文中利用统计能量分析方法，首先建立了计算汽车前围板传递损失的统计能量分析模型，采用最优拉丁超立方方法生成了36个声学包方案的试验点，其中以覆盖率、堵件厚度、PU泡沫厚度及EVA面密度为设计变量和以前围子系统隔声量和声学包重量为优化目标，并计算了不同声学包方案下前围子系统的传递损失。然后依此建立Kriging近似模型并验证模型的可信度，采用NSGA-II算法进行以声学包隔声量及重量为目标的多目标优化，获得了Pareto最优解集。赋予声学包隔声性能及总重量一样的权重，得到了覆盖率、堵件厚度、PU泡沫厚度及EVA面密度的最优值，并任取三组试验点计算其传递损失和整车中的基于能量的隔声量和驾驶员头部的声压级，从而验证该结果的正确性。结果表明，该最优值能够使得声学包在隔声性能与重量之间取得最佳平衡。
Abstract
In the paper, by using statistical energy analysis (SEA) method, the vehicle dash SEA model to calculate the transmission loss (TL) is firstly established. By using the optimal latin hypercube method, 36 test points of the dash sound package are generated, which are based on four design variables in terms of coverage, blocking thickness of the holes, PU foam thickness and EVA surface density and two optimization targets in terms of the insulation performance and the weight of the sound package. And the TLs of different sound package cases are calculated. Then the kriging approximation model can be built and also verified. The multi-objective optimizations of the insulation performance and the weight of sound package are performed by NSGA-II algorithm, then pareto optimal solution set is obtained. The optimal values of coverage，blocking thickness, PU foam thickness and EVA surface density are obtained by giving the same weight of the insulation performance and the sound package weight, and the result is also verified based on the TL and full vehicle results in terms of power based noise reduction (PBNR) and sound pressure level (SPL) at the driver’s head by three random test points. The result shows that the best balance between the insulation performance and the weight for the dash sound package can be acquired by the optimal values.
关键词
声学包优化 /
最优拉丁超立方 /
Kriging模型 /
NSGA-II算法
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Key words
Sound package optimization /
optimal latin hypercube /
kriging model /
NSGA-II algorithm
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