Skip to main navigation Skip to search Skip to main content

Vehicle parameters identification with particle swarm optimisation for four wheel independent motor-drive vehicle

  • Hongliang Zhou*
  • , Zhiyuang Liu
  • , Xingwang Yang
  • , Levent Güvenç
  • *Corresponding author for this work
  • Harbin Institute of Technology
  • China First Automotive Works Group Corporation Research and Design Center
  • Ohio State University

Research output: Contribution to journalArticlepeer-review

Abstract

An identification method for vehicle dynamics parameters which is based on particle swarm optimisation (PSO) is presented in this paper for a four wheel independent motor-drive (4WIMD) vehicle. The identification process consists of two steps. In the first step, wheel rotational dynamic and static resistance coefficients are identified using field test data of motor torque and wheel speed. In the second step, a nonlinear vehicle dynamics model with vehicle longitudinal and lateral dynamics, wheel dynamics model and tyre characteristics, and the parameters related to vehicle body and the tyre are identified with the test data of motor torque, accelerations, yaw rate and wheel speeds. The model outputs and test data are compared and the parameters show acceptable accuracy. A benchmarking study using a commercially available optimisation routine for the same parameter identification task is carried out and the PSD method presented here is observed to be much more accurate.

Original languageEnglish
Pages (from-to)127-142
Number of pages16
JournalInternational Journal of Vehicle Design
Volume79
Issue number2-3
DOIs
StatePublished - 2019

Keywords

  • 4WIMD
  • Four wheel independent motor-drive vehicle
  • PSD
  • Parameter identification
  • Particle swarm optimisation

Fingerprint

Dive into the research topics of 'Vehicle parameters identification with particle swarm optimisation for four wheel independent motor-drive vehicle'. Together they form a unique fingerprint.

Cite this