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dc.contributor.authorZhang, Z.
dc.contributor.authorNilssen, R.
dc.contributor.authorMuyeen, S.M.
dc.contributor.authorNysveen, A.
dc.contributor.authorAl-Durra, A.
dc.date.accessioned2017-01-30T12:09:47Z
dc.date.available2017-01-30T12:09:47Z
dc.date.created2016-10-05T19:30:23Z
dc.date.issued2017
dc.identifier.citationZhang, Z. and Nilssen, R. and Muyeen, S.M. and Nysveen, A. and Al-Durra, A. 2017. Design optimization of ironless multi-stage axial-flux permanent magnet generators for offshore wind turbines. Engineering Optimization. 49 (5): pp. 815-827.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/18747
dc.identifier.doi10.1080/0305215X.2016.1208191
dc.description.abstract

Direct-driven ironless-stator machines have been reported to have low requirements on the strength of the supporting structures. This feature is attractive for offshore wind turbines, where lightweight generators are preferred. However, to produce sufficient torque, ironless generators are normally designed with large diameters, which can be a challenge to the machine’s structural reliability. The ironless multi-stage axial-flux permanent magnet generator (MS-AFPMG) has the advantages of ironless machines but a relatively small diameter. The objective of this article is to present the design optimization and performance investigation of the ironless MS-AFPMG. An existing design strategy, which employs two- and three-dimensional static finite element analyses and genetic algorithm for machine optimization, is improved with the aim of reducing the calculation load and calculation time. This improved design strategy is used to investigate the optimal ironless MS-AFPMG. Some intrinsic features of this kind of machine are revealed.

dc.publisherTaylor and Francis
dc.titleDesign optimization of ironless multi-stage axial-flux permanent magnet generators for offshore wind turbines
dc.typeJournal Article
dcterms.source.startPage1
dcterms.source.endPage13
dcterms.source.issn0305-215X
dcterms.source.titleEngineering Optimization
curtin.note

This is an Author's Original Manuscript of an article published by Taylor & Francis in Engineering Optimization on 17/06/2016 available online at http://www.tandfonline.com/10.1080/0305215X.2016.1208191

curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusOpen access


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