Reprint

Performance of Induction Machines

Edited by
July 2022
222 pages
  • ISBN978-3-0365-4785-5 (Hardback)
  • ISBN978-3-0365-4786-2 (PDF)

This book is a reprint of the Special Issue Performance of Induction Machines that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary

Induction machines are one of the most important technical applications for both the industrial world and private use. Since their invention (achievements of Galileo Ferraris, Nikola Tesla, and Michal Doliwo-Dobrowolski), they have been widely used in different electrical drives and as generators, thanks to their features such as reliability, durability, low price, high efficiency, and resistance to failure.

The methods for designing and using induction machines are similar to the methods used in other electric machines but have their own specificity. Many issues discussed here are based on the fundamental achievements of authors such as Nasar, Boldea, Yamamura, Tegopoulos, and Kriezis, who laid the foundations for the development of induction machines, which are still relevant today. The control algorithms are based on the achievements of Blaschke (field vector-oriented control) and Depenbrock or Takahashi (direct torque control), who created standards for the control of induction machines.

Today’s induction machines must meet very stringent requirements of reliability, high efficiency, and performance. Thanks to the application of highly efficient numerical algorithms, it is possible to design induction machines faster and at a lower cost. At the same time, progress in materials science and technology enables the development of new machine topologies. The main objective of this book is to contribute to the development of induction machines in all areas of their applications.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
LIM; slip frequency; linear induction motor; automatic train operation; rotor field-oriented angle error; indirect rotor field-oriented control; induction machine drives; model-based prediction; linear induction motors; finite element analysis; end effect; induction machines; electrical machines; thermal modeling; soft magnetic material; thermal conductivity; induction motor; solid rotor; effective parameters; finite element method; modelling of ring induction motors; Monte Carlo method; accurate modelling; induction machine; electromagnetic models; model selection; optimization; artificial neural networks; pattern search; evolutionary strategy; simulated annealing; induction machine; electromagnetic models; model selection; artificial neural network; fourth central moment; homogeneity analysis; induction motors; mechanical unbalance; one broken rotor bar; outer-race bearing fault; startup transient current; two broken rotor bars; three-phase induction motor; squirrel-cage rotor; energy efficiency; motor performance; n/a; dynamic model; induction motor; Matlab/Simulink; rotor winding; stator winding