Wheel design and wheel rotation have been identified to be key factors influencing the overall aerodynamic performance of passenger cars. Hence, wheel aerodynamics has been the topic of various studies over the past few years. Recently, vehicle manufacturers have moved towards time-resolving CFD simulation methods. Therefore, a trend towards resembling the physical effect of wheel rotation by utilizing the Sliding Mesh Method can be observed in academia and the industry. The first part of the presented paper shows the results of CFD simulations using the Sliding Mesh Method on two generic test cases employing the Delayed Detached Eddy Simulation turbulence model. A rotating cylinder is investigated as well as a rotating wheel geometry, both in ground contact and lifted from the ground. The results show dependencies on the solution algorithm and the background turbulence model applied within the RANS region of the Delayed Detached Eddy Simulation model. The prediction accuracy of the CFD setup is assessed by comparing the results to experimental results on the rotating wheel geometry with ground contact obtained in a model scale wind tunnel. The second part of the paper focuses on the influence of the rim design on the aerodynamics of a full vehicle. Four rim geometries are investigated regarding their aerodynamic influence on the DrivAer reference body by CFD simulations using the Sliding Mesh Method. The DrivAer has recently been updated to include an engine bay geometry. This new version of the DrivAer is used for the presented study because the engine bay flow is expected to have a considerable influence especially on the flow around the front wheels. The simulation results are compared to experimental results obtained on a 1:2.5 scale model of the DrivAer with engine bay flow and are in good agreement.
Temporally resolved flow fields are commonly averaged in time, and mostly the time-averaged flow fields and forces are used for the aerodynamic optimization of road vehicles. Online DMD is found to be well suited for studying transient flow effects and leads to a deeper understanding of the complex flow around the vehicle. The investigated velocity field is computed by a Detached Eddy Simulation of the DrivAer reference body. The CFD setup and key considerations for the application of online DMD on large data sets are outlined, and the most dominant extracted coherent flow structures are analyzed independently.
It is believed that Dynamic Mode Decomposition (DMD) is a very useful method for the analysis of unsteady aerodynamics of road vehicles. However, it seems that the conventional DMD method is not practical regarding the application on the aerodynamic design of road vehicles, since DMD computation requires massive memory. Alternatively, online DMD methods seem to be useful in practice, as those require much less memory than the conventional method. In this paper, further validation of the online DMD on the aerodynamic forces on the DrivAer model is conducted, through the comparison with results from other enhanced DMD methods and FFT.
Wheel aerodynamics has a major impact on the overall aerodynamic performance of a vehicle. Different vortex excitation mechanisms are responsible for the induced forces on the geometry. Due to the high degree of complexity, it is difficult to gain further insight into the vortex structures at the rotating wheel. Therefore, wheel aerodynamics is usually investigated using temporally averaged flow fields. This work presents an approach to apply a recently introduced low-memory variant of Dynamic Mode Decomposition (DMD), namely Streaming Total DMD (STDMD), to investigate temporally resolved simulations in greater detail. The performance of STDMD is shown to be comparable to conventional DMD for a rotating generic closed wheel simulation test case. By creating a Reduced-Order Model (ROM) using a comparably small amount of DMD modes, the amount of complexity in the flow field can be drastically reduced. Orthonormal basis compression, amplitude ordering and a newly introduced amplitude weighting method are analyzed for creating a suitable ROM of DMD modes. A combination of compression and ordering by eigenvalue-weighted amplitude is concluded to be best suited and applied to the Delayed Detached Eddy Simulation (DDES) of the rotating generic closed wheel and a production vehicle rim wheel. The most dominant flow structures are captured at frequencies between 18Hz and 176Hz. Leading modes for both geometries are found close to the wheel rotation frequency and multiples of that frequency. The modes are identified as recirculation modes and vortex shedding.
To further reduce the aerodynamic drag of passenger vehicles, a deeper understanding of the flow field is required. Analysis methods like the dynamic mode decomposition (DMD) are useful to investigate unsteady flow phenomena around the vehicle. DMD results are only relevant for the aerodynamic development, if the used numerical data is able to predict the unsteady physical flow field. Therefore, in this study unsteady hot-wire data in the wake of a passenger vehicle is compared to a numerical dataset of an unsteady Spalart-Allmaras Delayed Detached Eddy simulation. Differences and wind tunnel effects are found and explained.
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