Rapid Optimization of Double-Stators Switched Reluctance Motor with Equivalent Magnetic Circuit
Wu-Sung Yao
Additional contact information
Wu-Sung Yao: Department of Mechanical and Automation Engineering, National Kaohsiung First University of Science and Technology, No.1, University Rd., Yanchao Dist., Kaohsiung City 824, Taiwan
Energies, 2017, vol. 10, issue 10, 1-20
Abstract:
The primary objective for this paper is to create a methodology to rapidly optimize double-stators switched reluctance motor (DSSRM). An analytical model of equivalent magnetic circuits for the air gap reluctances of aligned and unaligned positions is proposed and the optimal operation point of the magneto-motive force (MMF) can be determined. Genetic algorithm (GA) integrated of the proposed equivalent magnetic circuit is developed for rapid optimization of DSSRM to reach the maximum of the ratio of torque to volume of DSSRM. Compared to conventional switched reluctance motor (SRM), an illustrated example of a 3-KW three-phase 12-Slot-8-Pole DSSRM is used to verify the efficiency of the proposed method. Simplified 2-D electromagnetic models are analyzed and simulated. Finally, results of the analytical calculations and the finite-element analysis (FEA) are validated by the proposed motor to show the accuracy of the designed strategy.
Keywords: rapidly optimize; double-stators switched reluctance motor; equivalent magnetic circuit; electromagnetics analysis; genetic algorithm; finite-element analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.mdpi.com/1996-1073/10/10/1603/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/10/1603/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:10:y:2017:i:10:p:1603-:d:114886
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().