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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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  2/2020 - 14

 HIGHLY CITED PAPER 

Design of an Adaptive Flux Observer for Sensorless Switched Reluctance Motors Using Lyapunov Theory

ABDELMAKSOUD, H. See more information about ABDELMAKSOUD, H. on SCOPUS See more information about ABDELMAKSOUD, H. on IEEExplore See more information about ABDELMAKSOUD, H. on Web of Science, ZAKY, M. See more information about ZAKY, M. on SCOPUS See more information about ZAKY, M. on SCOPUS See more information about ZAKY, M. on Web of Science
 
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Download PDF pdficon (1,686 KB) | Citation | Downloads: 728 | Views: 2,244

Author keywords
AC machines, Lyapunov methods, motor drives, observers, state estimation

References keywords
reluctance(27), switched(26), sensor(22), position(20), motor(15), control(15), electronics(13), applications(13), power(12), estimation(11)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2020-05-31
Volume 20, Issue 2, Year 2020, On page(s): 123 - 130
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.02014
Web of Science Accession Number: 000537943500014
SCOPUS ID: 85087447190

Abstract
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This paper proposes an adaptive flux observer for a sensorless switched reluctance motor. The observer adaptive gains are designed using the Lyapunov theory to guarantee both the accuracy and stability of the sensorless control of a switched reluctance motor. A nonlinear inductance model is developed based on a finite element analysis data and used in the estimation algorithms for rotor position and speed. The adaptive flux observer estimates the rotor position at low, medium, and high speeds. A low-frequency ramp method is proposed to excite the switched reluctance motor during standstill where the voltage and current signals are unobservable. The proposed hybrid method is characterized by simplicity, accuracy, ease of implementation, and low real-time computation burden. Therefore, the sensorless control technique depends only on active phase measurements without extra hardware and memory storage for real-time implementation. Complete sensorless control of a three-phase 6/4-pole switched reluctance motor drive system is carried out using Matlab/Simulink. Also, it is implemented experimentally in real-time using the digital signal processor-DS1102 control board. The simulation and experimental results of the proposed sensorless scheme demonstrate the accurate estimation of both the speed and rotor position during the transient and steady states.


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

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[CrossRef] [Web of Science Times Cited 57] [SCOPUS Times Cited 88]


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[CrossRef] [Web of Science Times Cited 32] [SCOPUS Times Cited 40]


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[CrossRef] [Web of Science Times Cited 44] [SCOPUS Times Cited 56]


[13] G. Pasquesoone, R. Mikail, I. Husain, "Position estimation at starting and lower speed in three-phase switched reluctance machines using pulse injection and two thresholds," IEEE Transactions on Industry Applications, vol. 47, no.4, pp. 1724-1731, 2011.
[CrossRef] [Web of Science Times Cited 91] [SCOPUS Times Cited 114]


[14] H. Cheng, H. Chen, S. Xu, S. Yang, "Four-quadrant sensorless control in switched reluctance machine drive using pulse injection based on special flux linkage curves," IET Electrical Power Applications, vol. 11, no. 9, pp. 1566-1574, 2017.
[CrossRef] [Web of Science Times Cited 19] [SCOPUS Times Cited 22]


[15] J. Cai, Z. Deng, "Initial rotor position estimation and sensorless control of SRM based on coordinate transformation," IEEE Transactions Instrumentation and Measurement, vol. 64, no. 4, pp. 1004-1018, 2015.
[CrossRef] [Web of Science Times Cited 66] [SCOPUS Times Cited 76]


[16] S. Paramasivam, S. Vijayan, M. Vasudevan, R. Arumugam, R. Krishnan, "Real-time verification of AI based rotor position estimation techniques for a 6/4 pole switched reluctance motor drive," IEEE Transactions on. Magnetics, vol. 43, no. 7, pp. 3209-3222, 2007.
[CrossRef] [Web of Science Times Cited 64] [SCOPUS Times Cited 93]


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[18] Y. Cai, Y. Wang, H. Xu, S. Sun, C. Wang, L. Sun, "Research on rotor position model for switched reluctance motor using neural network," IEEE/ASME Transactions of Mechatronics, vol. 23, no. 6, pp. 2762-2773, 2018.
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[19] N. Ertugrul, D. Cheok, "Indirect angle estimation in switched reluctance motor drives using fuzzy logic based motor model," IEEE Transactions Power Electronics, vol. 15, no. 6, pp. 1029-1044, 2000.
[CrossRef] [Web of Science Times Cited 39] [SCOPUS Times Cited 55]


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[CrossRef] [Web of Science Times Cited 116] [SCOPUS Times Cited 162]


[21] E. Ofori, T. Husain, Y. Sozer, I. Husain, "A pulse-injection-based sensorless position estimation method for a switched reluctance machine over a wide speed range," IEEE Transactions on Industry Applications, vol. 51, no. 5, pp. 3867-3876, 2015.

[22] N. Chen, G. Cao, S. Huang, J. Sun, "Sensorless control of planar switched reluctance motors based on voltage injection combined with core-loss calculation," IEEE Transactions on Industrial Electronics, Oct. 2019.
[CrossRef] [Web of Science Times Cited 10] [SCOPUS Times Cited 14]


[23] K. Hu, Y. Chen and C. Liaw, "A reversible position sensorless controlled switched-reluctance motor drive with adaptive and intuitive commutation tunings," IEEE Transactions on Power Electronics, vol. 30, no. 7, pp. 3781-3793, 2015.
[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 59]


[24] A. Khalil, I. Husain, S. Hossain, S. Gopalakrishnan, A. Omekanda, B. Lequesne, H. Klode, "A hybrid sensorless SRM drive with eight- and six-switch converter topologies," IEEE Transactions on Industry Applications, vol. 41, no. 6, pp. 1647-1655, 2005.
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References Weight

Web of Science® Citations for all references: 1,686 TCR
SCOPUS® Citations for all references: 2,227 TCR

Web of Science® Average Citations per reference: 50 ACR
SCOPUS® Average Citations per reference: 66 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 2024-04-12 20:03 in 225 seconds.




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