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In this article the unsteady aerodynamic properties of a 25% scale DrivAer notchback model as well as the influence of the wind tunnel environment on the resulting unsteady aerodynamic forces and moments under crosswind excitation are investigated using experimental and corresponding numerical methods. Research Institute of Automotive Engineering and Vehicle Engines Stuttgart (FKFS) swing® (side wind generator) is used to reproduce the essential properties of natural stochastic crosswind in the open jet test section of the Institute for Internal Combustion Engines and Automotive Engineering (IVK) model scale wind tunnel (MWK). The results show that the test environment of an open jet wind tunnel alters the amplitudes of side force and yaw moment under crosswind excitation when compared to an ideal environment neglecting wind tunnel interference effects.

In addition to the analysis of human driving behavior or the development of new advanced driver assistance systems, the high simulation quality of today’s driving simulators enables investigations of selected topics pertaining to driving dynamics. With high reproducibility and fast generation of vehicle variants the subjective evaluation process leads to a better system understanding in the early development stages. The transfer of the original on-road test run to the virtual reality of the driving simulator includes the full flexibility of the vehicle model, the maneuver and the test track, which allows new possibilities of investigation. With the opportunity of a realistic whole-vehicle simulation provided by the Stuttgart Driving Simulator new analysis of the human’s thresholds of perception are carried out.

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.

This paper describes a method to simulate underhood temperature distributions in passenger cars. A simplified engine compartment simulation test rig is used to perform measurements with well known boundary conditions to validate the simulation strategy. The measurement setup corresponds to idle without working fan. The aim of this setup is to validate cases with strong natural convection, e.g. thermal soaking. A coupled steady-state CFD run and thermal analysis is undertaken to simulate the temperature distribution in the test rig. Convective heat transfer coefficients and air temperatures are calculated in StarCD™. The radiative and conductive heat transfer is considered in a RadTherm™ analysis. The strong coupling of flow field and wall temperature in buoyancy driven flows requires an iterative process. Calculated temperatures are compared to measured results in order to validate the simulation method as far as possible. Some of the results are reported in this paper.

Within the scope of a current research project at the Research Institute of Automotive Engineering and Vehicle Engines Stuttgart (FKFS), the potential for an estimation of vehicle side slip angle and yaw rate arising from online measurement of tire forces is evaluated. Investigations focus on how the vehicle state can be determined, if in addition to wheel speeds and steering angle the tire forces currently acting on the vehicle are known. Different estimation procedures based on inverse tire models, direct integration of vehicle accelerations and closed-loop-observer are discussed. The performance is tested with data from vehicle dynamics simulation.