id:"swepub:oai:DiVA.org:ltu-75673"
Search: id:"swepub:oai:DiVA.org:ltu-75673" > Intelligent data-dr...
- 1 of 1
- Previous record
- Next record
- To hitlist
Intelligent data-driven prognostic methodologies for the real-time remaining useful life until the end-of-discharge estimation of the Lithium-Polymer batteries of unmanned aerial vehicles with uncertainty quantification
-
- Eleftheroglou, Nick (author)
- Faculty of Aerospace Engineering, TU Delft, the Netherlands
-
- Mansouri, Sina Sharif (author)
- Luleå tekniska universitet,Signaler och system
-
- Loutas, Theodoros (author)
- Department of Mechanical Engineering & Aeronautics, University of Patras, Greece
- show more...
- show less...
- (creator_code:org_t)
- Elsevier, 2019
- 2019
- English.
- In: Applied Energy. - : Elsevier. - 0306-2619 .- 1872-9118. ; 254
- Journal article (peer-reviewed)
Abstract
Subject headings
Close
- In this paper, the discharge voltage is utilized as a critical indicator towards the probabilistic estimation of the Remaining Useful Life until the End-of-Discharge of the Lithium-Polymer batteries of unmanned aerial vehicles. Several discharge voltage histories obtained during actual flights constitute the in-house developed training dataset. Three data-driven prognostic methodologies are presented based on state-of-the-art as well as innovative mathematical models i.e. Gradient Boosted Trees, Bayesian Neural Networks and Non-Homogeneous Hidden Semi Markov Models. The training and testing process of all models is described in detail. Remaining Useful Life prognostics in unseen data are obtained from all three methodologies. Beyond the mean estimates, the uncertainty associated with the point predictions is quantified and upper/lower confidence bounds are also provided. The Remaining Useful Life prognostics during six random flights starting from fully charged batteries are presented, discussed and the pros and cons of each methodology are highlighted. Several special metrics are utilized to assess the performance of the prognostic algorithms and conclusions are drawn regarding their prognostic capabilities and potential.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Robotteknik och automation (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Robotics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Keyword
- Remaining useful life
- Data-driven prognostics
- UAVs
- Li-Po batteries
- End of discharge
- Machine learning
- Reglerteknik
- Control Engineering
Publication and Content Type
- ref (subject category)
- art (subject category)
Find in a library
- Applied Energy (Search for host publication in LIBRIS)
To the university's database
- 1 of 1
- Previous record
- Next record
- To hitlist
Find more in SwePub
- By the author/editor
- Eleftheroglou, N ...
- Mansouri, Sina S ...
- Loutas, Theodoro ...
- Karvelis, Petros
- Georgoulas, Geor ...
- Nikolakopoulos, ...
- show more...
- Zarouchas, Dimit ...
- show less...
- About the subject
-
- ENGINEERING AND TECHNOLOGY
- ENGINEERING AND ...
- and Electrical Engin ...
- and Robotics
-
- ENGINEERING AND TECHNOLOGY
- ENGINEERING AND ...
- and Electrical Engin ...
- and Control Engineer ...
- Articles in the publication
- Applied Energy
- By the university
- Luleå University of Technology
Search outside SwePub
- Extend your search to:
- Google Book Search
- Google Scholar
Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.
- Copyright © LIBRIS - National Library Systems
- LIBRIS.kb.se
