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Aerotecnica Missili & Spazio

, Volume 97, Issue 2, pp 68–84 | Cite as

Multi-objective Optimization for the Design of an Unconventional Sun-Powered High-Altitude-Long-Endurance Unmanned Vehicle

  • F. Mastroddi
  • L. M. Travaglini
  • S. Gemma
Article

Abstract

The use of High Altitude and Long Endurance (HALE) Unmanned Aerial Vehicles (UAVs) is becoming increasingly significant in both military and civil missions as High-Altitude Pseudo-Satellite (HAPS). Since this class of aircraft is usually powered by solar cells, it typically features unconventional configurations to maximize sun exposed surfaces. In the present paper, a Multidisciplinary Design Optimization (MDO) and a Multi-Objective Optimization (MOO) environment have been developed to provide a computational design tool for modeling and designing these unconventional aircraft in order to achieve as independent objectives the maximization of solar power flux, the maximization of the lift-to-drag ratio, and the minimization of mass. To this purpose, a FEM models generator, capable of managing unconventional geometries, and a solar power estimator, are suitably developed to be integrated within a multi objective optimization loop. The simultaneous use of MDO/MOO approaches, and Design Of Experiment (DOE) creation and updating principles, enables to efficiently take into account the multiple and contrasting objectives/constraints arising from the different disciplines involved in the design problem. The study is carried out by using two different commercial codes for multi-objective optimization and for structural and aeroelastic analyses respectively. The use of advanced MDO/MOO approaches revealed to be effective for designing unconventional vehicles.

Acronyms and Symbols

DOE

Design Of Experiment

FEM

Finite Element Method

HALE

High Altitude Long Endurance

HAPS

High Altitude Pseudo Satellite

LCU

Left of the Closest to Utopia point

MDO

Multidisciplinary Design Optimization

MOGA

Multi-Objective Genetic Algorithm

MOO

Multi-Objective Optimization

RCU

Right of the Closest to Utopia point

RPAS

Remotely Piloted Aerial System

SOO

Single-Objective Optimization

UAV

Unmanned Aerial Vehicle

ϕ

Energy flow

E

Lift-to-Drag ratio

L

Lift

CL

Lift coefficient

D

Drag

CD

Drag coefficient

W

Mass Weight

e

Oswald efficiency number

v⃗sun

Sun rays energy vector

n⃗i

Normal to the i-th panel surface area

Si

i-th panel surface area

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Copyright information

© AIDAA Associazione Italiana di Aeronautica e Astronautica 2018

Authors and Affiliations

  • F. Mastroddi
    • 1
  • L. M. Travaglini
    • 1
  • S. Gemma
    • 2
  1. 1.Dipartimento di Ingegneria Meccanica e Aerospaziale“Sapienza” - Università di RomaItaly
  2. 2.Thales Italian SpaceItaly

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