Our previous articles discussed the effect of drag, downforce, aerodynamic drivability and driver’s confidence on lap time. In this article we will discuss the role of aerodynamic performance predictability on the setup optimisation.
Racing teams carry out significant pre-event work using historical data and simulations to predict the ideal starting setup for a race weekend. During the weekend there are limited opportunities for on-track performance optimisation, therefore it is crucial for the teams to start running with a setup already very close to optimum.
The key aerodynamic parameters affecting the car setup for a given circuit are:
- Cooling specification, covering bodywork aperture sizes, radiator blanking, brake ducts and brake drums
- Rear wing specification to determine the optimum compromise between downforce and drag
- Front wing specification to determine the target balance and balance range required
- Ride heights
The quality of the prediction of the initial setup is determined by the quality the historical data and simulation tools the team has in hand. Parameters affecting this include the quality of the predicted aerodynamic performance map from the wind tunnel and CFD compared to the reality on track, the team’s ability to correctly model the through-lap car performance and the team’s ability to extrapolate their knowledge to new operating conditions such as a new car derived from a new set of regulations, a new circuit or unusual weather conditions.
In Formula 1 we often see teams struggling on Friday practice, which then lead them to implement significant changes ahead of the Saturday running. Even though these changes can recover some of the “missing” performance, the team will likely have a car which is less optimised in qualifying and race compared to the car from another team who started the first Friday practice with the setup close to optimum.
In summary, our articles so far have highlighted that aerodynamic performance is far from being about “more downforce and less drag” only. The performance has to be delivered in a way which minimises compromises across different types of corners of the track, delivered in a predictable or drivable manner, it should enhance the driver’s confidence in his car, and the team must be able to predict the optimum setup beforehand to give the track engineers the highest chance to maximise the car performance.
From the next article onwards, we will move the discussion to the predictability of aerodynamic performance, discussing the role of predictive tools such as wind tunnels, CFD and other data-driven tools