汽车车内噪声主动控制系统扬声器与麦克风布放优化方法

利用声固耦合边界元仿真方法与多目标遗传算法,实现了面向对象的车内噪声主动控制(ANC)系统扬声器麦克风布放方案的优化。首先基于自适应算法,推导了车内噪声主动控制系统降噪性能预测方法,并利用声固耦合边界元仿真方法,实现了面向对象的ANC系统降噪性能预测;在该仿真模型的基础上,建立对应的代理模型,以实现对系统降噪性能的快速预测;最后利用多目标遗传算法,获得系统关于扬声器麦克风数量与多个频率下降噪量的Pareto最优解集。该最优解集能定量描述ANC系统扬声器麦克风数量与降噪性能之间的关系,并为该系统与车辆的匹配提供依据。

Vehicle ANC hardware optimal placement using Multi-objective genetic algorithm

Here,the issue of loudspeakers or microphones optimal placement of vehicle active noise control (ANC) systems was investigated.First of all,a method was introduced to predict the effect of vehicle multichannel ANC systems based on the boundary element methods (BEM) simulation.The method was replaced by a surrogate model so that the fast predicting the system’s denoising performance was realized.The number and location of microphones and speakers were taken as variables in such a model so that the model was optimized with Matlab.A kind of Multi-objective genetic algorithm was used to optimize this model.The placement plans reducing noise well in full frequency domain with least loudspeakers and microphones were retained.Pareto optimal front of the optimization model was used to give a quantitative result of the relationship between the number of loudspeakers or microphones resources and the noise reduction effect.The results provided a basis for arranging the location of loudspeakers and microphones in a vehicles.