Identification of linear handling models for road vehicles

Arıkan K. B., ÜNLÜSOY Y. S., Korkmaz I., Çelebi A.

Vehicle System Dynamics, vol.46, no.7, pp.621-645, 2008 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 46 Issue: 7
  • Publication Date: 2008
  • Doi Number: 10.1080/00423110701576122
  • Journal Name: Vehicle System Dynamics
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.621-645
  • Keywords: bicycle model, structural identifiability, transfer function method, parameter estimation, prediction error, genetic algorithm, DYNAMICS
  • TED University Affiliated: No


This study reports the identification of linear handling models for road vehicles starting from structural identifiability analysis, continuing with the experiments to acquire data on a vehicle equipped with a sensor set and data acquisition system, and ending with the estimation of parameters using the collected data. The model structure originates from the well-known linear bicycle model that is frequently used in handling analysis of road vehicles. Physical parameters of the bicycle model structure are selected as the unknown parameter set that is to be identified. Global identifiability of the model structure is analysed, in detail, and concluded according to various available sensor sets. Physical parameters of the bicycle model structure are estimated using prediction error estimation method. Genetic algorithms are used in the optimisation phase of the identification algorithm to overcome the difficulty in the selection of initial values for parameter estimates. Validation analysis of the identified model is also presented. The identified model is shown to track the system response successfully.