Understanding the response characteristics of a high frequency crash data is important in frontal crashes. In this study, the response characteristics were studied under various impact conditions for frontal crashes.
This paper presents an analysis of the high frequency crash data in frontal crashes, rough road test and car frames impact test. This also presents a frontal crash sensing algorithm, which uses the high frequency crash data measured in the central control unit, and capable of continuously predicting the severity of a crash.
A high frequency data generated during crashes is attenuated as it passes through the vehicle's structure, especially during low-speed frontal crash and rough road test. It was determined that the high frequency data is also influenced by the crash velocity and the distance between the impact point and the measurement location.
The algorithm presented in this paper has two parts linked in series. The first part categorizes the velocity and the displacement of occupant during the frontal crash. The second part predicts the severity of the crash using an envelope of high frequency crash data. Using the two crash decision logics will lead to a higher performance in crash distinction without satellite crash sensors mounted on the crash zone in front of the vehicle.