Speed estimators using stator resistance adaption for sensorless induction motor drive

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86099927" target="_blank" >RIV/61989100:27240/16:86099927 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.15598/aeee.v14i3.1732" target="_blank" >http://dx.doi.org/10.15598/aeee.v14i3.1732</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.15598/aeee.v14i3.1732" target="_blank" >10.15598/aeee.v14i3.1732</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Speed estimators using stator resistance adaption for sensorless induction motor drive

Popis výsledku v původním jazyce

The paper describes speed estimators for a speed sensorless induction motor drive with the direct torque and flux control. However, the accuracy of the direct torque control depends on the correct information of the stator resistance, because its value varies with working conditions of the induction motor. Hence, a stator resistance adaptation is necessary. Two techniques were developed for solving this problem: model reference adaptive system based scheme and artificial neural network based scheme. At first, the sensorless control structures of the induction motor drive were implemented in Matlab-Simulink environment. Then, a comparison is done by evaluating the rotor speed difference. The simulation results confirm that speed estimators and adaptation techniques are simple to simulate and experiment. By comparison of both speed estimators and both adaptation techniques, the current based model reference adaptive system estimator with the artificial neural network based adaptation technique gives higher accuracy of the speed estimation.

Název v anglickém jazyce

Speed estimators using stator resistance adaption for sensorless induction motor drive

Popis výsledku anglicky

The paper describes speed estimators for a speed sensorless induction motor drive with the direct torque and flux control. However, the accuracy of the direct torque control depends on the correct information of the stator resistance, because its value varies with working conditions of the induction motor. Hence, a stator resistance adaptation is necessary. Two techniques were developed for solving this problem: model reference adaptive system based scheme and artificial neural network based scheme. At first, the sensorless control structures of the induction motor drive were implemented in Matlab-Simulink environment. Then, a comparison is done by evaluating the rotor speed difference. The simulation results confirm that speed estimators and adaptation techniques are simple to simulate and experiment. By comparison of both speed estimators and both adaptation techniques, the current based model reference adaptive system estimator with the artificial neural network based adaptation technique gives higher accuracy of the speed estimation.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

<a href="/cs/project/TE02000103" target="_blank" >TE02000103: Centrum inteligentních pohonů a pokročilého řízení strojů (CIDAM)</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Advances in Electrical and Electronic Engineering

ISSN

1336-1376

e-ISSN

—

Svazek periodika

14

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

7

Strana od-do

267-273

Kód UT WoS článku

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EID výsledku v databázi Scopus

2-s2.0-84988943370