Mathematical modeling of a vehicle crash test based on elasto-plastic unloading scenarios of spring-mass models
This paper investigates the usability of spring which exhibit nonlinear force-deflection characteristic in the area of mathematical modeling of vehicle crash. We present a method which allows us to obtain parameters of the spring-mass model basing on the full-scale experimental data analysis. Since vehicle collision is a dynamic event, it involves such phenomena as rebound and energy dissipation. Three different spring unloading scenarios (elastic, plastic, and elasto-plastic) are covered and their suitability for vehicle collision simulation is evaluated. Subsequently we assess which of those models fits the best to the real car’s behavior not only in terms of kinematic responses but also in terms of energy distribution.
KeywordsVehicle crash Spring-mass model Unloading stiffness Coefficient of restitution Total crash energy
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- 1.Pawlus W, Nielsen JE, Karimi HR, Robbersmyr KG (2010) Mathematical modeling and analysis of a vehicle crash. In: The 4th European computing conference, Bucharest, RomaniaGoogle Scholar
- 2.Pawlus W, Nielsen JE, Karimi HR, Robbersmyr KG (2010) Development of mathematical models for analysis of a vehicle crash. WSEAS Trans Appl Theor Mech 5(2):156–165Google Scholar
- 3.Pawlus W, Nielsen JE, Karimi HR, Robbersmyr KG (2010) Further results on mathematical models of vehicle localized impact. In: The 3rd international symposium on systems and control in aeronautics and astronautics, Harbin, ChinaGoogle Scholar
- 4.Karimi HR, Robbersmyr KG (2010) Wavelet-based signal analysis of a vehicle crash test with a fixed safety barrier. In: WSEAS 4th European computing conference, Bucharest, RomaniaGoogle Scholar
- 6.Trusca D, Soica A, Benea B, Tarulescu S (2009) Computer simulation and experimental research of the vehicle impact. WSEAS Trans Comput 8(1):1185–1194Google Scholar
- 9.Harmati IA, Rovid A, Szeidl L, Varlaki P (2008) Energy distribution modeling of car body deformation using LPV representations and fuzzy reasoning. WSEAS Trans Syst 7(1):1228–1237Google Scholar
- 11.Pawlus W, Nielsen JE, Karimi HR, Robbersmyr KG (2010) Comparative analysis of vehicle to pole collision models established using analytical methods and neural networks. In: The 5th IET international system safety conference, Manchester, UKGoogle Scholar
- 12.Várkonyi-Kóczy AR, Rövid A, Várlaki P (2004) Intelligent methods for car deformation modeling and crash speed estimation. In: The 1st Romanian–Hungarian joint symposium on applied computational intelligence, Timisoara, RomaniaGoogle Scholar
- 13.van der Laan E, Veldpaus F, de Jager B, Steinbuch M (2008) LPV modeling of vehicle occupants. In: AVEC ’08 9th international symposium on advanced vehicle control, Kobe, JapanGoogle Scholar
- 20.Robbersmyr KG (2004) Calibration test of a standard ford fiesta 1.1l, model year 1987, according to NS - EN 12767. Technical Report 43/2004, Agder Research, GrimstadGoogle Scholar