A Statistical Regression-Based Energy Method for Estimating Vehicle Interior Noise in Early Vehicle Design

A capability is developed to rapidly estimate in the early vehicle design stage the effect of different vehicle architecture types and specifications on the vehicle interior road and engine noise performance. Regression analyses from the database of vehicle on-road, wind tunnel, and chassis dynamometer tests are used to identify the sound energy transferred by various vehicle subsystem architectures. Energy excitation from tire-road interaction, aerodynamic loads, and powertrain loads are used to predict the interior noise (dBA) and Articulation Index (AI) responses. Comparisons of the estimated versus measured dBA and AI responses show reasonable agreement of the vehicle interior noise.