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State of the art electronic restraint systems rely on the acceleration measured during a vehicle crash for deployment decisions. The acceleration signal is analyzed with different criteria, among which the velocity change is a dominant criterion in almost any existing crash detection algorithm. Sensors in the front crush zone have recently been added to help develop restraint systems that comply with the new FMVSS208 and EuroNCAP regulations. Front crash sensors are usually evaluated for their velocity change during a crash and typically play a key role in the deployment decision. CAE based FEA analysis has recently been used to generate signals at the sensor module locations in crash simulations to provide supplemental information for crash sensing algorithm development and calibration. This paper presents an initial effort in developing a velocity-based crash detection algorithm, that allows broad use of CAE generated velocity time histories for system calibration.

Many rollover safety researches have been conducted experimentally and analytically to investigate the underlying causes of vehicle accidents and develop rollover test procedures and test methodologies to help understand the nature of rollover crash events. In addition, electronic and/or mechanical instrumentation are used in dummy and vehicle to measure their responses that allow both vehicle kinematics study and occupant injury assessment. However, method for measurement of dynamic structural deformation needs further exploration, and means to monitor vehicle-to-ground contact load is still lacking. Thus, this paper presents a method for determining the vehicle-to-ground load during laboratory-based rollover tests using results obtained from a camera-matching photogrammetric technology as inputs to a FE SUV model using a nonlinear crash analysis code.