東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back to Search results for [ null ]

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Combined Trajectory, Propulsion and Battery Mass Optimization for Solar-Regenerative High-Altitude Long-Endurance Aircraft.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Combined Trajectory, Propulsion and Battery Mass Optimization for Solar-Regenerative High-Altitude Long-Endurance Aircraft./
Author:	Gates, Nathaniel Spencer.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
Description:	128 p.
Notes:	Source: Masters Abstracts International, Volume: 83-01.
Contained By:	Masters Abstracts International83-01.
Subject:	Aerospace engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28538362
ISBN:	9798522939397

Combined Trajectory, Propulsion and Battery Mass Optimization for Solar-Regenerative High-Altitude Long-Endurance Aircraft.
Gates, Nathaniel Spencer.

Combined Trajectory, Propulsion and Battery Mass Optimization for Solar-Regenerative High-Altitude Long-Endurance Aircraft. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 128 p.

Source: Masters Abstracts International, Volume: 83-01.

Thesis (M.Sc.)--Brigham Young University, 2021.

This item must not be sold to any third party vendors.

This thesis presents the work of two significant projects. In the first project, a suite of benchmark problems for grid energy management are presented which demonstrate several issues characteristic to the dynamic optimization of these systems. These benchmark problems include load following, cogeneration, tri-generation, and energy storage, and each one assumes perfect foresight of the entire time horizon. The Gekko Python package for dynamic optimization is introduced and two different solution methods are discussed and applied to solving these benchmarks. The simultaneous solve mode out-performs the sequential solve mode in each benchmark problem across a wide range of time horizons with increasing resolution, demonstrating the ability of the simultaneous mode to handle many degrees of freedom across a range of problems of increasing difficulty. In the second project, combined optimization of propulsion system design, flight trajectory planning and battery mass optimization is applied to solar-regenerative high-altitude long-endurance (SR-HALE) aircraft through a sequential iterative approach. This combined optimization approach yields an increase of 20.2% in the end-of-day energy available on the winter solstice at 35°N latitude, resulting in an increase in flight time of 2.36 hours. The optimized flight path is obtained by using nonlinear model predictive control to solve flight and energy system dynamics over a 24 hour period with a 15 second time resolution. The optimization objective is to maximize the total energy in the system while flying a station-keeping mission, staying within a 3 km radius and above 60,000 ft. The propulsion system design optimization minimizes the total energy required to fly the optimal path. It uses a combination of blade element momentum theory, blade composite structures, empirical motor and motor controller mass data, as well as a first order motor performance model. The battery optimization seeks to optimally size the battery for a circular orbit. Fixed point iteration between these optimization frameworks yields a flight path and propulsion system that slightly decreases solar capture, but significantly decreases power expended. Fully coupling the trajectory and design optimizations with this level of accuracy is infeasible with current computing resources. These efforts show the benefits of combining design and trajectory optimization to enable the feasibility of SR-HALE flight.

ISBN: 9798522939397Subjects--Topical Terms:

1002622
Aerospace engineering.
Subjects--Index Terms:

Dynamic optimization

Combined Trajectory, Propulsion and Battery Mass Optimization for Solar-Regenerative High-Altitude Long-Endurance Aircraft.
LDR:03795nmm a2200373 4500 001 2347616
005 20220823142313.5
008 241004s2021 ||||||||||||||||| ||eng d
020 $a 9798522939397
035 $a (MiAaPQ)AAI28538362
035 $a (MiAaPQ)BrighamYoung9989
035 $a AAI28538362
040 $a MiAaPQ $c MiAaPQ
100 1 $a Gates, Nathaniel Spencer. $3 3686889
245 1 0 $a Combined Trajectory, Propulsion and Battery Mass Optimization for Solar-Regenerative High-Altitude Long-Endurance Aircraft.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 128 p.
500 $a Source: Masters Abstracts International, Volume: 83-01.
500 $a Advisor: Hedengren, John D.;Ning, Andrew;Wheeler, Dean R.
502 $a Thesis (M.Sc.)--Brigham Young University, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a This thesis presents the work of two significant projects. In the first project, a suite of benchmark problems for grid energy management are presented which demonstrate several issues characteristic to the dynamic optimization of these systems. These benchmark problems include load following, cogeneration, tri-generation, and energy storage, and each one assumes perfect foresight of the entire time horizon. The Gekko Python package for dynamic optimization is introduced and two different solution methods are discussed and applied to solving these benchmarks. The simultaneous solve mode out-performs the sequential solve mode in each benchmark problem across a wide range of time horizons with increasing resolution, demonstrating the ability of the simultaneous mode to handle many degrees of freedom across a range of problems of increasing difficulty. In the second project, combined optimization of propulsion system design, flight trajectory planning and battery mass optimization is applied to solar-regenerative high-altitude long-endurance (SR-HALE) aircraft through a sequential iterative approach. This combined optimization approach yields an increase of 20.2% in the end-of-day energy available on the winter solstice at 35°N latitude, resulting in an increase in flight time of 2.36 hours. The optimized flight path is obtained by using nonlinear model predictive control to solve flight and energy system dynamics over a 24 hour period with a 15 second time resolution. The optimization objective is to maximize the total energy in the system while flying a station-keeping mission, staying within a 3 km radius and above 60,000 ft. The propulsion system design optimization minimizes the total energy required to fly the optimal path. It uses a combination of blade element momentum theory, blade composite structures, empirical motor and motor controller mass data, as well as a first order motor performance model. The battery optimization seeks to optimally size the battery for a circular orbit. Fixed point iteration between these optimization frameworks yields a flight path and propulsion system that slightly decreases solar capture, but significantly decreases power expended. Fully coupling the trajectory and design optimizations with this level of accuracy is infeasible with current computing resources. These efforts show the benefits of combining design and trajectory optimization to enable the feasibility of SR-HALE flight.
590 $a School code: 0022.
650 4 $a Aerospace engineering. $3 1002622
650 4 $a Chemical engineering. $3 560457
650 4 $a Aircraft. $3 832698
650 4 $a Design optimization. $3 3681984
650 4 $a Velocity. $3 3560495
650 4 $a Electricity. $3 524507
650 4 $a Systems design. $3 3433840
650 4 $a Altitude. $3 746362
650 4 $a Variables. $3 3548259
650 4 $a Environmental impact. $3 3564810
650 4 $a Energy storage. $3 652130
650 4 $a Literature reviews. $3 3559998
650 4 $a Research & development--R&D. $3 3554335
650 4 $a Satellites. $3 924316
650 4 $a Emission standards. $3 3681915
650 4 $a Efficiency. $3 753744
653 $a Dynamic optimization
653 $a Multidisciplinary design optimization
653 $a Nonlinear model predictive control
653 $a Solar-regenerative high-altitude long-endurance aircraft
653 $a Unmanned aircraft systems
690 $a 0542
690 $a 0538
710 2 $a Brigham Young University. $3 1017451
773 0 $t Masters Abstracts International $g 83-01.
790 $a 0022
791 $a M.Sc.
792 $a 2021
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28538362