Author: Petter Ekman

Publisher: Linköping University Electronic Press

Published: 2020-04-02

Total Pages: 96

ISBN-13: 917929863X

Road transports are responsible for almost 18 % of the greenhouse gas emission in Europe and are today the leading cause of air pollution in cities. Aerodynamic resistance has a significant effect on fuel consumption and hence the emission of vehicles. For electric vehicles, emissions are not affected by the aerodynamics as such but instead have a significant effect on the effective range of the vehicle. In 2017, a new measurement procedure was introduced, Worldwide Harmonized Light Vehicles Test Procedure (WLTP), for measuring emissions, fuel consumption, and range. This procedure includes a new test cycle with increased average driving speed compared to the former procedure, which thereby increases the importance of the aerodynamic resistance, as it drastically increases with speed. A second effect is that the exact car configuration sold to the customer needs to be certified in terms of fuel consumption and emissions. The result is that every possible combination of optional extras, which might affect the aerodynamic resistance, needs to be aerodynamically analyzed and possibly improved. From 2021, the European Commission will introduce stricter emission regulations for new passenger cars, with the fleet-wide average lowered to 95 grams CO2=km, which puts an even higher demand on achieving efficient aerodynamics. Virtual development of the aerodynamics of road vehicles is today used to a great extent, using Computational Fluid Dynamics, as it enables faster and cheaper development. However, achieving high accuracy for the prediction of the flow field and aerodynamic forces is challenging, especially given the complexity of both the vehicle geometry in itself and the surrounding flow field. Even for a simplified generic bluff body, accurately predicting the flow field and aerodynamic forces is a challenge. The main reason for this challenge of achieving results with high accuracy is the prediction of the complex behavior of turbulence. Scale-resolving simulation (SRS) methods, such as Large Eddy Simulation (LES), where most of the turbulent structures are resolved has in many studies shown high accuracy but unfortunately to a very high computational cost. It is primarily the small turbulent structures within the near-wall region that requires a _ne resolution in both space (the mesh) and in time. This fine resolution is the reason for the very high computational cost and makes LES unfeasible for practical use in industrial aerodynamic development at present and in the near future. By modeling the turbulent structures within the near-wall region using a Reynolds-Averaged Navier-Stokes (RANS) model, and resolving the turbulence outside the region with a LES model, a coarser resolution is possible to use, resulting in significantly lower computational cost. Which used RANS model is of high importance, and especially how much turbulent viscosity the model generates, as too high values can result in suppression of the resolved turbulence. The transitioning between the RANS and LES regions have a significant effect on the results. Faster transition enables more resolved turbulence, favorable for higher accuracy, but needs to be balanced with sufficient shielding of the RANS region. If resolving the turbulence occurs within the near-wall region, and the mesh is not sufficiently fine, it can result in poor accuracy. By increasing the time-step size and disregarding best-practice guides, the computational cost can be significantly reduced. The accuracy is reasonably insensitive to the larger time step sizes until a certain degree, thereby enabling computationally cheaper SRS to achieve high accuracy of aerodynamic predictions needed to meet present and future emission regulations.