High performance parameter observation of induction motor with sensorless vector Control using extended Kalman filter

Md Samiul Haque Sunny; Manash Mandal; Eklas Hossain; Md Adbur Rafiq

doi:10.1109/EICT.2017.8275182

High performance parameter observation of induction motor with sensorless vector Control using extended Kalman filter

Md Samiul Haque Sunny, Manash Mandal, Eklas Hossain, Md Adbur Rafiq

Electrical Engineering Department

Khulna University of Engineering and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Speed sensor less vector control of induction motor drive faces two major problems: Speed estimation, and rotor flux observation. Because of the multiplication terms of state variables, the induction motor model is consisted of nonlinear state equations. To estimate the state variables of the motor model and gain the rotor flux and speed signals, a method is proposed in this paper using extended Kalman filter. Software programs are used to carry out extended Kalman filter (EKF) algorithm to estimate the rotor speed and fluxes. The obtained results prove that extended Kalman filter algorithm can estimate rotor speed and flux very accurately, and based on that, the speed sensor less drive system can have good static and dynamic performance.

Original language	English
Title of host publication	3rd International Conference on Electrical Information and Communication Technology, EICT 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-5
Number of pages	5
ISBN (Electronic)	9781538623053
DOIs	https://doi.org/10.1109/EICT.2017.8275182
State	Published - 2 Jul 2017
Event	3rd International Conference on Electrical Information and Communication Technology, EICT 2017 - Khulna, Bangladesh Duration: 7 Dec 2017 → 9 Dec 2017

Publication series

Name	3rd International Conference on Electrical Information and Communication Technology, EICT 2017
Volume	2018-January

Conference

Conference	3rd International Conference on Electrical Information and Communication Technology, EICT 2017
Country/Territory	Bangladesh
City	Khulna
Period	7/12/17 → 9/12/17

Keywords

Extended Kalman Filter
Flux observer
Induction Motor
Sensorless Vector Control
Speed Estimation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/EICT.2017.8275182

Cite this

Sunny, M. S. H., Mandal, M., Hossain, E., & Rafiq, M. A. (2017). High performance parameter observation of induction motor with sensorless vector Control using extended Kalman filter. In 3rd International Conference on Electrical Information and Communication Technology, EICT 2017 (pp. 1-5). (3rd International Conference on Electrical Information and Communication Technology, EICT 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EICT.2017.8275182

Sunny, Md Samiul Haque ; Mandal, Manash ; Hossain, Eklas et al. / High performance parameter observation of induction motor with sensorless vector Control using extended Kalman filter. 3rd International Conference on Electrical Information and Communication Technology, EICT 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-5 (3rd International Conference on Electrical Information and Communication Technology, EICT 2017).

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title = "High performance parameter observation of induction motor with sensorless vector Control using extended Kalman filter",

abstract = "Speed sensor less vector control of induction motor drive faces two major problems: Speed estimation, and rotor flux observation. Because of the multiplication terms of state variables, the induction motor model is consisted of nonlinear state equations. To estimate the state variables of the motor model and gain the rotor flux and speed signals, a method is proposed in this paper using extended Kalman filter. Software programs are used to carry out extended Kalman filter (EKF) algorithm to estimate the rotor speed and fluxes. The obtained results prove that extended Kalman filter algorithm can estimate rotor speed and flux very accurately, and based on that, the speed sensor less drive system can have good static and dynamic performance.",

keywords = "Extended Kalman Filter, Flux observer, Induction Motor, Sensorless Vector Control, Speed Estimation",

author = "Sunny, {Md Samiul Haque} and Manash Mandal and Eklas Hossain and Rafiq, {Md Adbur}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 3rd International Conference on Electrical Information and Communication Technology, EICT 2017 ; Conference date: 07-12-2017 Through 09-12-2017",

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Sunny, MSH, Mandal, M, Hossain, E & Rafiq, MA 2017, High performance parameter observation of induction motor with sensorless vector Control using extended Kalman filter. in 3rd International Conference on Electrical Information and Communication Technology, EICT 2017. 3rd International Conference on Electrical Information and Communication Technology, EICT 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-5, 3rd International Conference on Electrical Information and Communication Technology, EICT 2017, Khulna, Bangladesh, 7/12/17. https://doi.org/10.1109/EICT.2017.8275182

High performance parameter observation of induction motor with sensorless vector Control using extended Kalman filter. / Sunny, Md Samiul Haque; Mandal, Manash; Hossain, Eklas et al.
3rd International Conference on Electrical Information and Communication Technology, EICT 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-5 (3rd International Conference on Electrical Information and Communication Technology, EICT 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - High performance parameter observation of induction motor with sensorless vector Control using extended Kalman filter

AU - Sunny, Md Samiul Haque

AU - Mandal, Manash

AU - Hossain, Eklas

AU - Rafiq, Md Adbur

PY - 2017/7/2

Y1 - 2017/7/2

N2 - Speed sensor less vector control of induction motor drive faces two major problems: Speed estimation, and rotor flux observation. Because of the multiplication terms of state variables, the induction motor model is consisted of nonlinear state equations. To estimate the state variables of the motor model and gain the rotor flux and speed signals, a method is proposed in this paper using extended Kalman filter. Software programs are used to carry out extended Kalman filter (EKF) algorithm to estimate the rotor speed and fluxes. The obtained results prove that extended Kalman filter algorithm can estimate rotor speed and flux very accurately, and based on that, the speed sensor less drive system can have good static and dynamic performance.

AB - Speed sensor less vector control of induction motor drive faces two major problems: Speed estimation, and rotor flux observation. Because of the multiplication terms of state variables, the induction motor model is consisted of nonlinear state equations. To estimate the state variables of the motor model and gain the rotor flux and speed signals, a method is proposed in this paper using extended Kalman filter. Software programs are used to carry out extended Kalman filter (EKF) algorithm to estimate the rotor speed and fluxes. The obtained results prove that extended Kalman filter algorithm can estimate rotor speed and flux very accurately, and based on that, the speed sensor less drive system can have good static and dynamic performance.

KW - Extended Kalman Filter

KW - Flux observer

KW - Induction Motor

KW - Sensorless Vector Control

KW - Speed Estimation

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U2 - 10.1109/EICT.2017.8275182

DO - 10.1109/EICT.2017.8275182

M3 - Conference contribution

AN - SCOPUS:85050478262

T3 - 3rd International Conference on Electrical Information and Communication Technology, EICT 2017

SP - 1

EP - 5

BT - 3rd International Conference on Electrical Information and Communication Technology, EICT 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Electrical Information and Communication Technology, EICT 2017

Y2 - 7 December 2017 through 9 December 2017

ER -

Sunny MSH, Mandal M, Hossain E, Rafiq MA. High performance parameter observation of induction motor with sensorless vector Control using extended Kalman filter. In 3rd International Conference on Electrical Information and Communication Technology, EICT 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-5. (3rd International Conference on Electrical Information and Communication Technology, EICT 2017). doi: 10.1109/EICT.2017.8275182

High performance parameter observation of induction motor with sensorless vector Control using extended Kalman filter

Abstract

Publication series

Conference

Keywords

UN SDGs

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