Drag Analysis of Autonomous Vehicles in Different Arrays using CFD simulations

Abstract

Autonomous vehicles, which are defined as capable of sensing environment and navigating without any human input, are the top trend of the automotive industry. 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 vehicle 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 analysed. 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.