Numerical optimization of sound pressure responses for the dash panel based on automatically matched layer and genetic algorithm

The sound insulation performance of the dash panel has a direct influence on the level of sound absorption of the whole vehicle. Therefore, it is necessary to adopt proper optimization strategies to optimize the dash panel and interior sound pressure response. Firstly, damping loss factor was imported into the dash panel and the coupling model of interior acoustic cavity to compute the sound pressure response of the driver. Sound pressure response had multiple peak noises in the analyzed frequency band. With the increase of the analyzed frequency, Contours for the noise of interior acoustic cavity became increasingly dispersed. Secondly, reverberation chambers on both sides were coupled with the dash panel respectively to establish AML model. In this way, the computational transmission loss would be more consistent with the actual situation. AML method can directly obtain transmission loss without extracting the transmission sound power to compute transmission loss through relevant formulas. In reported papers, there are big differences between simulation and experiment in the low frequency because it is difficult to simulate the real boundary conditions. The computational results of this paper were more consistent with experimental results in the whole frequency band, which indicated that it was more effective to use AML method to compute the transmission loss of the dash panel. Then, a sound package was applied to the dash panel to conduct parametric analysis. Results showed that the thickness of the sound-absorption layer could effectively improve transmission loss over 250 Hz. When the thickness of the sound-absorption layer was 15 mm, transmission loss was relatively optimal. In addition, the thickness of the air layer had little influence on transmission loss. Finally, genetic algorithm was also used to optimize the parameters of sound package of the dash panel. Results showed that the optimized dash panel had a higher average transmission loss and total mass, and the average sound pressure response of the driver also decreased. Additionally, the transmission loss and sound pressure response of the driver optimized by genetic algorithm at each frequency point were improved in the analyzed frequency band to obtain a low-noise and lightweight dash panel