Optimal resource selection and sizing for unmanned aerial vehicles

Drones are gradually becoming an integral part of several applications like package delivery, military reconnaissance, and automated inspection systems. Drones may utilize one source of energy, which is usually a battery. However, drones operating on fossil fuels and large capacity fuel cells also exist. This paper introduces a novel optimization framework to decide on the optimal source or mix of sources to be installed on drones to minimize their running cost. The proposed approach considers three sources: batteries, fuel cells, and super-capacitors, the characteristics of which are embedded in the optimal selection approach. In addition, a drone aerodynamic model is incorporated, which is composed of four actions: hovering, ascending, descending, and moving forward. The proposed approach selects the optimal source(s) from a defined database of sources to power the drone according to the user-specified trip profile. The offline simulation of various case studies shows that the proposed framework enables the selection of appropriate power source(s) to sufficiently support the drone flight while simultaneously minimizing its operational cost. The present work focuses on energy sources, but future extensions can allow automated selection of all parts required to assemble a drone, such that longest flight time is achieved at least cost. The proposed approach also quickly allows ascertaining if a desired flight time is achievable given a flight profile and a database of energy sources/parts.