Complete Body Aerodynamic Study of three Vehicles

Cooling drag, typically known as the difference in drag coefficient between open and closed cooling configurations, has traditionally proven to be a difficult flow phenomenon to predict using computational fluid dynamics. It was seen as an academic yardstick before the advent of grille shutter systems. However, their introduction has increased the need to accurately predict the drag of a vehicle in a variety of different cooling configurations during vehicle development. This currently represents one of the greatest predictive challenges to the automotive industry due to being the net effect of many flow field changes around the vehicle. A comprehensive study is presented in the paper to discuss the notion of defining cooling drag as a number and to explore its effect on three automotive models with different cooling drag deltas using the commercial CFD solvers; STARCCM+ and Exa PowerFLOW. The notchback DrivAer model with under-hood cooling provides a popular academic benchmark alongside two fully-engineered production cars; a large saloon (Jaguar XJ) and an SUV (Land Rover Range Rover). Initially three levels of spatial discretization were used with three steady-state RANS solvers (k-ɛ realizable, k-ω SST and Spalart-Allmaras) to ascertain whether previous work using RANS on the large saloon studying cooling flows could be replicated on other vehicle shapes. For both the full-production vehicles, all three turbulence models were capable of predicting the cooling drag delta within 5 counts (0.005 Cd). However, the DrivAer model was much more sensitive to both changes in turbulence models and mesh sizes. For the SA turbulence model only the drag coefficient was well predicted, for the other two RANS models no amount of grid refinement allowed the models to correctly predict the flow field. It was seen when comparing the k-ɛ realizable and SA turbulence models the difference in cooling drag was attributed to the rear of the vehicle. This highlighted that despite similar drag values from the cooling package, the cooling deltas were very different, suggesting that cooling drag cannot be thought of as open-closed drag with the addition of drag due to the cooling package. Further work on the DrivAer model expanded on the RANS simulations utilizing the eddy-resolving methods, IDDES and LBM, as validation cases. Oscillations which were seen in the SA and k-ω SST RANS turbulence models were shown to be of similar levels to those in the transient methods indicating a pseudo-unsteadiness present in the steady-state solvers and the importance of resolving it. Drag and lift coefficient absolute values were compared showing that only the IDDES method with sliding wheels and LBM method could obtain physical results for the majority of the tested criteria. Introduction Current and future regulations in the automotive industry place a high importance on the environmental impact of vehicles. It is becoming increasingly important to be able to calculate the drag of each vehicle specification and the affect of each changeable component on the final configuration. Wind tunnels can obtain all this information but it is difficult to create representative prototypes early enough in the development process. With ever increasing computational power available Computational Fluid Dynamics (CFD) provides the ability to simulate and calculate the drag configurations for a variety of models, while state-of-the-art multi-physics simulations with coupling of aerodynamics, thermal management and power-train simulations provide the potential to model real-time simulations. This paper focuses on increasing understanding of so-called cooling air drag, as applied to a fully engineered production large saloon and SUV, this is achieved by discussing the concept of cooling drag vs. complete body aerodynamic simulations and comparing against the popular benchmark DrivAer model.