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Stefan cel Mare
University of Suceava
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ROMANIA

Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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 HIGHLY CITED PAPER 

Energy Efficient Control of High Speed IPMSM Drives - A Generalized PSO Approach

GECIC, M. See more information about GECIC, M. on SCOPUS See more information about GECIC, M. on IEEExplore See more information about GECIC, M. on Web of Science, KAPETINA, M. See more information about  KAPETINA, M. on SCOPUS See more information about  KAPETINA, M. on SCOPUS See more information about KAPETINA, M. on Web of Science, MARCETIC, D. See more information about MARCETIC, D. on SCOPUS See more information about MARCETIC, D. on SCOPUS See more information about MARCETIC, D. on Web of Science
 
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Download PDF pdficon (1,399 KB) | Citation | Downloads: 407 | Views: 3,886

Author keywords
energy efficiency, field oriented control, high speed, permanent magnet synchronous motor, particle swarm optimization

References keywords
control(15), optimization(13), swarm(11), drives(11), electronics(10), pmsm(9), permanent(9), magnet(9), machines(9), iemdc(8)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-02-28
Volume 16, Issue 1, Year 2016, On page(s): 27 - 34
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.01004
Web of Science Accession Number: 000376995400004
SCOPUS ID: 84960102896

Abstract
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In this paper, a generalized particle swarm optimization (GPSO) algorithm was applied to the problems of optimal control of high speed low cost interior permanent magnet motor (IPMSM) drives. In order to minimize the total controllable electrical losses and to increase the efficiency, the optimum current vector references are calculated offline based on GPSO for the wide speed range and for different load conditions. The voltage and current limits of the drive system and the variation of stator inductances are all included in the optimization method. The stored optimal current vector references are used during the real time control and the proposed algorithm is compared with the conventional high speed control algorithm, which is mostly voltage limit based. The computer simulations and experimental results on 1 kW low cost high speed IPMSM drive are discussed in details.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [Full Text] [Web of Science Times Cited 10] [SCOPUS Times Cited 14]


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[CrossRef] [SCOPUS Times Cited 83]


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[CrossRef] [Web of Science Times Cited 280] [SCOPUS Times Cited 373]


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[CrossRef] [SCOPUS Times Cited 7]


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[CrossRef] [SCOPUS Times Cited 4]


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[CrossRef] [SCOPUS Times Cited 30]


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[CrossRef] [Web of Science Times Cited 134] [SCOPUS Times Cited 160]


[14] I. Vlad, A. Campeanu, S. Enache, and G. Petropol, "Operation Characteristics Optimization of Low Power Three-Phase Asynchronous Motors," Advances in Electrical and Computer Engineering, vol. 14, no. 1, pp. 87-92, 2014.
[CrossRef] [Full Text] [Web of Science Times Cited 10] [SCOPUS Times Cited 13]


[15] M. Leuer, A. Ruting, and J. Bocker, "Efficiency-optimized Model Predictive Torque Control for IPMSM," in Energy Conference (ENERGYCON), 2014 IEEE International , vol., no., pp.9-13, 13-16 May 2014.
[CrossRef] [SCOPUS Times Cited 11]


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[CrossRef] [SCOPUS Times Cited 6]


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[CrossRef]


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[CrossRef] [SCOPUS Times Cited 9]


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[26] A. Ratnaweera, S. Halgamuge, and H. C. Watson, "Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients," IEEE Transactions on Evolutionary Computation, vol. 8, no. 3, pp. 240-255, Jun. 2004.
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[27] M. R. Rapaic, Z. Kanovic, Z. D. Jelicic, and D. Petrovacki, "Generalized PSO algorithm - an application to Lorenz system identification by means of neural-networks," in 9th Symposium on Neural Network Applications in Electrical Engineering, 2008. NEUREL 2008, pp. 31-35.
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References Weight

Web of Science® Citations for all references: 34,181 TCR
SCOPUS® Citations for all references: 4,332 TCR

Web of Science® Average Citations per reference: 1,068 ACR
SCOPUS® Average Citations per reference: 135 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-03-22 23:19 in 173 seconds.




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