. of Technol., Zibo

fYear

2007

fDate

18-21 Aug. 2007

Firstpage

3039

Lastpage

3043

Abstract

In light of the high nonlinearity of LuGre friction model, a novel method based on ant colony algorithm (ACA) for identifying the friction parameters of LuGre tire model is proposed. ACA is a parallelized bionic optimization algorithm inspired from the behavior of real ants, and a kind of positive feedback mechanism is adopted in ACA. On the basis of brief introduction of LuGre friction model, a method for identifying the static LuGre friction parameters and the dynamic LuGre friction parameters using ACA is derived. Finally, this new friction parameter identification scheme is applied to the simplified motion dynamics of a quarter-vehicle model with high precision. Simulation and application results verify the feasibility and the effectiveness of the scheme. It provides a new way to identify the friction parameters of LuGre tire model.

Keywords

friction; optimisation; parameter estimation; tyres; vehicle dynamics; LuGre tire model; ant colony algorithm; feedback mechanism; friction parameter identification scheme; motion dynamics; parallelized bionic optimization algorithm; quarter-vehicle model; Ant colony optimization; Feedback; Friction; Nonlinear dynamical systems; Parameter estimation; Road vehicles; Steady-state; Tires; Vehicle driving; Vehicle dynamics; ACA; LuGre tire model; friction; parameter identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2007 IEEE International Conference on

Conference_Location

Jinan

Print_ISBN

978-1-4244-1531-1

Type

conf

DOI

10.1109/ICAL.2007.4339103

Filename

4339103