Abstract—This study has investigated a vehicle lumped parameter model (LPM) in frontal crash. There are several ways for determining spring and damper characteristics and type of problem shall be considered as system identification. This study use genetic algorithm (GA) procedure, being an effective procedure in case of optimization issues, for optimizing errors, between target data (experimental data) and calculated results (being obtained by analytical solving). In this study analyzed model in 5-DOF then compared our results with 5-DOF serial model. In this paper, the solution method of crash equations for lumped parameter is investigated in discrete analysis method and presented a general solution with the help of numerical solution.
Index Terms—Vehicle, Lumped-parameter model, Genetic algorithm, Optimization, System identification.
J. Marzbanrad is assistant professor in School of Automotive Engineering, Iran University of Science and Technology, 16846-13114, Tehran, Iran (corresponding author to provide phone: +98-21-77240-3981;fax:+982173228981;E-mail:marzban@iust.ac.ir,Tehra n, Iran
M. Pahlavani is MS graduate of Iran University of Science and Technology, Tehran, Iran. He is now teaching some courses in Automotive fields. (E-mail: pahlavani.s@gmail.com).
Cite: Javad Marzbanrad and Mostafa Pahlavani, "A System Identification Algorithm for Vehicle Lumped Parameter Model in Crash Analysis," International Journal of Modeling and Optimization vol. 1, no. 2, pp. 163-168, 2011.
Copyright © 2008-2024. International Journal of Modeling and Optimization. All rights reserved.
E-mail: ijmo@iacsitp.com