A regression-based energy method is developed for rapid estimation of the overall passenger-compartment interior noise (dBA) and Articulation Index (AI) in a vehicle of prescribed architecture when the vehicle travels on a particular road at a particular speed. The method is developed for use in the early vehicle design stage when only limited vehicle architecture design information are known. Regression analyses from a database of vehicle on-road tests and vehicle wind-tunnel tests are used to identify the energy transfer functions that represent the prescribed vehicle architecture. Energy excitation from both tire-road interaction and aerodynamic loads is then used to predict the interior dBA and AI responses. Comparisons of the predicted versus measured dBA and AI responses show reasonable agreement for car and wagon-type vehicles, although limited architecture data somewhat underestimates the actual response in certain vehicles

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