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Language of Instruction
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English
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Level of Course Unit
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Doctorate's Degree
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Department / Program
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ELECTRICAL AND COMPUTER ENGINEERING
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Type of Program
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Formal Education
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Type of Course Unit
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Elective
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Course Delivery Method
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Face To Face
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Objectives of the Course
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1. To learn the fundemental flux linkage, multiple excitation, ampere-turns, permanent magnet concepts and their effects on machine design 2. To learn the operating principles, torque, loss and efficiency calculations, nonlinear analysis, performance analysis of VRMs and drives 3. To learn modelling, simulation, analysis and design of VRM and drives, 4. To learn how to review papers, analyze and interpret the concepts and content found in the papers
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Course Content
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Fundamentals of VRM Analysis. Practical VRM Configurations. Current Waveforms for Torque Production. VRM Drives. Nonlinear Analysis. Performance Analysis of VRMs and Drives by means of Software Simulations. Loss, Efficiency and Torque Calculations. Paper Reviews. Evaluation of Selected Studies by means of Software Simulations. Step Motor Operating Principles. Various Configurations of Step Motors. Step Motor Control Methods and Step Motor Drives.
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Course Methods and Techniques
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Lectures, Flipped Learning, Active Learning, Homework, Projects, Paper Critic, Discussion Sessions, Presentation
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Prerequisites and co-requisities
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None
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Course Coordinator
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None
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Name of Lecturers
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Prof.Dr. İRFAN ALAN https://avesis.agu.edu.tr/irfan.alan irfan.alan@agu.edu.tr
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Assistants
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Research Assist. Ebubekir Keskinkılıç https://avesis.agu.edu.tr/5417 ebubekir.keskinkilic@agu.edu.tr
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Work Placement(s)
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No
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Recommended or Required Reading
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Resources
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Course Notes
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Course Textbook: “Electrical Machinery”, Fitzgerald, 5th Edition, 1992, McGraw Hill Int. Lmtd .
Additional Materials: 1) “Theory and Application of Step Motors”, Kuo, B.C., West Publishing, St. Paul, MN, 1974. 2) ACSLX Software and Software User Manual 3) Other papers and publications about the subject
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Course Category
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Mathematics and Basic Sciences
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%25
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Engineering
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%25
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Engineering Design
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%25
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Science
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%25
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