A New Method for Iron Loss Separation

Detalhes bibliográficos
Autor(a) principal: Mendes,Filomena B. R.
Data de Publicação: 2021
Outros Autores: Suárez,Fredy M. S., Batistela,Nelson J., Leite,Jean V., Sadowski,Nelson, Bastos,João P. A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Journal of Microwaves. Optoelectronics and Electromagnetic Applications
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742021000400763
Resumo: Abstract In this work we propose a new method to separate iron losses by removing low frequency tests and reducing the number of experiments. The article deals with methodologies that use numerical methods to find the mathematical model coefficients of magnetic loss separation in hysteresis loss (Wh), eddy current loss (Wed) and excess loss (Wex). Three methodologies are presented and depend on experimental tests such as (i) varying magnetic induction Bm and constant supply frequency (f) of 50 Hz, (ii) constant magnetic induction around 1 T and varying frequency. The first methodology is based on Newton’s method to solve the numerical system generated with experimental data from two laboratory experiments. These data were reported in past references. Another two methodologies are based on genetic algorithms (GA). One of them depends on experimental data from both experiments and the another depends on experimental data only from experiment (i). Results indicate that genetic algorithms method presents excellent solutions in comparison with other ones. The GA method with two tests allows a better representation of the experimental behavior of the sample with maximum errors varying from 1.10% to 0.20%. In GA method with one test, minimization varied from 6.924 × 10−05 to 3.186 × 10−05.
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spelling A New Method for Iron Loss SeparationGenetic algorithmsiron lossesNewton’s methodAbstract In this work we propose a new method to separate iron losses by removing low frequency tests and reducing the number of experiments. The article deals with methodologies that use numerical methods to find the mathematical model coefficients of magnetic loss separation in hysteresis loss (Wh), eddy current loss (Wed) and excess loss (Wex). Three methodologies are presented and depend on experimental tests such as (i) varying magnetic induction Bm and constant supply frequency (f) of 50 Hz, (ii) constant magnetic induction around 1 T and varying frequency. The first methodology is based on Newton’s method to solve the numerical system generated with experimental data from two laboratory experiments. These data were reported in past references. Another two methodologies are based on genetic algorithms (GA). One of them depends on experimental data from both experiments and the another depends on experimental data only from experiment (i). Results indicate that genetic algorithms method presents excellent solutions in comparison with other ones. The GA method with two tests allows a better representation of the experimental behavior of the sample with maximum errors varying from 1.10% to 0.20%. In GA method with one test, minimization varied from 6.924 × 10−05 to 3.186 × 10−05.Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo2021-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742021000400763Journal of Microwaves, Optoelectronics and Electromagnetic Applications v.20 n.4 2021reponame:Journal of Microwaves. Optoelectronics and Electromagnetic Applicationsinstname:Sociedade Brasileira de Microondas e Optoeletrônica (SBMO)instacron:SBMO10.1590/2179-10742021v20i4254770info:eu-repo/semantics/openAccessMendes,Filomena B. R.Suárez,Fredy M. S.Batistela,Nelson J.Leite,Jean V.Sadowski,NelsonBastos,João P. A.eng2021-11-11T00:00:00Zoai:scielo:S2179-10742021000400763Revistahttp://www.jmoe.org/index.php/jmoe/indexONGhttps://old.scielo.br/oai/scielo-oai.php||editor_jmoe@sbmo.org.br2179-10742179-1074opendoar:2021-11-11T00:00Journal of Microwaves. Optoelectronics and Electromagnetic Applications - Sociedade Brasileira de Microondas e Optoeletrônica (SBMO)false
dc.title.none.fl_str_mv A New Method for Iron Loss Separation
title A New Method for Iron Loss Separation
spellingShingle A New Method for Iron Loss Separation
Mendes,Filomena B. R.
Genetic algorithms
iron losses
Newton’s method
title_short A New Method for Iron Loss Separation
title_full A New Method for Iron Loss Separation
title_fullStr A New Method for Iron Loss Separation
title_full_unstemmed A New Method for Iron Loss Separation
title_sort A New Method for Iron Loss Separation
author Mendes,Filomena B. R.
author_facet Mendes,Filomena B. R.
Suárez,Fredy M. S.
Batistela,Nelson J.
Leite,Jean V.
Sadowski,Nelson
Bastos,João P. A.
author_role author
author2 Suárez,Fredy M. S.
Batistela,Nelson J.
Leite,Jean V.
Sadowski,Nelson
Bastos,João P. A.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Mendes,Filomena B. R.
Suárez,Fredy M. S.
Batistela,Nelson J.
Leite,Jean V.
Sadowski,Nelson
Bastos,João P. A.
dc.subject.por.fl_str_mv Genetic algorithms
iron losses
Newton’s method
topic Genetic algorithms
iron losses
Newton’s method
description Abstract In this work we propose a new method to separate iron losses by removing low frequency tests and reducing the number of experiments. The article deals with methodologies that use numerical methods to find the mathematical model coefficients of magnetic loss separation in hysteresis loss (Wh), eddy current loss (Wed) and excess loss (Wex). Three methodologies are presented and depend on experimental tests such as (i) varying magnetic induction Bm and constant supply frequency (f) of 50 Hz, (ii) constant magnetic induction around 1 T and varying frequency. The first methodology is based on Newton’s method to solve the numerical system generated with experimental data from two laboratory experiments. These data were reported in past references. Another two methodologies are based on genetic algorithms (GA). One of them depends on experimental data from both experiments and the another depends on experimental data only from experiment (i). Results indicate that genetic algorithms method presents excellent solutions in comparison with other ones. The GA method with two tests allows a better representation of the experimental behavior of the sample with maximum errors varying from 1.10% to 0.20%. In GA method with one test, minimization varied from 6.924 × 10−05 to 3.186 × 10−05.
publishDate 2021
dc.date.none.fl_str_mv 2021-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742021000400763
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2179-10742021v20i4254770
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dc.publisher.none.fl_str_mv Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo
publisher.none.fl_str_mv Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo
dc.source.none.fl_str_mv Journal of Microwaves, Optoelectronics and Electromagnetic Applications v.20 n.4 2021
reponame:Journal of Microwaves. Optoelectronics and Electromagnetic Applications
instname:Sociedade Brasileira de Microondas e Optoeletrônica (SBMO)
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