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The Pelvis-Thorax Side Air Bag (PTSAB) is a typical restraint countermeasure offered for protection of occupants in the vehicle during side impact tests. Currently, the dynamic performance of PTSAB for occupant injury assessment in side impact is limited to full-vehicle evaluation and sled testing, with limited capability in computer aided engineering (CAE). The widely used CAE method for PTSAB is a flat bag with uniform pressure. The flat PTSAB model with uniform pressure has limitations because of its inability to capture airbag deployment during gap closure which results in reduced accuracy while predicting occupant responses. Hence there is a need to develop CAE capability to enhance the accuracy of prediction of occupant responses to meet performance targets in regulatory and public domain side impact tests. This paper describes a new CAE methodology for assessment of PTSAB in side impact.

An Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors in an attempt to assist pressure sensor algorithm development by using computer simulations. Acceleration-based crash sensors have traditionally been used to deploy restraint devises (e.g., airbags, air curtains, and seat belts) in vehicle crashes. The crash pulses recorded by acceleration-based crash sensors usually exhibit high frequency and noisy responses depending on the vehicle's structural design. As a result, it is very challenging to predict the responses of acceleration-based crash sensors by using computer simulations, especially those installed in crush zones. Therefore, the sensor algorithm developments for acceleration-based sensors are mostly based on physical testing.

In an attempt to predict the responses of side crash pressure sensors, the Corpuscular Particle Method (CPM) was adopted and enhanced in this research. Acceleration-based crash sensors have traditionally been used extensively in automotive industry to determine the air bag firing time in the event of a vehicle accident. The prediction of crash pulses obtained from the acceleration-based crash sensors by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crash zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side impact applications.