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Predictive crash sensing and deployment control of safety systems require reliable and accurate kinematic information about potential obstacles in the host vehicle environment. The projected trajectories of obstacles in the path of the vehicle assist in activation of safety systems either before, or just after collision for improved occupant protection. This paper presents an analysis of filtering and estimation techniques applied to imminent crash conditions. Optimization of design criteria to achieve required response performance, and noise minimization, are evaluated based on the safety system to be activated. The predicted target information is applied in the coordinated deployment of injury mitigation safety systems.

The current ability of the Virtual Aerodynamic/ Aeroacoustic Wind Tunnel to predict interior vehicle sound pressure levels is demonstrated using an automobile model which has variable windshield angles. This prediction method uses time-averaged flow solutions from a lattice gas CFD code coupled with wave number-frequency spectra for the various flow regimes to calculate the side window vibration from which the sound pressure level spectrum at the driver's ear is determined. These predictions are compared to experimental wind tunnel data. The results demonstrate the ability of this methodology to correctly predict wind noise spectral trends as well as the overall loudness at the driver's ear. A more sophisticated simulation method employing the same lattice gas code is investigated for prediction of the time-accurate flow field necessary to compute the actual side glass pressure spectra.