Title: Study of CAE crash signatures for airbag sensor calibration

Authors: Jerry Jianliang Le, Clifford C. Chou, Ping Chen

Addresses: Passive Safety R&AE, Product Development, Ford Motor Company, Room 2621, MD2115 RIC, 2101 Village Road, Dearborn, MI 48121, USA. ' Passive Safety R&AE, Product Development, Ford Motor Company, Room 2621, MD2115 RIC, 2101 Village Road, Dearborn, MI 48121, USA. ' Passive Safety R&AE, Product Development, Ford Motor Company, Room 2621, MD2115 RIC, 2101 Village Road, Dearborn, MI 48121, USA

Abstract: This paper presents a study of CAE signals generated from a sensor model by addressing frequency requirement, model quality and accuracy, method using Moving Least Squares (MLS) for tackling CAE pulses, and other issues. CAE crash waveforms generated from baseline models contain high levels of noise and are not accurate enough for airbag sensor algorithm calibration. The waveforms need to be improved prior to being used for calibrating the algorithms. MLS is developed primarily for reducing high frequency noise content from CAE waveforms for improving the CAE signal quality. Using a further improved single FEA model to simulate low speeds for non-firing cases, mid-range speeds and high speed firing cases, the frequencies of the CAE backbone signals are in fair agreement with the test data. The FEA sensor model with MLS method allows better simulation of crash sensor signatures for potential use in sensor algorithm calibration and/or restraint systems applications.

Keywords: CAE crash signatures; FEA; airbag sensors; sensor algorithm calibration; computer-aided engineering; finite element analysis; vehicle safety; moving least squares; MLS; crash waveforms; signal quality; simulation; restraint systems.

DOI: 10.1504/IJVS.2007.012583

International Journal of Vehicle Safety, 2007 Vol.2 No.1/2, pp.20 - 43

Published online: 25 Feb 2007 *

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