MULTI-OBJECTIVE OPTIMIZATION OF SOUND PACKAGE PARAMETERS FOR INTERIOR HIGH FREQUENCY NOISE OF HEAVY-DUTY TRUCK USING GREY THEORY

This article presents a new idea by applying different sound package parameters of to improve the acoustic performance of the commercial vehicle cab. A statistical energy analysis model of the commercial vehicle cab was created, and the SPL of the interior noise for the commercial vehicle cab was predicted and validated at speed of 80 km/h. The contributions of some major subsystems to interior noise were obtained at 80 km/h. Two major characteristics of interior SPL and total weight of sound packages were determined as the optimization targets. The thicknesses of the sound packages for floor, roof, front wall and rear wall were selected to be the optimal variables. The orthogonal array table with four factors and three levels are selected for the experimental design. The optimal combination of sound package parameters is determined by using grey relational analysis with Taguchi method. A grey relational grade is acquired from the analysis to optimize multiple performance characteristics. The experimental results show that the presented methods can effectively deal with the information redundancy problem with multiple sound package parameters for commercial vehicle cab.