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In this paper the influence of different turbulent flow conditions on the aerodynamic drag of a quarter scale model with notchback and estate back rear ends is investigated. FKFS swing® (Side Wind Generator) is used to generate a turbulent flow field in the test section of the IVK model scale wind tunnel. In order to investigate the increase in drag with increasing yaw, a steady state yaw sweep is performed for both vehicle models. The shape of the drag curves vary for each vehicle model. The notchback model shows a more pronounced drag minimum at 0° yaw angle and experiences a more severe increase in drag at increasing yaw when compared to the estate back model. Unsteady time averaged aerodynamic drag values are obtained at two flow situations with different turbulent length scales, turbulence intensities, and yaw angle amplitudes. While the first one is representing light wind, the second one is recreating the presence of strong gusty wind.

In the present work we investigated experimentally and computationally the unsteady flow around a BMW car model including wheels*. This simulation yields mean flow and turbulence fields, enabling the study aerodynamic coefficients (drag and lift coefficients, three-dimensional/spatial wall-pressure distribution) as well as some unsteady flow phenomena in the car wake (analysis of the vortex shedding frequency). Comparisons with experimental findings are presented. The computational approach used is based on solving the complete transient Reynolds-Averaged Navier-Stokes (TRANS) equations. Special attention is devoted to turbulence modelling and the near-wall treatment of turbulence. The flow calculations were performed using a robust, eddy-viscosity-based ζ - ƒ turbulence model in the framework of the elliptic relaxation concept and in conjunction with the universal wall treatment, combining integration up to the wall and wall functions.

The aeroacoustic development of vehicles is still mainly carried out in wind tunnels under steady flow conditions, although the real situation is different. However, as discussed in several earlier publications, a vehicle experiences unsteady, turbulent flow on road, which results for example from natural wind, wakes of other vehicles, or obstacles at the roadside in combination with side wind. The resulting temporal variations of the wind noise inside the cabin affect the passengers’ comfort and safety through fatigue. To be able to also consider the unsteady aeroacoustics in the vehicle development process, a comprehensive method has been developed that is presented in full for the first time in this paper. The on-road situation is simulated in a realistic and reproducible manner in the full-scale wind tunnel of the University of Stuttgart by means of an active turbulence generator, developed by FKFS.

This paper introduces an innovative approach, named synergetic 1D-3D-Coupling, by using synergy effects of 1D and 3D simulation in order to bring down modeling and simulation efforts. At the same time the methodology sustains the spatial resolution of a 3D model. This goal is reached by reducing the 3D fluid side with its time consuming continuity, momentum, energy and turbulence equations to a simple but precise 1D model. Because of the solid structure staying three dimensional, heat flux direction and spatial resolution have 3D accuracy but short calculation times due to the simple heat diffusion equation to be solved. The 1D model is represented by an automatically generated equation system which is capable of considering transient effects. The energy transfer between 1D fluid model and 3D structure model is realized through a neutral 1D-3D-coupling program and the application of the fluid element specific Nusselt correlations.

Typical automotive research in wind tunnels is conducted under idealized, stationary, low turbulence flow conditions. This does not necessarily reflect the actual situation in traffic. Thus, there is a considerable interest to simulate the actual flow conditions. Because of this, a system for the simulation of the turbulence intensity I, the integral linear scale L and the transient angle of incidence β measured in full-scale tests in the inflow of a test vehicle was developed and installed in a closed-loop, closed test section wind tunnel. The system consists of four airfoils with movable flaps and is installed in the beginning of the test section. Time-series of the flow velocity vector are measured in the empty test section to analyze the system’s envelope in terms of the turbulence intensity and the integral length scales.

Natural wind, roadside obstacles, terrain roughness, and traffic influence the incident flow of a vehicle driven on public roads. These transient on-road conditions differ from the idealized statistical steady-state flow environment utilized in CFD simulations and wind tunnel experiments. To understand these transient on-road conditions better, measurements were performed on German public highways and on a test site. A compact car was equipped with a measurement system that is capable of determining the transient airflow around the vehicle and the vehicle’s actual driving state. This vehicle was driven several times on a predefined 200 km long route to investigate different traffic densities on public highways in southern Germany. During the tests the transient incident flow and pressure distribution on the vehicle surface were measured.

A computational study of the vehicle aerodynamics influenced by the wake of the rotating wheel taking into account a detailed rim geometry is presently performed. The car configuration corresponds to a full-scale (1:1) notchback configuration of the well-known ‘DrivAer’ vehicle model, Heft et al. [1]. The objective of the present work is to investigate the performance of some popular turbulence models in conjunction with different methods for handling the wheel rotation – rotating wall velocity, ‘multiple reference frame’ and ‘sliding grid algorithm’. The specific focus hereby is on a near-wall RANS eddy-viscosity model based on elliptic-relaxation, sensitized to resolve fluctuating turbulence by introducing a specifically modeled production term in the scale-supplying equation, motivated by the Scale-Adaptive Simulation approach (SAS, [2]), proposed by Krumbein et al. [3].