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Proceedings Paper

LiPo battery energy studies for improved flight performance of unmanned aerial systems
Author(s): K. Chang; P. Rammos; S. A. Wilkerson; M. Bundy; S. Andrew Gadsden
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Paper Abstract

Energy storage is one of the most important determinants of how long and far a small electric powered unmanned aerial system (UAS) can fly. For years, most hobby and experimentalists used heavy fuels to power small drone-like systems. Electric motors and battery storage prior to the turn of the century were either too heavy or too inefficient for flight times of any usable duration. However, with the availability of brushless electric motors and lithium-based batteries everything has changed. Systems like the Dragon Eye, Pointer, and Raven are in service performing reconnaissance, intelligence, surveillance, and target acquisition (RISTA) for more than an hour at a time. More recently, multi-rotor vehicles have expanded small UAS capabilities to include activities with hovering and persistent surveillance. Moreover, these systems coupled with the surge of small, low-cost electronics can perform autonomous and semi-autonomous missions not possible just ten years ago. This paper addresses flight time limitation issues by proposing an experimental method with procedures for system identification that may lead to modeling of energy storage in electric UAS’. Consequently, this will allow for energy storage to be used more effectively in planning autonomous missions. To achieve this, a set of baseline experiments were designed to measure the energy consumption of a mid-size UAS multi-rotor. Several different flight maneuvers were considered to include different lateral velocities, climbing, and hovering. Therefore, the goal of this paper is to create baseline flight data for each maneuver to be characterized with a certain rate of energy usage. Experimental results demonstrate the feasibility and robustness of the proposed approach. Future work will include the development of mission planning algorithms that provide realistic estimates of possible mission flight times and distances given specific mission parameters.

Paper Details

Date Published: 13 May 2016
PDF: 10 pages
Proc. SPIE 9837, Unmanned Systems Technology XVIII, 98370W (13 May 2016); doi: 10.1117/12.2223352
Show Author Affiliations
K. Chang, Univ. of Maryland (United States)
P. Rammos, Univ. of Maryland (United States)
S. A. Wilkerson, U.S. Army Research Lab. (United States)
M. Bundy, U.S. Army Research Lab. (United States)
S. Andrew Gadsden, Univ. of Maryland (United States)


Published in SPIE Proceedings Vol. 9837:
Unmanned Systems Technology XVIII
Robert E. Karlsen; Douglas W. Gage; Charles M. Shoemaker; Grant R. Gerhart, Editor(s)

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