摘要
In contrast to steady airflow conditions in wind tunnel tests,vehicles on actual roads experience airflow with varying velocity and direction due to natural wind and wake effects from upstream vehicles.This study employs a simplified vehicle model to investigate turbulence characteristics of unsteady wind and unsteady wind noise sources at the front side window area.The research utilizes DES model,implementing both SEM and preceding vehicle method to generate unsteady wind excitation.Analysis of airflow velocity data collected in front of the model and at the front side window area revealed turbulence intensity ranging from 10%to 25%.The probability density distribution of airflow velocity and yaw angle follows a Gaussian distribution,while the power spectral density of fluctuating wind velocity corresponds to the von Karman spectrum,aligning with real road test conditions.Through integration with APE,distinct convective and acoustic pressure fluctuations at the front side window area were obtained.Results demonstrate that SEM's convective pressure fluctuation energy approximates steady wind excitation across all frequencies,with notably elevated acoustic pressure fluctuation energy between 500-2500 Hz.The preceding vehicle method shows reduced convective and acoustic pressure fluctuation energies compared to steady wind excitation due to upstream vehicle influence.Under unsteady wind excitation,the kurtosis value at the external ear position of the side window increases,contrasting with near-zero values under steady conditions.
区别于风洞试验的稳态来流,行驶在道路上的汽车会受到自然风、上游车辆尾迹等影响,经历的气流其速度与方向在不断变化。为研究非稳态来流的湍流特性和汽车前侧窗区域非稳态风噪声源特征,本文以类车体模型为研究对象,基于分离涡模型(DES),分别采用合成涡法(SEM)和前置车辆法生成非稳态风激励条件;通过采集两种方法下类车体前方和前侧窗区域的气流参数,计算出类车体前方的湍流强度达10%~25%,气流速度和角度的概率密度符合高斯分布,脉动风速功率谱符合卡门谱,与实际路试条件一致。结合声扰动方程(APE),分别得到前侧窗区域的对流与声学压力脉动,并使用峰度来表征压力信号的脉动量。结果显示,合成涡法的对流压力脉动能量与稳态风相近,声学压力脉动能量在500~2500 Hz频段较高;前置车辆法受上游车辆影响,两种压力脉动能量均低于稳态风条件。不同于稳态风激励下侧窗外部人耳位置峰度值接近于0的情况,在非稳态风激励下,此位置峰度值会有所增加。
出处
《同济大学学报(自然科学版)》
2025年第S1期68-82,共15页
Journal of Tongji University:Natural Science
基金
国家重点研发计划项目(2022YFE0208000)
国家自然科学基金项目(51575394)
中央高校基本科研业务费专项资金项目
