Publication detail

Synchronous Reluctance Motor Parameter and State Estimation Using Extended Kalman Filter and Current Derivative Measurement

MYNÁŘ, Z. VÁCLAVEK, P. BLAHA, P.

Original Title

Synchronous Reluctance Motor Parameter and State Estimation Using Extended Kalman Filter and Current Derivative Measurement

Type

journal article in Web of Science

Language

English

Original Abstract

The synchronous reluctance motor is becoming a very attractive alternative to the AC induction machine. This is due to the lack of rare-earth metals in their construction and a higher efficiency, which was brought about by recent progress in rotor design. However, in order to achieve an efficient and low-cost operation of the synchronous reluctance motor drive, an adaptive sensorless algorithm should be utilized to cope with machine non-linearities. This paper describes an adaptive observer, which can provide an estimation of rotor position and speed, as well as core loss and inductance parameters. A modified PWM switching scheme and a current derivative measurement method are proposed, together with an extended Kalman Filter design. Experimental results are shown to demonstrate method performance and feasibility.

Keywords

current derivative, extended Kalman filter, EKF, online adaptive observer, PWM excitation, sensorless control, synchronous reluctance motor, SynRM

Authors

MYNÁŘ, Z.; VÁCLAVEK, P.; BLAHA, P.

Released

1. 3. 2021

Publisher

IEEE

ISBN

0278-0046

Periodical

IEEE Transactions on Industrial Electronics

Year of study

68

Number

3

State

United States of America

Pages from

1972

Pages to

1981

Pages count

9

URL

Full text in the Digital Library

BibTex

@article{BUT161674,
  author="Zbyněk {Mynář} and Pavel {Václavek} and Petr {Blaha}",
  title="Synchronous Reluctance Motor Parameter and State Estimation Using Extended Kalman Filter and Current Derivative Measurement",
  journal="IEEE Transactions on Industrial Electronics",
  year="2021",
  volume="68",
  number="3",
  pages="1972--1981",
  doi="10.1109/TIE.2020.2973897",
  issn="0278-0046",
  url="https://ieeexplore.ieee.org/document/9011744"
}