A Novel IoT-Based Architecture for Self-Adaptive Aerodynamic Flow Control System for Motorcycle

In this paper, we introduce an autonomous system for aerodynamic flow control for motorcycle based on the Internet of Things (IoT) paradigm. The architecture we propose adapts dynamically the flows at the traveling conditions, in order to obtain an improvement of performance and vehicle stability. In our architecture, we deploy a group of sensors on the top surface of the wings to sense the air pressure. We design a centralized on-board unit that computes a new wing angle of attack according to the data received from the sensors. The on-board unit includes a local information database which represents its knowledge: it stores both the data gathered by the sensors and the fluid dynamics model used to compute and adjust the angle of attack. The on-board database is periodically updated transmitting all the measurements gathered from the sensors to a High-Performance Cloud Data Center (DC) which executes a parallel version of Computational Fluid Dynamics (CDF) algorithms, computes the updated model, and transmits the processed information back to the on-board unit. We perform preliminary tests in the wind tunnel, and we show how the cooperation between IoT devices and DC can reduce the on-board unit computational effort.