Computer Science and Engineering, Department of


Date of this Version

Spring 5-2014


A. Mittleider. Analysis, Optimization, and Implementation of a UAV-Based Wireless Power Transfer System. MS thesis, University of Nebraska-Lincoln, May 2014


A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Computer Science, Under the Supervision of Professors Carrick Detweiler and Sebastian Elbaum. Lincoln, Nebraska: May, 2014

Copyright (c) 2014 Andrew Mittleider


Wireless power transfer is rapidly advancing in its ability to efficiently transfer power to a variety of devices.

As the efficiency increases, more applications for these systems arise. Since magnetic resonant wireless power transfer can only transfer a small amount of power, most current applications only focus on powering low-powered devices.

Wireless Sensor Networks are composed of many low-powered nodes which currently require human interaction to remain powered. We propose recharging a low-powered Wireless Sensor Network (WSN) with a magnetic resonant wireless power transfer system attached to a quadrotor Unmanned Aerial Vehicle (UAV).

This thesis addresses three main challenges with this method of powering a WSN. First, quadrotor UAVs are small and have limited payload capacities. Since a larger power transfer system generally results in better power transfer range and efficiency, we optimize the parameters of a wireless power transfer system for the small UAV. We show that, compared to our previous work, the power transfer coils' quality factor can be nearly doubled while retaining the same mass. Second, the UAV needs very precise control to transfer power to a small WSN node. We use a the sensed magnetic field from the Wireless Power Transfer system coupled with a simulated optical flow system to show that we can localize to within 21 cm to transfer 3.38 W to the sensor node. Last, the UAV has significant power limits of its own. We show that by optimizing the speed of travel and optimizing the mass of the UAV's battery, we can increase the range of the UAV from 3 km in the worst case to 9.3km in the optimal case.

Adviser: Carrick Detweiler and Sebastian Elbaum

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