Abstract
Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this work, a brief overview of different vehicle crash modeling methodologies is proposed. The acceleration of a colliding vehicle is measured in its center of gravity—this crash pulse contains detailed information about vehicle behavior throughout a collision. A virtual model of a collision scenario is established in order to provide an additional data set further used to evaluate a suggested approach. Three different approaches are discussed here: lumped parameter modeling of viscoelastic systems, data-based approach taking advantage of neural networks and autoregressive models and wavelet-based method of signal reconstruction. The comparative analysis between each method’s outcomes is performed and reliability of the proposed methodologies and tools is evaluated.
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Pawlus, W., Karimi, H.R. & Robbersmyr, K.G. Investigation of vehicle crash modeling techniques: theory and application. Int J Adv Manuf Technol 70, 965–993 (2014). https://doi.org/10.1007/s00170-013-5320-3
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DOI: https://doi.org/10.1007/s00170-013-5320-3