Multilevel optimization for surface mounted PM machine incorporating with FEM

Wang, S; Meng, X; Guo, N; Li, H; Qiu, J; Zhu, JG; Guo, Y; Liu, D; Wang, Y; Xu, W

Multilevel optimization for surface mounted PM machine incorporating with FEM

Wang, S

Meng, X Guo, N Li, H Qiu, J Zhu, JG

Guo, Y

Liu, D

Wang, Y Xu, W

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Magnetics, 2009, 45 (10), pp. 4700 - 4703
Issue Date:: 2009-10-01

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Field	Value	Language
dc.contributor.author	Wang, S https://orcid.org/0000-0002-9081-0167	en_US
dc.contributor.author	Meng, X	en_US
dc.contributor.author	Guo, N	en_US
dc.contributor.author	Li, H	en_US
dc.contributor.author	Qiu, J	en_US
dc.contributor.author	Zhu, JG https://orcid.org/0000-0002-9763-4047	en_US
dc.contributor.author	Guo, Y https://orcid.org/0000-0001-6182-0684	en_US
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1581-5582	en_US
dc.contributor.author	Wang, Y	en_US
dc.contributor.author	Xu, W	en_US
dc.date.issued	2009-10-01	en_US
dc.identifier.citation	IEEE Transactions on Magnetics, 2009, 45 (10), pp. 4700 - 4703	en_US
dc.identifier.issn	0018-9464	en_US
dc.identifier.uri	http://hdl.handle.net/10453/8537
dc.description.abstract	In this paper, Multilevel Genetic Algorithm (MLGA) is presented to solve the optimization of surface mounted permanent magnet synchronous machine (SPMSM), which has features of mixed continuous and discrete design variables, multi-modal objective functions, etc. Firstly, the multilevel optimization problem is described by using the problem matrix. The values in the problem matrix are deduced by correlation analysis. Secondly, the architecture and implementation of MLGA are carried out. Thirdly, the new algorithm is applied to a bilevel optimization of SPMSM to verify this multilevel optimization. The results compared with those of traditional genetic algorithm (GA) and discussions of the multilevel optimization are presented. © 2009 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Magnetics	en_US
dc.relation.isbasedon	10.1109/TMAG.2009.2024875	en_US
dc.subject.classification	Applied Physics	en_US
dc.title	Multilevel optimization for surface mounted PM machine incorporating with FEM	en_US
dc.type	Journal Article
utslib.citation.volume	10	en_US
utslib.citation.volume	45	en_US
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	02 Physical Sciences	en_US
utslib.for	09 Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
pubs.organisational-group	/University of Technology Sydney/Strength - CCET - Centre for Clean Energy Technology
utslib.copyright.status	open_access
pubs.issue	10	en_US
pubs.publication-status	Published	en_US
pubs.volume	45	en_US

Abstract:

In this paper, Multilevel Genetic Algorithm (MLGA) is presented to solve the optimization of surface mounted permanent magnet synchronous machine (SPMSM), which has features of mixed continuous and discrete design variables, multi-modal objective functions, etc. Firstly, the multilevel optimization problem is described by using the problem matrix. The values in the problem matrix are deduced by correlation analysis. Secondly, the architecture and implementation of MLGA are carried out. Thirdly, the new algorithm is applied to a bilevel optimization of SPMSM to verify this multilevel optimization. The results compared with those of traditional genetic algorithm (GA) and discussions of the multilevel optimization are presented. © 2009 IEEE.

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http://hdl.handle.net/10453/8537