Detail publikace

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

MYNÁŘ, Z. VÁCLAVEK, P. BLAHA, P.

Originální název

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

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

MYNÁŘ, Z.; VÁCLAVEK, P.; BLAHA, P.

Vydáno

1. 3. 2021

Nakladatel

IEEE

ISSN

0278-0046

Periodikum

IEEE Transactions on Industrial Electronics

Ročník

68

Číslo

3

Stát

Spojené státy americké

Strany od

1972

Strany do

1981

Strany počet

9

URL

Plný text v Digitální knihovně

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"
}