纯电动汽车车内噪声源信号的降噪研究

Noise Reduction Study of Noise Source Signals in Pure Electric Vehicles

传递路径分析是识别车内噪声源技术的重要研究方法,但试验车辆在运行工况下,其输入端中各路径易受外部因素干扰,导致采集的噪声源信号中含有噪声。针对此问题,本文提出采用集合经验模态分解与小波阈值的方法对噪声源信号进行降噪处理,其中,引入了相关系数方便更精确的识别出高频分量进而达到更优降噪效果。以某款国产纯电动汽车为试验车辆,采集加速工况的时域数据,应用搭建的工况传递路径模型对车内噪声源贡献量分析并进行降噪处理。结果表明,本文提出的降噪方法在车内噪声源信号中降噪的可行性。

Transmission path analysis is an important research method for identifying noise sources in vehicles,but the paths in the input of the test vehicle are easily disturbed by external factors under operating conditions,resulting in noise in the collected noise source signals.To address this problem,this paper proposes the use of collective empirical modal decomposition and wavelet thresholding to noise source signals for noise reduction processing,in which the introduction of correlation coefficients facilitates more accurate identification of high-frequency components to achieve better noise reduction effects.A domestic pure electric vehicle is used as the test vehicle to collect the time domain data of acceleration conditions,and the noise source contribution is analyzed and noise reduction is performed by applying the constructed condition transfer path model.The results show the feasibility of the noise reduction method proposed in this paper in the in-vehicle noise source signal.