Your shopping cart is empty.
Product Qty Amount

[email protected]
/ Categories: Archive, testing


In Formula One, every decade sees new off-track technologies pushing car performance on track. In the 1980s, wind tunnels became the ‘must-have facility’; in the 1990s CAD and CFD systems revolutionised car design, while the first decade of the 20th century has seen simulators emerge as a vital development tool. Initially introduced as driver training aids, simulators are now at the stage where they can also be used to actually develop a car, referred to as ‘driver in the loop’ testing.

Ever-tightening track testing restrictions has meant that teams have had to rely increasingly on off-track testing methods in order to develop their cars both before and during the season. This has seen considerable investment in facilities such as wind tunnels, with many teams running tunnels continuously to test different component iterations.

However, recognising that this was leading to spiralling costs, the FIA began to place limits on the volume of off-track testing that could be undertaken, specifically targeting wind tunnels. Computer simulation packages also came to the fore, combining data collected on track, on test rigs and from CFD and wind tunnel testing to simulate the impact of set-up changes or new components. With the increase in complexity of these simulations, ever more powerful computing facilities were required to process the vast quantities of calculations required. But the constantly falling cost and rising power of mainstream computers have made it possible for even small teams to have processing power which even the top teams could only dream of a decade ago.

Track testing restrictions not only impact car development programmes but also have implications for drivers, both experienced and inexperienced. New drivers no longer have the opportunity to gain experience in Formula One machinery, while current drivers are left with only a couple of free practice sessions in which to acclimatise to new car developments. To counter this, driver simulators have seen widespread adoption to mitigate some of these problems. While simulators have long been in use in the aviation industry, machines capable of realistically representing the forces experienced in a modern Formula One machine have only recently become widely available. Tricking the human brain into believing that the body is experiencing lateral, horizontal and vertical accelerations without moving it any great distance is no mean feat.

While there have been simulators that work on rails, along which the whole driver capsule is accelerated, these require a lot of space and are limited to one or two acceleration events in a row, making them unsuitable for replicating the rapid accelerations and decelerations encountered in a racecar. Instead, most simulators (at least those used by Formula One teams) are now of the ‘six degrees of freedom’ variety. These place the driver – often in a replicated vehicle cockpit – on a platform supported by hydraulic actuators that provide forward, backward and lateral movement, as well as rotation around the x, y and z axes.

These simulators do not recreate the precise movements of a racecar; instead they trick the driver’s brain into thinking they are experiencing greater directional changes than are actually occurring. The key is to provide these cues in a subtle fashion. For example, if the platform tilts too much while simulating a cornering event, the driver will recognise that it is tilting, rather than associate the forces as those experienced during a high-speed turn. It is a fine line for simulator developers to tread, but when the correct level of cueing is achieved, time spent in a simulator will invariably correlate directly with performance on the track.

Beyond simple driver training, the accuracy of the latest generation of simulators means they can be used reliably as a development tool. The physics engines that determine car behaviour – dictating everything from steering feedback to grip levels and aerodynamic downforce – are fed real-world data, including aero maps and tyre models. The result is that the impact on performance of car set-up changes can be assessed without the car every hitting the track. As mentioned earlier, it is possible to do this using regular simulation tools, but the factor these tools lack is the impact of the driver on car performance.

The best example of why this could be a problem is where a set-up derived from a simulation should theoretically reduce lap times, yet on track the changes present a driver with handling traits that prevent them from exploiting the theoretical performance. Given the limited testing time teams are allowed, this equates to a substantial waste of resources. If, however, the team and driver can test changes in a simulator, eliminating those which will definitely not work, then time spent trackside can be dedicated to developments with a greater chance of improving performance.

To this end, it is not unusual for teams to have a dedicated ‘sim’ driver, who will be testing set-up changes as a Grand Prix weekend progresses. The caveat here though is that, as with any ‘virtual’ testing tool, the data generated from simulators is only as accurate as the data fed in. Therefore a careful eye must be kept on the correlation between simulated and on-track results. As long as this condition is taken into account, simulators assume a similar role to that of CFD, acting as a filter for developments that will not work and reducing the amount of resources wasted on blind alleys in either the wind tunnel or at the track.


Fig. 1 - Most Formula One teams now rely on simulators for both driver and car development (Courtesy of Red Bull Racing)

Written by Lawrence Butcher

Next Article Particle image velocimetry