Vertical reference flight trajectory optimization with the particle swarm optimisation

Alejandro Murrieta-Mendoza, Hugo Ruiz, Ruxandra Mihaela Botez

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)

Abstract

The consumption of fossil fuels in order to power flights leads to undesirable pollution particles to be released to the atmosphere. Fuel also represents an important expense for airlines. For these reasons, it is of interest to reduce fuel burn for a given flight. In this article, the altitudes followed by a commercial aircraft during the cruise phase of a flight, also called vertical reference trajectory, were optimized in terms of fuel burn. The airspace was modelled under the form of a unidirectional graph. Fuel burn was computed using a numerical performance model. The weather forecast was obtained from the model delivered by Environment Canada. The selection of waypoints where to execute the changes in altitudes that provided the most economical flight cost in terms of fuel burn was determined using the particle swarm optimisation (PSO) algorithm. The trajectories provided by the algorithm developed in this paper were compared against simple geodesic trajectories to validate its optimization potential, and against as flown trajectories. Results have showed that up to 6.5% of fuel burn can be saved comparing against simple trajectories, and up to 3.1% was optimized comparing against as flown trajectories.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference Modelling, Identification and Control, MIC 2017
PublisherActa Press
Pages138-146
Number of pages9
ISBN (Electronic)9780889869882
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event2017 IASTED International Conference on Modelling, Identification and Control, MIC 2017 - Innsbruck, Austria
Duration: 20 Feb 201721 Feb 2017

Publication series

NameProceedings of the IASTED International Conference on Modelling, Identification and Control
Volume848
ISSN (Print)1025-8973

Conference

Conference2017 IASTED International Conference on Modelling, Identification and Control, MIC 2017
Country/TerritoryAustria
CityInnsbruck
Period20/02/1721/02/17

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