Downforce plays an important role in cornering performance of a car. Across a lap, the vehicle will experience changes in attitude due to braking, cornering and acceleration. These changes in yaw, pitch, roll and steer affect the aerodynamic performance and overall downforce the car is producing. Thus, the cornering potential changes depending on the car’s ‘attitude’. If these changes and their relationship with downforce are not well understood, it creates uncertainties in the car’s cornering performance.

One solution to tackle these uncertainties might be using an unsprung aerodynamic package, in which the aerodynamic devices can move independent of the vehicle body and maintain their designed position with respect to the ground. The team has used such aero packages previously, as well as semi-unsprung packages. However, these packages add to the complexity of the vehicles which in turn increases the number of failure modes.

Another alternative solution is to determine a method of understanding the relationship between ‘attitude’ and performance. This method would allow the optimization of the aero design and vehicle dynamics in parallel resulting in best performance across a competition or lap.

One common method to achieve a proper understanding of these relationships is through aerodynamic mapping. An aero map is a chart which shows the changes in a performance metric such as; CLA,CDA and balance as a function of the car attitudes.

For example, ground effect devices like diffusers and front wings are particularly sensitive to change in pitch of the car. Analyzing the effect of pitch on downforce would require an aero map showing the CLA for given ride height values at the front and rear of the car. Similarly, one could create aero maps which would tell us about the effect of roll, yaw and steer, on a specific metric.

While analyzing pitch, front and rear ride height data points from either testing or simulation are overlaid onto the aero map to get a range of attitudes we are actually seeing on track. We can thus visualise the expected ride height range across a lap and integrate it with suspension design allowing optimisation of the overall car rather than individual systems. A compromise in the suspension geometry is made such that the car remains in the range of attitudes with highest downforce and lowest sensitivity. We then weigh up the metrics and establish a compromise between predictability and overall downforce.

So how do we create our Aero maps? Based on attitudes we see on track, we know the range of front and rear ride heights, yaw, steer and roll angles our cars are likely to experience. Using this data, we carry out a baseline CFD run at a certain attitude which is most frequently experienced and weighted heavily across laps for various tracks. Then, multiple CFD simulations are carried out by varying parameters like front & rear ride height, roll, yaw and steer. Results from these simulations, CLA or CDA, are compared to the baseline CFD run and plot on a chart as a function of these parameters to create an aero map.

However, CFD models are idealisations of real-world situations and the predicted flow structures may vary compared to on-track conditions. To mitigate inaccuracies in CFD simulations, it is also important to complete real world testing. During testing of our cars, pressure taps are used to look at the pressure readings on certain points of the wing and then correlate them with CFD simulations. Currently we are looking at how this pressure tapping data could be used to refine the aero maps for our cars.

Using Aero maps not only helps us understand the sensitivity of our aero packages for various parameters, but also enables us to visualize aero balance across the attitude range. It ensures that our aero platform designs are stable across a range of vehicle attitudes and helps us in driving suspension design decisions. Thus, instead of chasing aerodynamic target metrics in straight-line, by including aero mapping in the design process, we optimize performance across the lap, improving lap time and potential for points.

Aero Mapping

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