Analysis of the Influence of Different Turbulence Models on the Prediction of Vehicle Aerodynamic Performance

Luwei Wang, Xingjun Hu, Peng Guo (), Zirui Wang, Jingyu Wang, Yuqi Wang, Yan Ma, Ying Li, Jing Zhao, Xu Yang, Ruixing Ma, Yinan Zhu and Jianjiao Deng
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Luwei Wang: National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun 130012, China
Xingjun Hu: National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun 130012, China
Peng Guo: National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun 130012, China
Zirui Wang: National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun 130012, China
Jingyu Wang: National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun 130012, China
Yuqi Wang: National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun 130012, China
Yan Ma: China First Automobile Group Co., Ltd. R & D Institute, Changchun 130000, China
Ying Li: China First Automobile Group Co., Ltd. R & D Institute, Changchun 130000, China
Jing Zhao: China First Automobile Group Co., Ltd. R & D Institute, Changchun 130000, China
Xu Yang: China First Automobile Group Co., Ltd. R & D Institute, Changchun 130000, China
Ruixing Ma: China First Automobile Group Co., Ltd. R & D Institute, Changchun 130000, China
Yinan Zhu: China First Automobile Group Co., Ltd. R & D Institute, Changchun 130000, China
Jianjiao Deng: China First Automobile Group Co., Ltd. R & D Institute, Changchun 130000, China

Energies, 2025, vol. 18, issue 11, 1-17

Abstract: As global energy grows short and environmental governance pressure increases, the automotive industry, a major energy consumer and pollution emitter, must enhance vehicle aerodynamics to cut energy use and emissions. This study creates an open-domain and virtual wind tunnel dual-computational-domain setup. It optimizes mesh refinement and boundary conditions, and evaluates the k-ε, k-ω, and Detached Eddy Simulation (DES) turbulence models. These models predict vehicle aerodynamic resistance, lift, and wake flow structure. The k-ε model best predicts the steady-state drag coefficient (Cd) (error 0.0009). DES excels in transient conditions (Cd error −0.4%, lift coefficient Cl matching experiments). The k-ω model, with its near-wall flow capture ability, has the lowest lift prediction error (−2.7%). Moreover, open-domain simulations align more closely with real free-flow environments and experimental data than virtual wind tunnel simulations. Overall, the study clarifies the varying applicability of turbulence models in complex flows, and offers a basis for model selection and technical support for vehicle aerodynamic optimization. It is highly significant for reducing fuel consumption, boosting the range of new-energy vehicles, and promoting sustainable industry development.

Keywords: computational fluid dynamics; wind tunnel experiments; different turbulence models; virtual wind tunnel simulation technology; energy efficiency; vehicle aerodynamics (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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