Novel Approach in Vehicle Front-End Modeling for Numerical Analyses of Pedestrian Impact Scenarios

2017-01-1451

03/28/2017

Features
Event
WCX™ 17: SAE World Congress Experience
Authors Abstract
Content
In this paper a novel approach in developing a simplified model of a vehicle front-end is presented. Its surface is segmented to form an MBS model with hundreds of rigid bodies connected via translational joints to a base body. Local stiffness of each joint is calibrated using a headform or a legform impactor corresponding to the EuroNCAP mapping. Hence, the distribution of stiffness of the front-end is taken into account. The model of the front-end is embedded in a whole model of a small car in a simulation of a real accident. The VIRTHUMAN model is scaled in height, weight and age to represent precisely the pedestrian involved. Injury risk predicted by simulation is in correlation with data from real accident. Namely, injuries of head, chest and lower extremities are confirmed. Finally, mechanical response of developed vehicle model is compared to an FE model of the same vehicle in a pedestrian impact scenario. VIRTHUMAN model of a 13-year-old boy (150 cm, 40 kg) is chosen to represent the pedestrian and the lateral impact at 45 km/h is considered for various initial positions of pedestrian. While local deformation of the MBS bonnet leads to the HIC value corresponding to the EuroNCAP assessment, prediction obtained in the case of FE model may differ. This reflects the fact that deformation of the bonnet caused by an impact of the torso may influence the shape and the stiffness of the bonnet at the location of head strike.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-01-1451
Pages
11
Citation
Vychytil, J., Spicka, J., Hyncik, L., Manas, J. et al., "Novel Approach in Vehicle Front-End Modeling for Numerical Analyses of Pedestrian Impact Scenarios," SAE Technical Paper 2017-01-1451, 2017, https://doi.org/10.4271/2017-01-1451.
Additional Details
Publisher
Published
Mar 28, 2017
Product Code
2017-01-1451
Content Type
Technical Paper
Language
English