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作 者:段孟华 赖晨光 王勇[1] 冯锦阳 谭文林 Meng-hua DUAN;Chen-guang LAI;Yong WANG;Jin-yang FENG;Wen-lin TAN(Wind Tunnel Center of China Automobile Engineering Research Institute Co.,Ltd.,Chongqing 401122,China;College of Vehicle Engineering,Chongqing University of Technology,Chongqing 400054,China;Institute of Fluid Science,Tohoku University,Sendai 980-8577,Japan)
机构地区:[1]中国汽车工程研究院股份有限公司汽车风洞中心,重庆401122 [2]重庆理工大学车辆工程学院,重庆400054 [3]东北大学流体科学研究所,仙台980-8577
出 处:《机床与液压》2020年第6期78-84,共7页Machine Tool & Hydraulics
基 金:国家自然科学基金资助项目(51305477);中美提高中重型卡车能源效率关键技术联合研究项目(2017YFE0102800)。
摘 要:运用分离涡模拟(DES),以商用软件Star CCM+为研究工具对某SUV在车窗封闭状态下,对汽车后视镜区域进行了外流场稳态和瞬态的计算分析,获得车身表面和周围的压力脉动,以此作为激励计算车内噪声。应用声学软件对后视镜以及周围进行流场到声场的耦合分析,得到声压级的频谱图。通过分析基础模型和改进模型内、外场气动声学特性表明:后视镜柄的长度,镜柄与镜罩的夹角以及镜罩形状对后视镜下游流场和声压级影响较大。改进模型相比基础模型前侧窗玻璃外表面总声压级得以降低,驾驶员左耳处内场总声压级降低了6.41%,语音清晰度提高了33.89%,取得很好的改进效果。By using the separated eddy simulation(DES)and the fluid software as the research tool,the steady and transient simulation and analysis of the external flow field are carried out under the closed window condition in the rear-view mirror area of a vehicle.The pressure fluctuation on the body surface,which is used as the excitation to calculate the interior noise of the vehicle,is obtained.The coupling analysis of flow field and acoustic field around the rear-view mirror is realized by using acoustic software,and then the spectrum of sound pressure level is obtained.By analyzing the aeroacoustic characteristics of the internal and external fields of the basic model and the improved model,it is shown that the length of the rear-view mirror handle,the angle between the mirror handle and the mirror cover,and the shape of the mirror cover have great influence on the downstream flow field and the sound pressure level of the rear-view mirror.Compared with the basic model,the total sound pressure level on the outer surface of the front left-side windscreen of the improved model is reduced;the total sound pressure level in the inner field of the driver’s left ear is reduced by 6.41%,and the speech intelligibility is improved by 33.89%.
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