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

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

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...

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Bibliographic Details
Main Authors: Luwei Wang, Xingjun Hu, Peng Guo, Zirui Wang, Jingyu Wang, Yuqi Wang, Yan Ma, Ying Li, Jing Zhao, Xu Yang, Ruixing Ma, Yinan Zhu, Jianjiao Deng
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Energies
Subjects:
computational fluid dynamics
wind tunnel experiments
different turbulence models
virtual wind tunnel simulation technology
energy efficiency
vehicle aerodynamics
Online Access:https://www.mdpi.com/1996-1073/18/11/2803
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Summary: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.
ISSN:1996-1073

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