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The upstream flow conditions and the use of tractive power to accelerate a vehicle are both sources of energy loss. The vehicle speed and the upstream flow conditions result in the oncoming wind vector experienced by the moving vehicle. The aim of the present work is to show a new approach to consider the chaotic and random behavior of surrounding flow conditions and their influence on driving performance. The approach is shown for the example of motorbike racing conditions. Special interest was put on a description of the flow conditions with respect to well know turbulent flow field parameters like the turbulent length scale or the turbulence intensity. Depending on where the flow conditions are measured, stationary in the earth reference frame, or on a moving vehicle, it is quite difficult to get a robust description of the flow field parameters. These parameters are used together with the Reynolds number to predict the aerodynamic behavior by correlation functions or maps.

World Championship races are the competition of the fastest motorcycle riders in the world. They are a rare selection of professionals which can ride race bikes on the absolute physical limits in the longitudinal and lateral direction. The exact understanding of race bike performance for race engineers, riders and race bike development companies is quite difficult as the movement of a race bike and a rider is a complex combination of various physical effects. The aim of the present work is to approach the understanding of race bike performance from a scientific point of view. The actual assessment of race bike performance is mainly data-driven and based on the comparison of racing lines and single measurement channels for different laps and race events. The new approach is to add physical multibody models to understand single segments from real-world racetrack measurements.