Development of a Surrogate Model for Drag Prediction of Cars Based on Wind Tunnel Data in the Context of Aerodynamic Optimization of Tires

The scope of this publication is to present the research line and status of data-driven models that predict the drag coefficient of cars with wind tunnel data, in the context of aerodynamic optimization of tires. Advancements in two Machine Learning models under development are presented, one with internal BMW wind tunnel data (with 18 dat-points) and one with 500 aerodynamic open source simulations.