Robust multilevel optimization of PMSM using design for six sigma

Meng, X; Wang, S; Qiu, J; Zhang, Q; Zhu, JG; Guo, Y; Liu, D

Robust multilevel optimization of PMSM using design for six sigma

Meng, X Wang, S Qiu, J Zhang, Q Zhu, JG

Guo, Y

Liu, D

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Magnetics, 2011, 47 (10), pp. 3248 - 3251
Issue Date:: 2011-10-01

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Field	Value	Language
dc.contributor.author	Meng, X	en_US
dc.contributor.author	Wang, S	en_US
dc.contributor.author	Qiu, J	en_US
dc.contributor.author	Zhang, Q	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.date.issued	2011-10-01	en_US
dc.identifier.citation	IEEE Transactions on Magnetics, 2011, 47 (10), pp. 3248 - 3251	en_US
dc.identifier.issn	0018-9464	en_US
dc.identifier.uri	http://hdl.handle.net/10453/18362
dc.description.abstract	In this paper, a robust optimization method based on design for six sigma (DFSS) is combined to the optimization of a surface mounted permanent synchronous machine (PMSM) by using multilevel genetic algorithm (MLGA). First, MLGA and DFSS are introduced in the robust optimization. Second, by taking into account the tolerances of the motor products, important input parameters could be varied with six sigma distribution and Monte Carlo simulation (MCS) method is used to reduce the calculation cost. Third, to verify the new algorithm, the presented algorithm is applied to the optimization of a PMSM. The results compared with those of traditional GA and MLGA and the discussion of the robust optimization combined with MLGA are presented. © 2011 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Magnetics	en_US
dc.relation.isbasedon	10.1109/TMAG.2011.2157322	en_US
dc.subject.classification	Applied Physics	en_US
dc.title	Robust multilevel optimization of PMSM using design for six sigma	en_US
dc.type	Journal Article
utslib.citation.volume	10	en_US
utslib.citation.volume	47	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0903 Biomedical 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	47	en_US

Abstract:

In this paper, a robust optimization method based on design for six sigma (DFSS) is combined to the optimization of a surface mounted permanent synchronous machine (PMSM) by using multilevel genetic algorithm (MLGA). First, MLGA and DFSS are introduced in the robust optimization. Second, by taking into account the tolerances of the motor products, important input parameters could be varied with six sigma distribution and Monte Carlo simulation (MCS) method is used to reduce the calculation cost. Third, to verify the new algorithm, the presented algorithm is applied to the optimization of a PMSM. The results compared with those of traditional GA and MLGA and the discussion of the robust optimization combined with MLGA are presented. © 2011 IEEE.

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http://hdl.handle.net/10453/18362