Subjective Evaluation of Vehicle Sound Quality via Auralization Supported by Statistical Energy Analysis for Design Sensitivity Investigation

摘要

CAE simulation is a powerful tool to predict the Noise & Vibration performance of automotive vehicle. For airborne noise sensitivity, Statistical Energy Analysis (SEA) is the preferred simulation solution to optimize the sound package of automotive vehicle. However, SEA, as any other simulation method for acoustics, does not evaluate Sound Quality as this requires the ability to generate sounds in time domain that are dependent on vehicle speed, engine RPM, road profile, etc. In this paper, we will present the solution that was developed to evaluate the sound quality of virtual vehicle prototypes based on measurements for source-path-contribution characterization and SEA simulation to calculate the vehicle airborne sensitivity or transfer functions. We also present results from an application case using test and simulation data.