Analysis of crash test and computer aided engineering pulses for airbag sensor development Online publication date: Thu, 16-Apr-2009
by Clifford C. Chou, Jerry Jialiang Le, Jamel E. Belwafa
International Journal of Vehicle Safety (IJVS), Vol. 3, No. 3, 2008
Abstract: The concept of frequency analysis to extract a representative signal that is experienced by a vehicle during a crash for sensor development is described. The method of Fourier series is used, as an illustration, for characterising crash sensor signal to derive a base crash curve for developing sensing algorithms in airbag fire/no-fire decision making. Based on the signals from various crash test data, a cut-off frequency of 300 Hz is found to give accurate representation of signals. Results indicate that low frequency band in signals dominates the crash behaviour. This desired cut-off frequency can be used in sensor studies for sensing algorithm development as well as for assessing current computer aided engineering capability in predicting sensor crash pulses in the frequency domain. Crash signal predictions from finite element analysis (FEA) models correlate fairly well at low frequency range up to this cut-off frequency. In addition, improvements of FEA methods for sensor development are proposed.
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