Abstract
This study is to develop the prediction model for the HIC15 in frontal vehicle crash tests. The 28 frontal impact test results of the MY2019 and MY2020 USNCAP are utilized. The metrics for evaluating the crash pulse severity such as moving average acceleration, Restraint Quotient (RQ) and ride-down efficiency are reviewed to find out whether the metrics can predict the HIC15. It is observed that the R2 values based on the linear regression of all pairs between the existing metrics and the occupant injuries such as the HIC15, 3 ms chest g's and chest deflection are very low. In this study, using the vehicle crash pulses, the linear regression model for estimating the HIC15 is developed. The vehicle crash pulse is splitted seven 10 ms intervals in 70 ms after impact for extracting the average accelerations in each intervals. The prediction model can predict effectively not only the HIC15 but also the maximum head g's, chest deflection and 3 ms chest g's of 13 vehicles out of 28 vehicles.