Asset Details
Do you wish to reserve the book?
Analysis of the Influence of Different Turbulence Models on the Prediction of Vehicle Aerodynamic Performance
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Analysis of the Influence of Different Turbulence Models on the Prediction of Vehicle Aerodynamic Performance
Do you wish to request the book?
Analysis of the Influence of Different Turbulence Models on the Prediction of Vehicle Aerodynamic Performance
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Analysis of the Influence of Different Turbulence Models on the Prediction of Vehicle Aerodynamic Performance
2025
Overview
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.
Publisher
MDPI AG
