Power Magnetic Devices. Scott D. Sudhoff

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Power Magnetic Devices - Scott D. Sudhoff

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intent to provide a cookbook of design information for all devices. Rather, it is intended a position to leave the reader well poised to start adapting the approach to specific devices of interest to their work—whether it be a transformer or a novel type of rotating machine.

      From a pedagogical point of view, the organization of the text is designed to involve the readers in the design process as rapidly as possible. While it might be more efficient to discuss all the relevant physical effects, and then to discuss the design, such an approach is not always satisfying in that it leaves the reader hungry for a meal a long time before dinner is served. For that reason, the first thirteen chapters of the text generally alternate between discussing a physical effect and considering a design problem in which that effect is considered.

      Chapter 1 introduces multi‐objective optimization using genetic algorithms. This chapter provides a sufficient background to conduct formal multi‐objective optimization‐based design. Next, Chapter 2 provides a background in the magnetic analysis that is used throughout the book. Formal design is introduced in Chapter 3, wherein a simple inductor design is considered, using the material from Chapters 1 and 2. In Chapter 4, force and torque production are considered – and in Chapter 5 this material is used in simple electromagnet design. Chapter 6 concerns magnetic core loss. In this second edition, this chapter has been greatly expanded to include characterization of magnetic materials, as well as to include more information on modeling of magnetic hysteresis. Chapter 7 uses the magnetic core loss models in the design of a single‐phase transformer. The alternating pattern of analysis and design continues, with Chapters 8 and 9 focusing on the rotating machinery.

      The amount of material is adequate for two courses. The author recommends that Chapter 1 through Chapter 6 be covered as a starting point. The remaining chapters could be covered at that discretion of the instructor or the reader.

      Chapters 8 and 9 are based on Chapters 2 and 15 of Analysis of Electric Machinery and Drive Systems, 3rd Edition, by Paul Krause, Oleg Wasynczuk, Scott Sudhoff, and Steve Pekarek. This work is also published by IEEE/Wiley.

      MATLAB source code to support this book is given in S. D. Sudhoff, “MATLAB codes for Power Magnetic Devices: A Multi‐Objective Design Approach, 2nd Edition” [Online]. Available: http://booksupport.wiley.com. This code includes the Genetic Optimization System Engineering Toolbox, a Magnetic Equivalent Circuit Toolbox, a Thermal Equivalent Circuit Toolbox, as well as all the design examples discussed in the book. This should greatly reduce the amount of work needed to either to teach from the book, or to use the principals taught in this text for the reader’s own purposes. Partially annotated slides and a solutions manual are also available.

      Throughout this work, scalar variables are normally in italic font (for example) while vectors and matrices are bold non‐italic (for example). Functions of all dimensionalities are denoted by non‐italic non‐bold font (for example). Brackets in equations are associated with iteration number in iterative methods.

      The author of this book is deeply indebted to many individuals. First, to my parents, who gave me the time, support, and indulgence for me to pursue my interests. While in high‐school, I was blessed with many excellent teachers. I am particularly indebted to Sister Thomasita Hayes. As an undergraduate, I was also fortunate to have some outstanding instructors – particularly Stanislaw Zak in control and optimization, Fred Mowle who taught me how to code, and Paul Krause, who taught me electric machinery. I spent the beginning part of my career at the University of Missouri – Rolla where I was fortunate to have a number of excellent mentors including Keith Stanek, Max Anderson, and especially Mariesa Crow and Jim Drewniak.

      I would thank many current and former students, post docs, and research scientists who directly or indirectly contributed to this book. These include Benjamin Loop, Chunki Kwon, Jim Cale, Aaron Cramer, Brandon Cassimere, Brant Cassimere, Chuck Sullivan, Ricky Chan, Shengyu Wang, Yonggon Lee, Cahya Harianto, Jacob Krizan, Grant Shane, Omar Laldin, Ahmed Taher, Jamal Alsawhali, Harish Suryanarayana, and Jonathan Crider. Jamal Alsawalhi, Grant Shane, Jonathan Crider, Ahmed Taher, Ruiyang Lin, David Loder, Andrew Kasha, Vinicius Cabral Do Nascimento, Akhil Prasad, and Harshita Singh contributed in performing many of the FEA and/or experimental results in the book. I would also especially thank Dionysios Aliprantis for sparking my interest in genetic algorithms.

      A variety of U.S. government agencies have contributed to research efforts which contributed to this book, including the Army, Navy, DOE, Sandia National Labs, NREL, ORNL, and NASA. The Office of Naval Research in particular has provided steady support for my entire career which directly and indirectly supported this work, and without which this work would not have been possible. The support of the Grainger Foundation has also been very important to the program at Purdue.

      I would thank my colleagues at Purdue. A key attribute of any institution is the people your work with. With this regard, my colleagues at Purdue, namely Oleg Wasynczuk, Steve Pekarek, and Dionysios Aliprantis, are a great group.

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