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Title: Performance enhancement of wound rotor induction motor by rotor capacitive reactance control using computational intelligence techniques
Researcher: Ranjith kumar K
Guide(s): Palaniswami S
Keywords: Electrical engineering
Induction Motors
Squirrel- Cage Induction Motor
Wound Rotor Induction Motors
Upload Date: 28-Feb-2014
University: Anna University
Completed Date: 01/11/2012
Abstract: Induction Motors (IM) are the most widely used electrical machine. newlineThey consume more than 60% of total electrical energy worldwide. Based on newlinethe rotor design and construction, induction motors are classified as Squirrel- newlineCage Induction Motor (SCIM) and Wound Rotor Induction Motors (WRIM). newlineWRIM has many promising features and advantages like high torque, starting newlinewith high inertia loads, adjustable speed drives and soft starts with reduction newlinein starting currents. This leads to the necessity of improving the performance newlinecharacteristics such as efficiency, power factor, speed-torque in a wide newlineoperating range and reducing harmonics. Hence the performance newlineenhancement is the major objective of this work. The conventional variable Rotor Resistance control reduces the newlinemachine efficiency due to high copper losses in the rotor. In recent years, the newlineresearch focus has been on the rotor impedance control. This research deals newlinewith varying the rotor impedance by controlling external rotor capacitance. newlineThis work introduces several novel rotor impedance control schemes to newlineovercome losses due to rotor resistance control. This work is an attempt to illustrate the utility and effectiveness of newlineComputational Intelligent Techniques in modeling, control and finding the newlineoptimal value of the rotor capacitance for efficient operation of the motor. The newlinepresent work will concentrate on the pioneering of i. Genetic Algorithm (GA) based Rotor Capacitive Reactance newlineControl (RCRC) newlineii. Fuzzy Logic Control (FLC) based RCRC newlineiii. Hardware implementation of RCRC newlineiv. Artificial Neural Network based RCRC. In GA based approach, rotor capacitive reactance is adjusted such newlinethat for any desired torque and slip values, the total copper loss is minimized. newlineIn the proposed method, GA is used as an optimization tool to find the newlineoptimum value of the rotor capacitive reactance. The simulation results newlinevalidate improvement in WRIM efficiency.
Pagination: xxii, 159p.
Appears in Departments:Faculty of Electrical and Electronics Engineering

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01_title.pdfAttached File26.31 kBAdobe PDFView/Open
02_certificate.pdf208.22 kBAdobe PDFView/Open
03_abstract.pdf11.29 kBAdobe PDFView/Open
04_acnkowledgements.pdf6.87 kBAdobe PDFView/Open
05_contents.pdf43.44 kBAdobe PDFView/Open
06_chapter1.pdf206.69 kBAdobe PDFView/Open
07_chapter2.pdf155.18 kBAdobe PDFView/Open
08_chapter3.pdf335.38 kBAdobe PDFView/Open
09_chapter4.pdf1.18 MBAdobe PDFView/Open
10_chapter5.pdf729.02 kBAdobe PDFView/Open
11_chapter6.pdf667.6 kBAdobe PDFView/Open
12_chapter7.pdf15.17 kBAdobe PDFView/Open
13_appendix.pdf5.32 kBAdobe PDFView/Open
14_references.pdf55.48 kBAdobe PDFView/Open
15_publications.pdf10.5 kBAdobe PDFView/Open
16_vitae.pdf6.4 kBAdobe PDFView/Open

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