• Formula 1
• Handling
• Methodology
• Simulation
• Vehicle dynamics

Formula 1 is highly competitive, and teams work hard to reduce the lap time in every way they can. Handling is the study of how a vehicle responds to driver inputs, and good handling is crucial for the driver to use the full performance of his car. With tight regulations on track testing and limited availability of driver-in-the-loop driving simulators, optimization of handling is difficult. Starting a session with better handling properties and a clear idea on how setup changes affect handling leaves more time to focus on improving performance.

Therefore, it is desirable to evaluate handling properties before an event by using simulations. Current solutions to the problem used by Scuderia AlphaTauri are limited to quasi-steady simulations, which neglect transient effects. Since these are unable to accurately predict handling, the goal of this thesis is to develop a new method of analyzing vehicle handling based on vehicle dynamics simulations for Scuderia AlphaTauri.

To develop the new methodology, transient vehicle dynamics simulations without the simplifications of the quasi-steady method controlled by open-loop inputs or simple speed-controllers are used. The corner is first divided into four phases: End of straight, entry, apex and exit. Separate simulations are defined for each phase.

For the end of straight and apex phases, the vehicle is considered in an equilibrium state. Based on step steer simulations a frequency response function is calculated. For the entry and exit phases different maneuvers are analyzed and the time history is analyzed. Parameters are extracted to describe the vehicles straight line steering response, braking stability, apex steering response and reaction to throttle. Using the new methodology shows significant differences for typical setup changes.

The methodology developed in this thesis shows promising results to describe handling behavior. Due to the subjective nature of driver feedback on handling, evaluating the result is difficult, and should be done after using the method in practice.

Formula 1 is highly competitive, and teams work hard to reduce the lap time in every way they can. Handling is the study of how a vehicle responds to driver inputs, and good handling is crucial for the driver to use the full performance of his car. With tight regulations on track testing and limited availability of driver-in-the-loop driving simulators, optimization of handling is difficult. Starting a session with better handling properties and a clear idea on how setup changes affect handling leaves more time to focus on improving performance. Therefore, it is desirable to evaluate handling properties before an event by using simulations. Current solutions to the problem used by Scuderia AlphaTauri are limited to quasi-steady simulations, which neglect transient effects. Since these are unable to accurately predict handling, the goal of this thesis is to develop a new method of analyzing vehicle handling based on vehicle dynamics simulations for Scuderia AlphaTauri. To develop the new methodology, transient vehicle dynamics simulations without the simplifications of the quasi-steady method controlled by open-loop inputs or simple speed-controllers are used. The corner is first divided into four phases: End of straight, entry, apex and exit. Separate simulations are defined for each phase. For the end of straight and apex phases, the vehicle is considered in an equilibrium state. Based on step steer simulations a frequency response function is calculated. For the entry and exit phases different maneuvers are analyzed and the time history is analyzed. Parameters are extracted to describe the vehicles straight line steering response, braking stability, apex steering response and reaction to throttle. Using the new methodology shows significant differences for typical setup changes. The methodology developed in this thesis shows promising results to describe handling behavior. Due to the subjective nature of driver feedback on handling, evaluating the result is difficult, and should be done after using the method in practice.