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Vehicle side impact performance is potentially affected by a large number of parameters which may be related to body stiffness and energy absorption characteristics, and packaging dimensions. An understanding of the principal variables controlling TTI (Thoracic Trauma Index) is fundamental to the achievement of high LINCAP (Lateral Impact New Car Assessment Program) rating especially for sedans. In the present study, the effects on TTI of the following are considered: response-related parameters such as velocity and intrusion (which are in turn related to body structure), countermeasures such as side airbag, and dummy to structure clearance dimensions. With the help of test data gathered from side impact tests carried out on cars and trucks at Ford, a new “best subset” regression model is developed and is shown to be able to predict TTI for a number of LINCAP tests which were not part of the suite used in the derivation of the model.

Adhesively bonded steel hat section components have been experimentally studied in the past as a potential alternative to traditional hat section components with spot-welded flanges. One of the concerns with such components has been their performance under axial impact loading as adhesive is far more brittle as compared to a spot weld. However, recent drop-weight impact tests have shown that the energy absorption capabilities of adhesively bonded steel hat sections are competitive with respect to geometrically similar spot-welded specimens. Although flange separation may take place in the case of a specimen employing a rubber toughened epoxy adhesive, the failure would have taken place post progressive buckling and absorption of impact energy.

The present work is concerned with the objective of multi disciplinary design optimization (MDO) of an automotive front end structure using truncated finite element model. A truncated finite element model of a real world vehicle is developed and its efficacy for use in design optimization is demonstrated. The main goal adopted here is minimizing the weight of the front end structure meeting NVH, durability and crash safety targets. Using the Response Surface Method (RSM) and the Design Of Experiments (DOE) technique, second order polynomial response surfaces are generated for prediction of the structural performance parameters such as lowest modal frequency, fatigue life, and peak deceleration value.