Abstract
Acoustic packages are commonly used to reduce the mid-high frequency noise in the automobile, but fully characterizing their absorption and insulation mechanisms poses challenges. Introducing a data-driven approach to analyze their performance, existing research lacks clarity on the factors influencing acoustic package efficacy when constructing approximate models. To alleviate this, a method of optimizing the acoustic package by combining range analysis with a Response Surface Methodology (RSM) model is proposed in this paper. Initially, a validated Statistical Energy Analysis (SEA) model predicts automobile interior noise, pinpointing the dash panel as a key component for optimization through contribution analysis. Then, acoustic material tests are conducted to design the acoustic package. To compare the design scheme and the original scheme for the acoustic package in the automobile, the simulation and the test of the automobile ATF are performed and the automobile SEA model is verified through the test. Based on the range analysis, an RSM model is developed with the significant factors as input and the sound pressure level (SPL) of the driver’s head acoustic cavity as output. Genetic algorithm optimization is finally performed to obtain the optimized scheme within constrained thickness and weight. The results reveal that the acoustic package optimized scheme effectively improves the noise reduction effect in the mid-frequency range and decreases the weight of the acoustic package, which promotes the comprehensive performance of the acoustic package.
Published Version
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