Taking Human Driver Skills into Account

Driver and track-specific optimal setups are required to achieve victories in motorsport. The setup is typically tuned on race tracks, however, testing on race tracks and using driving simulators is time-consuming and often limited. Setup tuning can also effectively be supported by applying advanced simulation models. Due to the availability of more accurate and applicable measurement equipment and increasing computing power, realistic and validated models may help to find the optimal setup.

Previous lap time simulations have taken driver skills insufficiently into account. The optimal setup found in this way can only be transferred to the real vehicle to a limited extent. As a consequence, the aim of the project (thesis) is the utilisation of offline simulation for an optimal setup and race trajectory, taking human rider skills into account. Therefore, the driver's skills are mapped to the drivability of the vehicle. The trade-off between performance (i.e. minimum lap time) and drivability is studied in detail and a practice-oriented setup optimization based on off-line simulations, where the defined design process allows for an effective combination of test drives and simulations, is proposed. To demonstrate and validate this design process, an example use-case is shown and discussed.

Figure 1: Race lines for 3 different drivers with respective optimised setups based on their individual driver skill

References

Ganzner, Mathias. "Simulationsbasierte optimale Lösung des Zielkonfliktes zwischen Performance und Fahrbarkeit in der Rennfahrzeugabstimmung., opens an external URL in a new window" PhD thesis, Technische Universität Wien, 2023.

Paper preparation in progress

Researcher

• Mathias Ganzner

Project Partner

• Porsche Motorsport