A Method for Predicting HIC15, Chest G’s and Chest Deflection Based on Results of USNCAP Frontal Impact Tests

This study is to develop the linear regression model for estimating and predicting the HIC15, chest deflection and 3 ms chest g’s of driver and passenger dummy. Frontal impact test results of 28 vehicles from the MY2019 ∼ MY2020 USNCAP are utilized to construct the linear regression model. The average accelerations of vehicle, dummy head and chest are handled as the main variables. The fundamental concept is splitting the 100 ms range into 10 intervals for obtaining the average accelerations at each 10 ms intervals. The results from the developed regression model correlate very well with the test results from the MY2019 ∼ MY2020 USNCAP frontal impact test. The linear regression model is able to predict the HIC15 and the 3ms chest g’s of Hybrid III 50 th percentile male dummy and 5 th percentile female dummy, effectively and sufficiently. In case of the chest deflection, although the regression model remains to be improved, the prediction using the model is still acceptable.