The frontal airbag in a vehicle is considered a supplemental restraint to the safety belt restraint system and is important in lowering measured injury assessment values for Anthropomorphic Test Devices (ATD) during vehicle crash testing. Neck injuries for the right front passenger occupant are especially sensitive to the passenger airbag (PAB) shape. Therefore, multiple sled tests and Computer Aided Engineering (CAE) simulations are required for PAB development to arrive at a balanced restraint system and achieve optimal performance for occupant injury metrics.

The purpose of this study is to establish a design procedure and optimization process for passenger airbags by using CAE techniques to minimize development time.

In this study, a design method to create a new baseline airbag is introduced. Surrogate sled CAE models were generated to make efficient use of computing resource availability. Validation of CAE surrogate models was performed using sled tests. A direct optimization method, not meta-model based, was developed for airbag shape optimization across multiple load cases. Parameterized airbag shape and morphing techniques were used in the optimization. The objective function is US-NCAP performance, however, major injury criteria from FMVSS208 (belted and unbelted) as well as airbag volume were used as constraint conditions. All optimization processes were automated, and airbag shape is optimized per objective functions and constraint conditions. Additionally, different optimization algorithms were compared to find the most efficient method for airbag design.