If vehicle manufacturers have an airbag sensing algorithm, they could use this algorithm to find optimal airbag sensor locations for the better airbag sensing performance, to get an optimal firing logic for their certain vehicle, and to get the overall good performance by considering both the vehicle structure and the airbag sensing algorithm. One study in this paper shows how to find the optimal locations of front impact sensors (FIS) using in-house airbag sensing algorithm, crash test data and CAE simulation models. For this purpose, three steps are fulfilled as follows. In the first step, the acceleration sensor signals of the crash tests are collected at several positions of the vehicle. In the second step, the full car crash simulations are made and correlated to the crash test data. Using these well defined crash vehicle models and crash test data, the acceleration signals of the FIS candidate locations, such as radiator, front side members, and bumper back beam, are obtained. In the final step, using these acceleration signals and airbag algorithm, the airbag sensing performance are evaluated, and the final candidate positions are selected. The robust FIS positions are selected effectively for various crash conditions and velocities via this approach.

The other study shows how to determine an airbag deployment logic using CAE. From simulation models which have several crash speeds, several crash modes, and several restraint conditions, the airbag deployment logic can be determined to minimize the occupant injury level. In addition, the roles and limitations of CAE simulations are demonstrated in the airbag algorithm calibration process and the airbag restraint system development.