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Klim Dyachkov
Klim Dyachkov

Control Of Electric Machine Drive Systems [WORK]

Based on the author's vast industry experience and collaborative works with other industries, Control of Electric Machine Drive Systems is packed with tested, implemented, and verified ideas that engineers can apply to everyday problems in the field. Originally published in Korean as a textbook, this highly practical updated version features the latest information on the control of electric machines and apparatus, as well as a new chapter on sensorless control of AC machines, a topic not covered in any other publication.

Control of Electric Machine Drive Systems

The book begins by explaining the features of the electric drive system and trends of development in related technologies, as well as the basic structure and operation principles of the electric machine. It also addresses steady state characteristics and control of the machines and the transformation of physical variables of AC machines using reference frame theory in order to provide a proper foundation for the material.

The heart of the book reviews several control algorithms of electric machines and power converters, explaining active damping and how to regulate current, speed, and position in a feedback manner. Seung-Ki Sul introduces tricks to enhance the control performance of the electric machines, and the algorithm to detect the phase angle of an AC source and to control DC link voltages of power converters. Topics also covered are:

Every chapter features exercise problems drawn from actual industry experience. The book also includes more than 300 figures and offers access to an FTP site, which provides MATLAB programs for selected problems. The book's practicality and real-world relatability make it an invaluable resource for professionals and engineers involved in the research and development of electric machine drive business, industrial drive designers, and senior undergraduate and graduate students.

Outcome 1 (Students will demonstrate expertise in a subfield of study chosen from the fields of electrical engineering or computer engineering):1.Analyze open- and closed-loop DC, induction, and synchronous motor drive systems, including torque, current and speed control.2.Model and simulate the dynamic operation of ac and dc machines using the generalized theory of electric machines.

Outcome 2 (Students will demonstrate the ability to identify and formulate advanced problems and apply knowledge of mathematics and science to solve those problems):1.Model and simulate the dynamic operation of ANY type electric machine, including those yet to be proposed.2.Design torque and speed control methods for electric machines.

Outcome 3 (Students will demonstrate the ability to utilize current knowledge, technology, or techniques within their chosen subfield):1.Apply new concepts in the literature and apply them to the design and analysis of electric machine drives

Purdue researchers have also been highly involved in control development for permanent magnet synchronous machines. In [8], a feedback based approach to flux weakening is set forth which allows flux weakening to occur without knowledge of the machine model (flux-weakening is a technique used to increase the speed range). In [9] an approach is set forth to reduce sensor requirements, thereby reducing the cost of the drive system. In [10-13], the performance of permanent-magnet synchronous machines is set forth. Therein, the optimal current waveform in terms of loss and torque ripple is found, and a method to obtain this waveform is set forth. This control strategy addresses the problems of reducing loss and torque ripple (which causes acoustic noise). The control which obtains the desired waveform is generalized in [14]. This paper introduces the multiple reference frame synchronous estimator / regulator concept, a control which can exactly regulate a waveform with a prescribed harmonic content. This can be used to inject desired harmonic content (for example, to reduce cogging torque) or to make sure that irregularities in a machine (such as a slight imbalance) do not introduce objectionable harmonics. The application of these concepts to the switched reluctance machine is described in [15-16].

Purdue has had considerable efforts in power electronics based Marine and Aerospace Power Systems, and this interest has included the controls. In [30], a systematic means of semiautomatically designing system controls is set forth. Purdue has also been interested in exotic power systems. The control design of a 400 Hz/20 kHz aerospace power system is indicative of these efforts and is described in [31].

Recently, Purdue has been able to implement real-time Model Predictive Control (MPC) of dc-dc converters. In MPC, control is determined at each sampling, through the solution of an optimal control problem. The optimal control formulation for switching systems is presented in [32]. In [33]-[36], the optimization is implemented within a Model Predictive Control framework for control of switching in a dc-dc boost converter. The primary focus of this research is on the real-time implementation of the control method, wherein the control problem is solved online in less than one switch period. A benefit of MPC control is that it achieves fast dynamic response over a wide range of operating points, even for systems with dynamic loads.

The course starts with covering three phase circuits and power calculations in three-phase systems. Active and reactive power transfer in an electrical grid are analyzed. Concepts of electromagnetic energy conversion and transformers will be introduced. Different types of energy sources and their interconnection to the grid will be covered such as hydro energy, wind power, solar photovoltaics and energy storage. The course is concluded with an introduction to economics of power generation and an overview of elements of smart grids. Prerequisites: Ece 202 and Ece 310 or permission of instructor.

Advanced topics on the modeling and control of electrical machines. Topics covered include induction machine equations, dynamic analysis of induction machines in terms of dq-windings, vector control of induction motor drives, mathematical description of vector control, detuning effects in induction motor vector control, dynamic analysis of doubly-fed induction generators and their vector control, space-vector pulse-width modulated inverters, direct torque control and encoder-less operation of induction motors, vector control of permanent magnet synchronous-motor drives and switched-reluctance motor drives. Prerequisite(s): Ece 414 or equivalent or permission of instructor.

This course covers principles of electric power systems, three-phase transformers, transmission line parameters, admittance model, impedance model, network work calculations, power-flow solution, symmetrical faults, symmetrical components and sequence network, asymmetrical faults, elements of power system protection and power system stability. Prerequisites: Ece 202, Ece 310 and Ece 413 or permission of instructor.

The organization of the hardware components of computing systems. Logic design theory review. Comparative survey of instruction set architectures. Design, control, communication, and interconnection strategies for major components such as arithmetic-logic units, control units, CPUs, memories, and I/O systems. Prediction and measurement of performance. Introduction to VLSI, parallel processing, and other current architectural trends. Only one of Csi 504 and Ece 532 may be taken for credit. Prerequisites: Csi 404 or Ece 432 or equivalent.

This course is an introduction to the basics of models, analysis tools, and control for embedded systems operating in real time. Topics include models of computation, basic analysis, control, and systems simulation, interfacing with the physical world, mapping to embedded platforms and distributed embedded systems. This course has a lab component. Course fee applies. Consult the Schedule of Classes. Prerequisites: Ece 233 or Csi 404 and either Ece 371 or APhy 415.

An introduction to the analysis and design of linear control systems. Mathematical models, including state-space variable models. Continuous and sampled-data systems. Feedback control, and stability. Root locus and frequency response compensation methods. Uncertain models and robustness. Prerequisites: Ece 371 Signals and Systems or equivalent. 041b061a72


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