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Development of Response Surface Model of Endurance Time and Structural Parameter Optimization for a Tailsitter UAV

This study designed a vertical take-off and landing tailsitter unmanned aerial vehicle (UAV) with a long endurance time. Nine parameters of the tailsitter UAV were investigated. Using a 2(k) full factorial test, 512 experiments on the nine parameters were conducted at their maximum and minimum value...

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Autores principales: Yao, Xiaomin, Liu, Wenshuai, Han, Wenting, Li, Guang, Ma, Qian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7147476/
https://www.ncbi.nlm.nih.gov/pubmed/32235793
http://dx.doi.org/10.3390/s20061766
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author Yao, Xiaomin
Liu, Wenshuai
Han, Wenting
Li, Guang
Ma, Qian
author_facet Yao, Xiaomin
Liu, Wenshuai
Han, Wenting
Li, Guang
Ma, Qian
author_sort Yao, Xiaomin
collection PubMed
description This study designed a vertical take-off and landing tailsitter unmanned aerial vehicle (UAV) with a long endurance time. Nine parameters of the tailsitter UAV were investigated. Using a 2(k) full factorial test, 512 experiments on the nine parameters were conducted at their maximum and minimum values. The time coefficient and air resistance were calculated using the computational fluid dynamics (CFD) method under different parameter combinations. The analysis of variance determined that the specific factors influencing the time coefficient and air resistance were the root chord, wingtip chord, wingspan, and sweep angle. By carrying out a central composite design (CCD) test, 25 sample points of the four particular factors were constructed. The time coefficient and air resistance were simulated under different structural parameter combinations using the CFD method. CFD simulation was verified by carrying out a wind tunnel test, and the results revealed that the aerodynamic coefficient error was less than 5%, while the air resistance error was less than 6%. The response surface methodology (RSM) for the time coefficient and air resistance was established using a genetic aggregation method. A multi-objective genetic algorithm (MOGA) was used to optimize the parameters with regard to the maximum time coefficient and minimum air resistance. The optimal structural parameters were wing root chord length at 315 mm, wingtip chord length at 182 mm, wingspan length at 1198 mm, and sweep angle at 16°. Compared with the original layout and size, the time coefficient of the new design of the tailsitter UAV improved by 19.5%, while the air resistance reduced by 34.78%. The results obtained by this study are significant for the design of tailsitter UAVs.
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spelling pubmed-71474762020-04-20 Development of Response Surface Model of Endurance Time and Structural Parameter Optimization for a Tailsitter UAV Yao, Xiaomin Liu, Wenshuai Han, Wenting Li, Guang Ma, Qian Sensors (Basel) Article This study designed a vertical take-off and landing tailsitter unmanned aerial vehicle (UAV) with a long endurance time. Nine parameters of the tailsitter UAV were investigated. Using a 2(k) full factorial test, 512 experiments on the nine parameters were conducted at their maximum and minimum values. The time coefficient and air resistance were calculated using the computational fluid dynamics (CFD) method under different parameter combinations. The analysis of variance determined that the specific factors influencing the time coefficient and air resistance were the root chord, wingtip chord, wingspan, and sweep angle. By carrying out a central composite design (CCD) test, 25 sample points of the four particular factors were constructed. The time coefficient and air resistance were simulated under different structural parameter combinations using the CFD method. CFD simulation was verified by carrying out a wind tunnel test, and the results revealed that the aerodynamic coefficient error was less than 5%, while the air resistance error was less than 6%. The response surface methodology (RSM) for the time coefficient and air resistance was established using a genetic aggregation method. A multi-objective genetic algorithm (MOGA) was used to optimize the parameters with regard to the maximum time coefficient and minimum air resistance. The optimal structural parameters were wing root chord length at 315 mm, wingtip chord length at 182 mm, wingspan length at 1198 mm, and sweep angle at 16°. Compared with the original layout and size, the time coefficient of the new design of the tailsitter UAV improved by 19.5%, while the air resistance reduced by 34.78%. The results obtained by this study are significant for the design of tailsitter UAVs. MDPI 2020-03-22 /pmc/articles/PMC7147476/ /pubmed/32235793 http://dx.doi.org/10.3390/s20061766 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yao, Xiaomin
Liu, Wenshuai
Han, Wenting
Li, Guang
Ma, Qian
Development of Response Surface Model of Endurance Time and Structural Parameter Optimization for a Tailsitter UAV
title Development of Response Surface Model of Endurance Time and Structural Parameter Optimization for a Tailsitter UAV
title_full Development of Response Surface Model of Endurance Time and Structural Parameter Optimization for a Tailsitter UAV
title_fullStr Development of Response Surface Model of Endurance Time and Structural Parameter Optimization for a Tailsitter UAV
title_full_unstemmed Development of Response Surface Model of Endurance Time and Structural Parameter Optimization for a Tailsitter UAV
title_short Development of Response Surface Model of Endurance Time and Structural Parameter Optimization for a Tailsitter UAV
title_sort development of response surface model of endurance time and structural parameter optimization for a tailsitter uav
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7147476/
https://www.ncbi.nlm.nih.gov/pubmed/32235793
http://dx.doi.org/10.3390/s20061766
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