Automotive Aerodynamics
2.3 Methods used for Evaluating Automotive Performance
(a) Aerodynamic downforce versus wing angle of at- tack, uncertainty inCL=±0.03, inα=±0.2◦.
(b) Aerodynamic drag versus wing angle of attack, uncertainty inCD=±0.015, inα=±0.2◦.
Figure 2.5: Interaction between the rear wing and the car body [21].[coefficients based on the car reference area;c: chord;αw: wing angle of attack;∆H: rear wing height from car;∆x: rear wing backward position from rear deck;A: aspect ratio;β: under-body channel angle.]
edge, perpendicular to the chord line. It was used on race cars prior to aerospace applications as a small vertical reinforcement because of the high speed and structural considerations and to the surprise of aerodynamicists, a drag reduction was reported along with the increase in the overall efficiency [14].
The effect of such devices on highly cambered wings is a result of the trailing edge boundary-layer reattachment as well as a change in the direction of the trailing edge flow, inducing larger circulation [24]. Three-dimensional effects on airplane wings were conducted by Myoseet al. [25] who measured a13% increase in the maximum lift coefficient (CLmax) for a small drag penalty compared with a clean wing, improving theL/Dratio.
In three-dimensional wings (or finite wings) such as the front and rear wing, the flow around the side edge (tip) must be considered as the pressure difference between the upper and lower surfaces cannot be maintained, generating strong wing-tip vortices which reduce its effectiveness [1]. In order to over- come this problem ofleaking flow, endplates are used to separate both surfaces of the wing maintaining a two-dimensional effect at the wing-tip and improving its efficiency [1, 3, 6]. In general, increasing the endplate size increases the downforce generation and improves both vehicle yaw acceleration and steady state cornering [23].
most reliable way to effectively improve a vehicle performance.
2.3.1 Numerical Simulations
CFD is a modern computational analysis tool that provides numerical solutions using algorithms to solve fluid flow governing equations (Navier-Stokes equations), in order to simulate determined physi- cal conditions. Motorsport was one of the first professional sports to adopt commercial CFD tools for competitive advantage because of its relative cheapness and scalable knowledge, relative to building further wind tunnels. Besides the increase of computational power over the last two decades, the other biggest influence on the CFD market has been the growth of CAD tools, which enabled complex real- world geometries to be created and parametrised [26]. Combining both CAD and CFD tools, engineers could quickly evaluate and develop new design ideas without the requirement of costly prototype testing.
However, such instrument has its own weaknesses. It is only a simulation of what could happen in the real world, and the numerical solution strongly depends on user-defined elements (mesh generation and turbulence modelling). Such modelling techniques have an important effect on the quality of the numerical solution, in particular for the prediction of flow separation (in smooth curved surfaces) and for the transition from laminar to turbulent flow at high-Reynolds numbers [14].
One example of the research of such user-defined elements influence are the American Institute of Aeronautics and Astronautics (AIAA) CFD Drag Prediction Workshops. They have been comparing several solutions methods with wind tunnel results for the flow over generic airplanes configurations, spe- cially the prediction of the incremental drag associated with the nacelle/pylon installation [27, 28, 29].
In general, the conclusion is that the grid attributes (quality and resolution) and turbulence modelling choice have a crucial affect in the results of the force coefficients, due to differences both in friction drag and predicted flow phenomena, such as the large separation zone at the wing-body junction. Although achieving good comparison with experiment results, in general the estimation of lift is more accurate (although over-predicted) than that of the drag force (usually under-predicted). Same results were ob- tained by Wordley & Saunders [23] for example. Such conclusions are as well very relevant to the high-Reynolds number flow over race cars, dominated by both laminar and turbulent flow regimes and localised flow separations.
2.3.2 Wind Tunnel Testing
As the capability of a CFD simulation to predict flow behaviour depends on the modelling techniques utilised, it is very important to validate and correlate CFD results with physical experimentation. This can be achieved through road or track testing, however, a safer and more convenient alternative is the use of scale model wind tunnel testing. Besides the cost reduction, such facilities provides a controlled test environment isolated from external weather effects.
Wind tunnel methodology became an essential tool in the race car design during the 1960s, when the significance of aerodynamics was realised (Section 2.1). At this time, such methods were already advanced and widely used by the aerospace industry, but such facilities imposed several difficulties for
the testing of race cars. The major problems was due to the small clearance between the vehicle under- body and the stationary floor of the test section and the mounting of the rotating wheels [14]. These are very important measures to take in account when testing vehicles performance and the moving ground simulation is essential for such cases [16]. Solutions to simulate the moving ground simulation were reported by Katz [1], in the form of blowing, suction, rolling grounds, symmetry or all of them combined, along with techniques for the mounting of rotating wheels.
Through the 1980s and 1990s customised wind tunnel facilities were rapidly increasing and devel- oped for general automotive and race car testing, all with moving ground simulation [1]. In order to avoid or minimise effects of blockage and boundary layer generation, working section area, model size and correct Reynolds number must be carefully selected to accurately predict aerodynamic behaviour of full-size models.
2.3.3 Road and Track Testing
Comparing both experimental methodologies used to evaluate aerodynamic performance of vehicles, the difficulties associated with wind tunnel testing: moving ground, rolling wheels, the correct Reynolds number and wind tunnel blockage correction, are all resolved on the full-scale testing on the road or race track. Although the vehicle must exists, be more expensive (track renting if not owned by manufacturers and instrumentation) and dependent on the weather conditions, with the advance in sensor technology and data acquisition systems, desirable forces, moments and pressures can be easily measured, trans- mitted via wireless communication and analysed in real time [14]. If the external conditions cooperate, this is ultimately the most accurate way to evaluate the vehicles performance and to validate CFD or wind tunnel results.