A crash severity algorithm for all frontal crash modes using compensation factors

Abstract

In advanced air bag systems, there are normally two satellite accelerometers at the front and one accelerometer in the air bag electronic control unit (ACU) at the central tunnel. By using the deceleration signals from these accelerometers, crash algorithms in the ACU should determine whether or not and when air bag deployment is required, and how severe the crash is. In order to modulate the air bag power, the information on the crash severity as well as on the occupant position, occupant weight, and belt usage is essential. In this paper, a new crash discrimination algorithm and a new crash severity algorithm were developed for a sedan. For the crash discrimination algorithm, two metrics were proposed to be used, and the times to fire air bags were determined only when both metrics became bigger than their respective thresholds. For the crash severity algorithm, two compensation factors for an oblique, an offset, or a pole crash were proposed to be used, and crash severity levels were determined for all crash tests without classifying the crash modes but by comparing a metric with its thresholds set the same for all crash modes. The reliability of the algorithms was also evaluated for numerous crash signals generated by the Monte-Carlo method, and both algorithms were proven to be robust.