CFD drag analysis of autonomous vehicles in different arrays 2018-36-0184
Autonomous vehicles, which are defined as capable of sensing environment and navigating without any human input, are the top trend of the automobilist industry in terms of technology. The computers responsible for the control are able to set the vehicle to optimum operation point. With the advent of Computational Fluid Dynamics -CFD software, it is possible to study drag reduction proposals when the vehicles drive at the velocity, which contributes to increase fuel economy. In this context, based on a sedan virtual drag model, several simulations cases were developed considering different vehicle arrays and changing the distance between each one. The study aims to demonstrate, using virtual simulations, the potential drag coefficient reduction when vehicles are moving in a constant speed and which configuration leads to better performance increment. Taking the isolated vehicle as the baseline value, all the vehicles in the different arrays were analyzed. Results show that the vehicles staying behind the first vehicle in the arrays have better drag coefficient performance. Considering the presented results, it is possible to apply this methodology to others types of vehicles and optimize the driving of autonomous vehicles.
Citation: Buscariolo, F., Magazoni, F., Volpe, L., Maruyama, F. et al., "CFD drag analysis of autonomous vehicles in different arrays," SAE Technical Paper 2018-36-0184, 2018. Download Citation
Filipe Fabian Buscariolo, Felipe Magazoni, Leonardo José Della Volpe, Flavio Koiti Maruyama, Julio Cesar Lelis Alves
Imperial College London/NDF-USP/McLaren Racing, Thermax/NETeF-USP, GM North America, UFABC