湍流模型参数对气动力仿真精度影响研究

doi:10.19562/j.chinasae.qcgc.2025.09.011

Abstract

Abstract:

The shear-stress-transport （SST） $k - ω$ turbulence model is one of the best comprehensive two-equation turbulence models available and is widely used in the research of automotive aerodynamics. The existing studies have shown that the closure coefficients in the $S S T ? k - ω$ turbulence model significantly affect the accuracy of aerodynamic simulation for vehicles. However， most researches are limited to simplified models. Therefore， in this paper， the impact of the typical turbulence model coefficients on the accuracy of aerodynamic simulations of a sedan is studied under stationary wheel conditions. It is found that the turbulence model coefficients $σ ω 1, ? σ ω 2, ? β *$ and $C T$ are linearly related to aerodynamic drag and lift， while approximately quadratic for $a 1$ . Furthermore， this paper uncovers the influence mechanism of turbulence model coefficients on the flow field around the vehicle， and the recommended values for turbulence model coefficients to improve the accuracy of aerodynamic simulation are provided： $σ ω 1 = 0.3$ ， $σ ω 2 = 0.7$ ， $β * = 0.06$ ， $a 1 = 0.5$ and $C T = 1.0$ .This paper provides theoretical and engineering guidance for more accurate and reliable aerodynamic simulation of vehicles.

Key words: automotive aerodynamics, turbulence model coefficients, aerodynamic drag, aerodynamic lift

Wenqiang Shang,Fengli Zhang,Wenjiang Wang,Qiuli Luo,Peng Zhou. Study on Effect of Turbulence Model Coefficients on Accuracy of Aerodynamic Simulation[J].Automotive Engineering, 2025, 47(9): 1752-1762.

Figures/Tables 18

网格方案	网格总数	$C D$	$C L$
1	3 293万	0.273	0.121
2	5 800万	0.271	0.113
3	7 592万	0.271	0.113
试验		0.267	0.078

$σ ω 1$	$C D$ -试验	$C D$ -仿真	$C L$ -试验	$C L$ -仿真	$C D$ 误差（仿真-试验）	$C L$ 误差（仿真-试验）	收敛性
0.2	0.267	0.269	0.078	0.111	0.002	0.033	波动大
0.3	0.267	0.270	0.078	0.110	0.003	0.032	收敛
0.5	0.267	0.271	0.078	0.113	0.004	0.035	收敛
0.8	0.267	0.275	0.078	0.140	0.008	0.062	收敛

$σ ω 2$	$C D$ -试验	$C D$ -仿真	$C L$ -试验	$C L$ -仿真	$C D$ 误差（仿真-试验）	$C L$ 误差（仿真-试验）	收敛性
0.6	0.267	0.267	0.078	0.103	0	0.025	波动大
0.7	0.267	0.267	0.078	0.101	0	0.023	收敛
0.856	0.267	0.271	0.078	0.113	0.004	0.035	收敛
1.0	0.267	0.274	0.078	0.117	0.007	0.039	收敛

$β *$	$C D$ -试验	$C D$ -仿真	$C L$ -试验	$C L$ -仿真	$C D$ 误差（仿真-试验）	$C L$ 误差（仿真-试验）	收敛性
0.06	0.267	0.267	0.078	0.094	0	0.016	收敛
0.07	0.267	0.268	0.078	0.104	0.001	0.026	收敛
0.09	0.267	0.271	0.078	0.113	0.004	0.035	收敛
0.11	0.267	0.272	0.078	0.118	0.005	0.040	收敛

$a 1$	$C D$ -试验	$C D$ -仿真	$C L$ -试验	$C L$ -仿真	$C D$ 误差（仿真-试验）	$C L$ 误差（仿真-试验）	收敛性
0.31	0.267	0.262	0.078	0.113	-0.005	0.035	波动大
0.5	0.267	0.265	0.078	0.094	-0.002	0.016	收敛
0.7	0.267	0.271	0.078	0.116	0.004	0.038	收敛
1.0	0.267	0.271	0.078	0.113	0.004	0.035	收敛

$C T$	$C D$ -试验	$C D$ -仿真	$C L$ -试验	$C L$ -仿真	$C D$ 误差（仿真-试验）	$C L$ 误差（仿真-试验）	收敛性
0.6	0.267	0.265	0.078	0.121	-0.002	0.043	波动大
0.8	0.267	0.264	0.078	0.095	-0.003	0.017	收敛
1.0	0.267	0.267	0.078	0.101	0	0.023	收敛
1.2	0.267	0.271	0.078	0.113	0.004	0.035	收敛

参数	$σ ω 1$	$σ ω 2$	$β *$	$a 1$	$C T$
数值	0.3	0.7	0.06	0.5	1.0

湍流模型参数	皮尔逊相关系数		斯皮尔曼相关系数
湍流模型参数	$C D$	$C L$	$C D$	$C L$
$σ ω 1$	0.98 （0.139 1）	0.95 （0.202 3）	1.00 （0.000 0）	1.00 （0.000 0）
$σ ω 2$	1.00 （0.037 7）	0.97 （0.164 2）	1.00 （0.000 0）	1.00 （0.000 0）
$β *$	0.98 （0.021 2）	0.96 （0.035 8）	1.00 （0.000 0）	1.00 （0.000 0）
$a 1$	0.80 （0.406 5）	0.72 （0.486 8）	0.87 （0.333 3）	0.50 （0.666 7）
$C T$	1.00 （0.052 4）	0.98 （0.121 0）	1.00 （0.000 0）	1.00 （0.000 0）

References 9

[1]	FU C， BOUNDS C， UDDIN M， et al. Fine tuning the SST k - ω turbulence model closure coefficients for improved NASCAR cup racecar aerodynamic predictions［C］. SAE Paper 2019-01-0641.
[2]	FU C， UDDIN M， ROBINSON C， et al. Turbulence models and model closure coefficients sensitivity of NASCAR racecar RANS CFD aerodynamic predictions［J］. SAE International Journal of Passenger Cars - Mechanical Systems， 2017， 10（1）： 330-344.
[3]	CHARLES P B， ZHANG C， MESBAH U. Improved CFD prediction of flows past simplified and real-life automotive bodies using modified turbulence model closure coefficients［J］. Journal of Automobile Engineering， 2020， 234（10-11）： 2522-2545.
[4]	CHAMUNDESWAR S D. Sensitivity of turbulence closure coefficients on the aerodynamic predictions of flow over a simplified road vehicle［D］. The University of North Carolina at Charlotte， 2018.
[5]	BOUNDS C， UDDIN M， DESAI S. Tuning of turbulence model closure coefficients using an explainability based machine learning algorithm［C］. SAE Paper 2023-01-0562.
[6]	罗秋丽，张风利，张荣荣，等. 比亚迪汉汽车空气动力学开发［J］. 汽车工程学报， 2020， 10（6）： 399-406.
	LUO Q L， ZHANG F L， ZHANG R R， et al. The aerodynamic development of the BYD Han［J］. Chinese Journal of Automotive Engineering， 2020， 10（6）： 399-406.
[7]	张荣荣，彭倩，罗秋丽，等. 基于Powerflow的汽车风阻仿真对标研究［C］. 2019汽车空气动力学分会年会论文集. 重庆：中国汽车工程研究院股份有限公司， 2019： 17-23.
	ZHANG R R， PENG Q， LUO Q L， et al. Correlation of automotive air drag simulation with wind tunnel test based on powerflow［C］. Academic Annual Conference of Automotive Aerodynamic Committee. Chongqing： China Automotive Engineering Research Institute Co.， Ltd.， 2019： 17-23.
[8]	MENTER F R. Improved two-equation k-ω turbulence models for aerodynamic flows［M］. NASA Technical Memorandum， 1992： 103975.
[9]	DURBIN P A. On the k- ε stagnation point anomaly［J］. International Journal of Heat and Fluid Flow， 1996， 17（1）： 89-90.

[1]	Chao Peng,Han Bu,Qingyang Wang,Qianwen Zhang,Jie Yang,Gan Lian. Correction Study of Balance Additional Lift in Full-Scale Vehicle Wind Tunnel [J]. Automotive Engineering, 2025, 47(7): 1415-1424.
[2]	Qianwen Zhang,Lei Xu,Qingyang Wang,Shengjin Xu. Dynamic Effect of Underbody Flow Separation on Aerodynamic Drag in Electric Vehicles [J]. Automotive Engineering, 2025, 47(5): 910-919.
[3]	Jingfeng Shao,Huihui Zuo,Xingjun Hu. Optimization of Aerodynamic Drag Reduction and Its Flow-Field Mechanism for a Sport Utility Vehicle (SUV) [J]. Automotive Engineering, 2024, 46(2): 356-365.
[4]	Shuangshuang Li,Wei Song,Liang Zou,Junying Min,Jianping Lin. Influence of the Windward Angle of Front Bumper Deflector on the Aerodynamic Drag of a Light Bus [J]. Automotive Engineering, 2022, 44(11): 1779-1785.
[5]	Yingchao Zhang,Tao Liu,Huinan Cao,Zhe Zhang,Guohua Wang. Optimization of Aerodynamic Drag Coefficient for a Cabover Truck Considering the Effects of Crosswind [J]. Automotive Engineering, 2021, 43(5): 713-720.
[6]	Hong Liao,Yaohui Lu,Qingyang Wang,Xiaochun Yin,Xiaobo Shi,Yanhui Tang. Research on the Influences of Side-Wing Diffuser on Automotive Aerodynamic Characteristics [J]. Automotive Engineering, 2021, 43(11): 1653-1661.
[7]	Li Xianjin, Li Zhelong. Research on Aerodynamic Characteristics of Rear Spoiler in an Electric SUV [J]. Automotive Engineering, 2020, 42(9): 1211-1215.
[8]	Wang Qingyang, Huang Wenpeng, Lai Chenguang, Zhu Xijia, Wang Yong. Study on Aerodynamic Drag Reduction of a HeavyTruck Based on Aerodynamic Accessories [J]. Automotive Engineering, 2020, 42(6): 746-752.
[9]	Song Xin, Li Shuya, Yan Jie, Liu Zheng, Yang Hui, Guo Xiquan. Study on the Correlation Between Digital Wind TunnelSimulation and Open Road Simulation [J]. Automotive Engineering, 2020, 42(6): 759-764.
[10]	Wang Jingyu, Yan Wei, Li Song, Hu Xingjun, Sang Tao, Wang Mo. Research on Microchannel Structure Optimization of Electric Vehicle Battery Cold Plate [J]. Automotive Engineering, 2020, 42(5): 672-680.
[11]	He Yansong, Cao Lipeng, Zhang Zhifei, Li Yun, Chen Zhao. Optimization of Vehicle Aerodynamic Drag Based on Discrete Adjoint Method and Surrogate Model [J]. Automotive Engineering, 2020, 42(11): 1577-1584.
[12]	Fang Jian & Wang Fuliang. A Study on CFD Simulation and Wind Tunnel Test on Aerodynamic Effectsof Wheel Rotation and Drag Reduction Optimization [J]. Automotive Engineering, 2019, 41(9): 1006-1012.
[13]	Yuan Zhiqun, Yang Mingzhi, Zhang Bingrong. A Study on Car Drag Reduction by Active and PassiveControl of Complex Underbody Flow Field [J]. Automotive Engineering, 2019, 41(5): 537-544.
[14]	Xu Jianmin. A Research on Drag Reduction of a Van-type Truck with a Bionic Cab-roof Fairing [J]. , 2019, 41(3): 283-288.
[15]	Peng Lijuan, Yuan Xiayi, Chen Zhifu, Tang Zhuliang, Chen Lin, Wang Chaoyi. Aerodynamic Performance Optimization and Verification of a SUV [J]. , 2019, 41(2): 147-152.

Study on Effect of Turbulence Model Coefficients on Accuracy of Aerodynamic Simulation

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 18

References 9

Related Articles 15

Metrics

Comments

Recommended 0