• DocumentCode
    2738437
  • Title

    Searching for a nonlinear ODE model of vehicle crash with genetic optimization

  • Author

    Horvath, András ; Hatwagner, Miklos F. ; Harmati, István Á

  • Author_Institution
    Dept. of Phys. & Chem., Szechenyi Istvan Univ., Gyor, Hungary
  • fYear
    2012
  • fDate
    24-26 May 2012
  • Firstpage
    131
  • Lastpage
    136
  • Abstract
    Vehicle crash is a very complex process, which can be modelled in details using the finite element method (FEM), but a simple, quasi-heuristic model with a limited number of parameters is often more beneficial. In this paper we propose a relatively simple dynamic model for deformation and force during a frontal collision process, which has very similar behavior to the experimental data. A genetic-type optimization of model parameters is executed on three car crash experimental data sets.
  • Keywords
    deformation; finite element analysis; genetic algorithms; nonlinear differential equations; parameter estimation; road safety; search problems; vehicle dynamics; FEM; car crash experimental data sets; dynamic deformation model; dynamic force model; finite element method; frontal collision process; genetic optimization; model parameter optimization; nonlinear ODE model searching; quasiheuristic model; vehicle crash; Elastic recovery; Force; Measurement uncertainty; Power capacitors; Springs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Computational Intelligence and Informatics (SACI), 2012 7th IEEE International Symposium on
  • Conference_Location
    Timisoara
  • Print_ISBN
    978-1-4673-1013-0
  • Electronic_ISBN
    978-1-4673-1012-3
  • Type

    conf

  • DOI
    10.1109/SACI.2012.6249990
  • Filename
    6249990