Semi-analytical range and endurance computation of battery-powered multi-copter unmanned aerial systems under steady wind conditions-Reference-Cited by-同舟云学术

Semi-analytical range and endurance computation of battery-powered multi-copter unmanned aerial systems under steady wind conditions

Published:2019-04-16 Issue:14 Volume:233 Page:5282-5294
ISSN:0954-4100
Container-title:Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
language:en
Short-container-title:Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering

Author:

Godbole Ameya¹,Subbarao Kamesh¹^ORCID,Dogan Atilla¹,Huff Brian²

Affiliation:

1. Department of Mechanical and Aerospace Engineering, University of Texas at Arlington, USA

2. Department of Industrial and Manufacturing Systems Engineering, University of Texas at Arlington, USA

Abstract

The range and endurance of an unmanned aerial system operating nominally in an outdoor environment depends upon the available power and environmental factors like the magnitude and direction of the prevailing wind. This paper focuses on the development of semi-analytical approaches to computing the range and endurance of battery-powered multi-copter unmanned aerial system under varying wind conditions. The analytically derived range is verified against a comprehensive unmanned aerial system simulation which includes experimentally validated elements such as the propulsion system and electric power consumption modules. It is shown that the analytical approach yields the range maps in close agreement with the simulation results.

Funder

National Science Foundation

Publisher

SAGE Publications

Subject

Mechanical Engineering,Aerospace Engineering

Link

http://journals.sagepub.com/doi/pdf/10.1177/0954410019842714

Reference7 articles.

1. Range and Endurance Estimates for Battery-Powered Aircraft

2. Maximum Range for Battery-Powered Aircraft

3. Rotorcraft flight endurance estimation based on a new battery discharge model

4. Nonlinear Model Predictive Control for Unmanned Aerial Vehicles

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