A Computational Approach to Evaluate the Vehicle Interior Noise from Greenhouse Wind Noise Sources

For most car manufacturers, aerodynamic noise is becoming the dominant high frequency noise source (≻500 Hz) at highway speeds. Design optimization and early detection of issues related to aeroacoustics remain an experimental art implying high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the development of a reliable numerical prediction capability. This paper presents a computational approach that can be used to predict the vehicle interior noise from the greenhouse wind noise sources, during the early stages of the vehicle developmental process so that design changes can be made to improve the wind noise performance of the vehicle. This method is based on coupling an unsteady Computational Fluid Dynamics (CFD) solver for the wind noise excitation to a Statistical Energy Analysis (SEA) solver for the structural acoustic behavior; both the CFD and SEA codes are well-validated industry standard tools. In this paper the computational approach is applied on a real production vehicle to reduce the noise contribution from the green house region. Multiple mirror configurations are considered and the computational results are validated against wind tunnel test measurements.