Automotive Interior Noise Prediction Based on Single Sound Cavity Using Statistical Energy Analysis Method

Abstract

In order to predict car interior noises at the car design and development stage, the statistical energy analysis (SEA) method was used. All the input parameters – modal density (MD), damping loss factor (DLF) and coupling loss factor (CLF) were calculated with SEA principle. Meanwhile, the sound excitation was calculated with sound power experiment data of internal combustion engine given by the engine manufacturer and sound source radiation formula. Engine mount excitation was also computed through the acceleration at initiative side of the engine mount and the transmissibility. A car virtual prototype was built to calculate a car body suspension receiving excitation from road roughness. A computational fluid dynamics (CFD) model was also built up to analyze the wind excitation on the outside surfaces. The car interior noises were predicted by the SEA model with all of the parameters and excitations. A good agreement was indicated by comparing predicted results with measured ones. The maximum relative error between prediction and measurement results is less than 3%, and the maximum absolute error is less than 2.5 dB (A). The above predicted results satisfy engineering precision requirements and as well as showing that using SEA method to predict car internal noises is feasible. The acoustic sensitivity analysis was made at the end. The car internal noise prediction method presented in the paper can be used at car design and development stage.