dc.contributor.author | Eguren-Alustiza, Imanol | |
dc.contributor.author | Almandoz, Gaizka | |
dc.contributor.author | Egea, Aritz | |
dc.contributor.author | Madina, Patxi | |
dc.contributor.author | Escalada Aguado, Ana Julia | |
dc.date.accessioned | 2025-07-11T07:00:59Z | |
dc.date.available | 2025-07-11T07:00:59Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-1-83953-542-0 | en |
dc.identifier.other | https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=164912 | en |
dc.identifier.uri | https://hdl.handle.net/20.500.11984/13907 | |
dc.description.abstract | Linear 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.iso | eng | en |
dc.publisher | IEEE | en |
dc.rights | © 2020 | en |
dc.subject | Linear motor | en |
dc.subject | Switched-Flux | en |
dc.subject | Ripple | en |
dc.title | Thrust ripple optimisation method for linear switched-flux machines | en |
dcterms.accessRights | http://purl.org/coar/access_right/c_f1cf | en |
dcterms.source | International Conference on Power Electronics, Machines and Drives (PEMD) | en |
local.contributor.group | Accionamientos aplicados a la tracción y a la generación de energía eléctrica | es |
local.description.peerreviewed | true | en |
local.description.publicationfirstpage | 284 | en |
local.description.publicationlastpage | 289 | en |
local.identifier.doi | https://doi.org/10.1049/icp.2021.1152 | en |
local.embargo.enddate | 2140-12-31 | |
local.contributor.otherinstitution | Orona | es |
local.source.details | 10. Virtual, 15-17 Decembre 2020 | en |
oaire.format.mimetype | application/pdf | en |
oaire.file | $DSPACE\assetstore | en |
oaire.resourceType | http://purl.org/coar/resource_type/c_c94f | en |
oaire.version | http://purl.org/coar/version/c_ab4af688f83e57aa | en |
oaire.funderName | Gobierno Vasco | en |
oaire.funderIdentifier | https://ror.org/00pz2fp31 / http://data.crossref.org/fundingdata/funder/10.13039/501100003086 | en |
oaire.fundingStream | Programa predoctoral de formación del personal investigador no doctor 2018-2019 | en |
oaire.awardNumber | PRE_2018_1_0223 | en |
oaire.awardTitle | Sin información | en |
oaire.awardURI | Sin información | en |