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This paper demonstrates the benefit of using simulation and robust optimization for the problem of balancing vehicle noise, vibration, and ride performance over road impacts. The psychophysics associated with perception of vehicle performance on an impact is complex because the occupants encounter both tactile and audible stimuli. Tactile impact vibration has multiple dimensions, such as impact hardness and memory shake. Audible impact sound also affects occupant perception of the vehicle quality. This paper uses multiple approaches to produce the similar, robust, optimized tuning strategies for impact performance. A Design for Six Sigma (DFSS) project was established to help identify a balanced, optimized solution. The CAE simulations were combined with software tools such as iSIGHT and internally developed Kriging software to identify response surfaces and find optimal tuning.

This paper presents a pioneer work and first time application of Multi Objective Robust Optimization to analytically improve Idle Shake Performance. The method is developed to obtain a robust design with multiple objectives under consideration along with managing material property variation. It was a Robust Optimization on top of Multi Objective Genetic Algorithm, Robu-MOGA. The design variables in the study included the nominal values and tolerances of Sound Transmission Loss property, and interior material Absorption property. The analytical objective was not only to minimize the peak airborne noise at each specified frequency, but also to reduce the total cost and the total mass of the materials. In the study, AutoSEA (statistical energy analysis) from ESI Software, Inc. was used as the solver. AutoSEA was integrated with iSIGHT from Engineous Software, Inc.