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A passenger airbag is an important part of a vehicle restraint system which provides supplemental protection to an occupant in a crash event. New Federal Motor Vehicle Safety Standards No. 208 requires considering multiple crash scenarios at different speeds with various sizes of occupants both belted and unbelted. The increased complexity of the new requirements makes the selection of an optimal airbag shape a new challenge. The aim of this research is to present an automated optimization framework to facilitate the airbag shape design process by integrating advanced tools and technologies, including system integration, numerical optimization, robust assessment, and occupant simulation. A real-world frontal impact application is used to demonstrate the methodology.

The optimization method and CAE analysis have been widely used in structure design for crash safety. Combining the CAE analysis and optimization approach, vehicle structure design for crash can be implemented more efficiently. One of the recent safety desirables in structure design is to reduce vehicle pitch and drop. At frontal impact tests with unbelted occupants, the interaction between occupant's head and interior header/sun visor, which is caused by excessive vehicle pitch and drop, is not desired in vehicle crash development. In order to comply with the federal frontal crash requirements for unbelted occupant, it is necessary to manage the vehicle pitch and drop by improving structure design. In this paper, a systematic process of CAE analysis with optimization approach is applied for discovering the major structural components affecting vehicle pitch and drop.

In vehicle safety engineering, it is important to determine the severity of occupant injury during a crash. Computer simulations are widely used to study how occupants move in a crash, what they collide during the crash and thus how they are injured. The vehicle motion is typically defined for the occupant simulation by specifying a crash pulse. Many computer models used to analyze occupant kinematics do not calculate both vehicle motion and occupant motion at the same time. This paper presents a framework of response surface methodology for the crash pulse prediction and vehicle structure design optimization. The process is composed of running simulation at DOE sampling data points, generating surrogate models (response surface models), performing sensitivity analysis and structure design optimization for time history data (e.g., crash pulse).