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dc.contributor.authorEguren-Alustiza, Imanol
dc.contributor.authorAlmandoz, Gaizka
dc.contributor.authorEgea, Aritz
dc.contributor.authorMadina, Patxi
dc.contributor.authorEscalada Aguado, Ana Julia
dc.date.accessioned2025-07-11T07:00:59Z
dc.date.available2025-07-11T07:00:59Z
dc.date.issued2020
dc.identifier.isbn978-1-83953-542-0en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=164912en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/13907
dc.description.abstractLinear switched-flux machines are a very promising technology thanks to their high thrust density and permanent magnet immunity. However, they usually have to deal with a high detent force and a high thrust force ripple. The thrust force ripple has been reduced in the literature by placing additional permanent magnets in the ends of the machine. Nevertheless, this addition of magnets may bring an increased detent force ripple. In this paper, a new approach for the sizing of the end magnets is presented. The position and size of the magnets are optimised with a genetic algorithm. The results show that with this new approach, the thrust ripple of a basic switched-flux machine can be reduced in 64 %, while also lowering the peak to peak detent force in 65 % and the volume of the end magnets in 66 %.en
dc.language.isoengen
dc.publisherIEEEen
dc.rights© 2020en
dc.subjectLinear motoren
dc.subjectSwitched-Fluxen
dc.subjectRippleen
dc.titleThrust ripple optimisation method for linear switched-flux machinesen
dcterms.accessRightshttp://purl.org/coar/access_right/c_f1cfen
dcterms.sourceInternational Conference on Power Electronics, Machines and Drives (PEMD)en
local.contributor.groupAccionamientos aplicados a la tracción y a la generación de energía eléctricaes
local.description.peerreviewedtrueen
local.description.publicationfirstpage284en
local.description.publicationlastpage289en
local.identifier.doihttps://doi.org/10.1049/icp.2021.1152en
local.embargo.enddate2140-12-31
local.contributor.otherinstitutionOronaes
local.source.details10. Virtual, 15-17 Decembre 2020en
oaire.format.mimetypeapplication/pdfen
oaire.file$DSPACE\assetstoreen
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94fen
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaen
oaire.funderNameGobierno Vascoen
oaire.funderIdentifierhttps://ror.org/00pz2fp31 / http://data.crossref.org/fundingdata/funder/10.13039/501100003086en
oaire.fundingStreamPrograma predoctoral de formación del personal investigador no doctor 2018-2019en
oaire.awardNumberPRE_2018_1_0223en
oaire.awardTitleSin informaciónen
oaire.awardURISin informaciónen


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