Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (10): 2244-2255.doi: 10.13229/j.cnki.jdxbgxb20210307

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Aerodynamic noise optimization of vehicle claw-pole generator

Tai-ming HUANG1(),Wei-ping LI2(),Tao-tao HU2,Wan-hao YUE2,Nian-zhou JI2,Yu-bang LI3   

  1. 1.School of Mechanical Engineering,Hunan Institute of Science and Technology,Yueyang 414006,China
    2.State Key Laboratory for Advanced Design and Manufacture of Automobile Body,Hunan University,Changsha 410082,China
    3.School of Materials Science and Engineering,Central South University,Changsha 410083,China
  • Received:2021-04-12 Online:2022-10-01 Published:2022-11-11
  • Contact: Wei-ping LI E-mail:htm426@hnu.edu.cn;lwpzlbb@yeah.net

Abstract:

Aiming at the problem that a certain type of claw-pole generator has obvious order aerodynamic noise characteristics under high-speed conditions, a noise test experiment is designed to obtain the main order noise, and the finite element software is used to establish a numerical simulation model of the flow field and sound field. The pressure distribution of the front and rear fan blades, the pressure and sound power distribution of the stator and rotor are analyzed, and the influence of different parts on the aerodynamic noise of the claw-pole generator is studied. The fan blade distribution angle was optimized by the vector synthesis method, and the simulation and test are established for the optimized fan blade to verify the aerodynamic noise optimization effect of the claw-pole generator. Experimental results show that the average noise reduction of the 8th and 12th order of the optimized claw pole generator in the entire speed range has reached 2.5 dB.

Key words: vehicle engineering, aerodynamic noise, claw-pole generator, vector composition method

CLC Number: 

  • U463.63

Fig.1

Claw-pole generator"

Fig.2

Experimental site"

Fig.3

Curves of acoustic power level of each order in no-load conditions"

Fig.4

Computational domains and interfaces"

Fig.5

Local section of calculation model mesh"

Fig.6

Grid independence test"

Fig.7

Acoustic calculation model"

Fig.8

Pressure contour in cross section of front and rear fan"

Fig.9

Pressure and surface acoustic power level contours of rotor"

Fig.10

Pressure and surface acoustic power level contours of stator"

Fig.11

Acoustic power level distribution"

Fig.12

Acoustic power level at 12 000 r/min"

Table 1

Blade angle distribution before and after optimization"

扇叶序号

前风扇

原始叶片

前风扇

优化叶片

后风扇

原始叶片

后风扇

优化叶片

136.00036.00043.00041.003
230.00030.00029.00031.232
330.00030.00029.00028.631
424.00024.00029.00024.773
524.00024.00029.00039.747
624.00024.00036.00035.443
724.00024.00036.00035.735
824.00024.00043.00033.727
936.00036.00043.00053.866
1036.00036.00044.00037.415
1136.00036.000--
1236.00036.000--

Fig.13

3D printed physical model"

Table 2

Average mass flow of each fan blade in axial direction before and after optimization"

流量监测截面位置

转速

/(r·min-1

平均质量流量/(kg·s-1

变化量

/%

优化前优化后
前风扇80000.02830.02871.4
后风扇80000.03250.0322-0.9
前风扇12 0000.04090.04182.2
后风扇12 0000.04870.0474-2.7

Fig.14

Acoustic power level contour under 12 000 r/min"

Fig.15

Pressure contour on section at optimized fan"

Fig.16

Comparison of sound power levels before and after optimization under 12 000 r/min"

Fig.17

Test curve of rear fan before and after optimization"

Table 3

Main order noise changes were measured by test before and after rear fan optimization"

转速

/(r·min-1

阶 次优化前/dB优化后/dB变化量/dB
8000668.3970.42-2.03
873.5169.603.91
1071.1270.150.97
1272.6469.493.15
1469.2469.60-0.36
1669.2670.03-0.77
12 000680.4882.97-2.49
884.7682.811.95
1081.2880.810.47
1282.7679.653.11
1483.0182.110.90

Fig.18

Changes of total noise level before and after optimization"

Table 4

Noise variation of each order afteroptimization"

阶 次

最大减小量

/dB

最大增加量

/dB

平均变化量

/dB

6-0.9+4.7+2.2
8-5.1+0.2-2.5
9-1.4+3.6+1.0
10-3.1+0.7-1.0
11-3.3+4.0+0.2
12-5.2-0.4-2.8
14-1.9+2.6+0.1
16-2.9+1.8-0.3
24-3.4+1.6-1.1
1 Le Goff V, Vidal V, Fakes M, et al. Flow induced noise predictions of an automotive alternator using a lattice boltzmann method[C]∥Turbo Expo: Power for Land, Sea, and Air. American Society of Mechanical Engineers, Düsseldorf, Germany, 2014: 45578.
2 Kim W, Jeon W H, Hur N, et al. Development of a low-noise cooling fan for an alternator using numerical and doe methods[J]. International Journal of Automotive Technology, 2011, 12(2): 307-314.
3 Khelladi S, Kouidri S, Bakir F, et al. Predicting tonal noise from a high rotational speed centrifugal fan[J]. Journal of Sound and Vibration, 2008, 313(1/2): 113-133.
4 Hua C, Zhang Y, Dong D, et al. Aerodynamic noise numerical simulation and noise reduction study on automobile alternator[J]. Journal of Mechanical Science and Technology, 2017, 31(5): 2047-2055.
5 Zhang J H, Chu W L, Zhang H G, et al. Numerical and experimental investigations of the unsteady aerodynamics and aero-acoustics characteristics of a backward curved blade centrifugal fan[J]. Applied Acoustics, 2016, 110: 256-267.
6 陈鑫, 王宁, 沈传亮, 等. 后视镜造型对前侧窗气动噪声的影响[J]. 吉林大学学报: 工学版, 2020, 50(2): 426-436.
Chen Xin, Wang Ning, Shen Chuan-liang, et al. Effect of rearview mirror modeling on aerodynamic noise of front window[J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(2): 426-436.
7 Zheng W L, Yan C, Liu H K, et al. Comparative assessment of SAS and DES turbulence modeling for massively separated flows[J]. Acta Mechanica Sinica, 2016, 32(1): 12-21.
8 Kaltenbacher M, Escobar M, Becker S, et al. Numerical simulation of flow‐induced noise using LES/SAS and Lighthill's acoustic analogy[J]. International Journal for Numerical Methods in Fluids, 2010, 63(9): 1103-1122.
9 杨博, 胡兴军, 王夫亮. 轻型客车侧窗区域气动噪声的数值模拟与验证[J]. 吉林大学学报: 工学版, 2010, 40(4): 915-919.
Yang Bo, Hu Xing-jun, Wang Fu-liang. Numerical simulation and verification of aerodynamic noise from side window region of minivan[J]. Journal of Jilin University(Engineering and Technology Edition), 2010, 40(4): 915-919.
10 高富东, 王德心, 王海东, 等. 基于射流冲击作用的舰机适配性数值分析与优化[J]. 中国机械工程, 2020, 31(12): 1425-1436.
Gao Fu-dong, Wang De-xin, Wang Hai-dong,et al. Numerical analysis and optimization of carrier/air vehicle integrations based on jet impingements[J]. China Mechanical Engineering, 2020, 31(12): 1425-1436.
11 Zheng W L, Yan C, Liu H K, et al. Comparative assessment of SAS and DES turbulence modeling for massively separated flows[J]. Acta Mechanica Sinica, 2016, 32(1): 12-21.
12 詹福良, 徐俊伟. Virtual.Lab Acoustics声学仿真计算从入门到精通[M]. 陕西:西北工业大学出版社,2013: 336-408.
13 Curle N. The influence of solid boundaries upon aerodynamic sound[J]. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 1955, 231(1187): 505-514.
14 Zheng Z G, Li R X. The application of numerical simulation technology in the external aerodynamic noise field of high-speed train[J]. Applied Mechanics and Materials, 2012(101/102): 197-201.
15 Zheng Z Y, Li R X. Application of numerical simulation technology to prediction of aerodynamic dipole acoustics source on automobile surface[C]∥The 2nd International Conference on Digital Manufacturing & Automation, Zhangjiajie, China, 2011: 216-220.
16 汪怡平, 谷正气, 李伟平, 等. 汽车气动噪声数值计算分析[J]. 汽车工程, 2009, 31(4): 385-388.
Wang Yi-ping, Gu Zheng-qi, Li Wei-ping, et al. Numerical analysis of automobile aerodynamic noise[J]. Automotive Engineering, 2009, 31(4): 385-388.
17 胡坤, 顾中浩, 马海峰. ANSYS CFD疑难问题实例详解[M]. 北京:人民邮电出版社,2017.
18 Li W, Yue W, Huang T, et al. Optimizing the aerodynamic noise of an automobile claw pole alternator using a numerical method[J]. Applied Acoustics, 2020, 171: No. 107629.
19 Zuo S, Xie C, Wu X, et al. Numerical simulation and optimization of aerodynamic noise for claw pole alternator[J]. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2018, 233(3): 857-879.
20 张亚东, 董大伟, 闫兵, 等. 车用交流发电机气动噪声数值分析[J]. 振动与冲击, 2016, 35(1): 174-182, 187.
Zhang Ya-dong, Dong Da-wei, Yan Bing, et al. Numerical simulation analysis for aerodynamic noise of a vehicle alternator[J]. Journal of Vibration and Shock, 2016, 35(1): 174-182, 187.
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