Delivery Drone Driving Cycle

Abstract

Large companies such as Amazon and Google are currently testing deliveries using unmanned drones, intending to use these drones on the market. Topics tackled in this field of research include object collision routing optimization, delivery routing optimization, battery management optimization, and the addition of solar panels on the drones. Little publicly available research has been found to have been conducted on developing the methods to optimize the powertrain of the drones to maximize their delivery radii through modifying their electric motor and propeller parameters. In working towards that goal, this paper puts forth a delivery drone driving cycle simulation written in MATLAB with which to monitor their performance and fine-tune their properties. The driving cycle has been written to accommodate unmanned drones that use any number of propellers and perform vertical take-off and landing maneuvers. This driving cycle algorithm iteratively runs through multiple driving profiles to find the one which produces the maximal delivery radius for the drone. A data processing tool for polynomial interpolation, which is also written in MATLAB, is developed to manipulate the electric motor and propeller data into usable states for the simulation. For the tested drone configurations, no discernible pattern was noticed in the ideal power throttle needed to reach cruise altitude most efficiently. During cruise, an ideal pitch between 27 to 47 degrees which allowed them to displace horizontally while spending the least amount of energy per meter was found for all configurations.