OPTIMIZATION OF CAR SOUND PACKAGE WITH STATISTICAL ENERGY ANALYSIS MODEL USING GREY RELATIONAL ANALYSIS AND TAGUCHI METHOD

Optimization design of the structures and thicknesses of the sound packages is performed for automotive interior acoustic performance and lightweight characteristics. A SEA model of the car was created, and its interior noise of the automobile was predicted and validated at speed of 120km/h. The contributions of some major subsystems to interior noise were calculated at 120km/h. Both of major characteristic indices including interior SPL and total weight of sound packages are selected to evaluate automotive interior acoustic performance and lightweight characteristics, and four selected optimization parameters are structures and thicknesses of the sound package of firewall and front floor. The problem of multiple performance indices is simplified into single performance index by using grey relational grade. The optimal combination of sound package parameters is determined by employing grey relational analysis method. Furthermore, the validation tests show that the values of interior SPL and overall weight of sound packages decrease by 1.31% and 60.36%, respectively. Also, the comparison of the overall SPL for automotive interior noise experiments between original and optimized structures and thicknesses of the sound packages shows that automotive interior acoustic performance is obviously improved from 200Hz to 10,000Hz. Therefore, it is demonstrated that it is an effective way to deal with optimization problems by using the presented approach in this research.