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.
Published Version
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