Improved Headlamp Fracture Modeling for Crash Sensing through Component Level Development 2022-28-0091
The main objective of crash sensing is to predict a vehicle collision early in the event and command vehicle’s occupant protection systems to take appropriate actions to reduce the severity of crash injury.
Currently Computer Aided Engineering (CAE) models are being used to predict the sensing signals with sensors placed at front end structure of the vehicle. The front-end structure as well as other critical components packaged in the front end play important role in absorbing energy and provide sensing signals during impact, headlamp being one such critical components. The headlamp with its lens being the exterior surface, experience large magnitude of loads from barrier during full frontal, angled and offset impact. The impact with barrier usually results in scattered damage to the headlamp and its lens.
In this paper, CAE model of headlamp has been improved to reflect similar deformation pattern as observed in physical tests. A standalone component level testing on headlamps gives complete understanding of deformation pattern and its behavior under impact loads equivalent to full vehicle energy. Component level testing of headlamps required development of a robust fixture which would experience high impact velocity at different orientation of impactor to mimic full vehicle angled impact scenario.
This paper presents improved fracture behavior of headlamp in CAE based on component level testing. The simulation results from this project helped to standardize the development process for other headlamp component tests, and improved prediction of sensing signals at system level.
