Publication detail

Induction Machine Models and Equivalent Circuits Based on Hybrid Parameters of Two–Port Network

PAZDERA, I. PROCHÁZKA, P. HUTÁK, P. CIPÍN, R. CTIBOR, J. PATOČKA, M.

Original Title

Induction Machine Models and Equivalent Circuits Based on Hybrid Parameters of Two–Port Network

Type

conference paper

Language

English

Original Abstract

The paper is focused on development of induction machine (IM) model based on general two-port network theory, which is elemental theory well-known for all electrical engineers. Since the theory of IM is more specialized and known for engineers with some expertise in the field of electrical machines and drives. Application of the two-port network theory on IM can clarify the development process of IM model or eventually equivalent circuit for wide area of electrical engineers. The whole building process is also based on analogy with transformer and the theory of rotational coordinates is also employed. The models and equivalent circuits are then more suitable for understanding physical principles of IM from macroscopic point of view.

Keywords

Induction machine, Equivalent circuit, Two-port network, Hybrid parameters.

Authors

PAZDERA, I.; PROCHÁZKA, P.; HUTÁK, P.; CIPÍN, R.; CTIBOR, J.; PATOČKA, M.

Released

1. 1. 2018

Publisher

Springer International Publishing AG 2018

ISBN

978-3-319-65959-6

Book

Mechatronics 2017

ISBN

2194-5357

Periodical

Advances in Intelligent Systems and Computing

State

Swiss Confederation

Pages from

202

Pages to

210

Pages count

9

URL

https://link.springer.com/chapter/10.1007/978-3-319-65960-2_26

BibTex

@inproceedings{BUT141420,
  author="Ivo {Pazdera} and Petr {Procházka} and Petr {Huták} and Jiří {Ctibor} and Radoslav {Cipín} and Miroslav {Patočka}",
  title="Induction Machine Models and Equivalent Circuits Based on Hybrid Parameters of Two–Port Network",
  booktitle="Mechatronics 2017",
  year="2018",
  journal="Advances in Intelligent Systems and Computing",
  pages="202--210",
  publisher="Springer International Publishing AG 2018",
  doi="10.1007/978-3-319-65960-2\{_}26",
  isbn="978-3-319-65959-6",
  issn="2194-5357",
  url="https://link.springer.com/chapter/10.1007/978-3-319-65960-2_26"
}