Details
Originalsprache | Englisch |
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Titel des Sammelwerks | 2016 18th European Conference on Power Electronics and Applications, EPE 2016 ECCE Europe |
Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
ISBN (elektronisch) | 9789075815245 |
Publikationsstatus | Veröffentlicht - 25 Okt. 2016 |
Veranstaltung | 18th European Conference on Power Electronics and Applications, EPE 2016 ECCE Europe - Karlsruhe, Deutschland Dauer: 5 Sept. 2016 → 9 Sept. 2016 |
Publikationsreihe
Name | 2016 18th European Conference on Power Electronics and Applications, EPE 2016 ECCE Europe |
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Abstract
This paper deals with the online parameter estimation of squirrel-cage induction machines using the Gradient Descent Method and coupled stator and rotor flux observers. Stator resistance, rotor resistance and mutual inductance can be estimated simultaneously in real time. For a non-ambiguous parameter tracking, an additional voltage is superimposed. The influence of inverter nonlinearity, current and speed measurement errors is investigated. The presented approach is applicable to a standard industrial drive, including current measurement and motor speed feedback. The concept is verified by experimental tests for open loop V/f control as well as for field-oriented control.
ASJC Scopus Sachgebiete
- Energie (insg.)
- Energieanlagenbau und Kraftwerkstechnik
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
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2016 18th European Conference on Power Electronics and Applications, EPE 2016 ECCE Europe. Institute of Electrical and Electronics Engineers Inc., 2016. 7695353 (2016 18th European Conference on Power Electronics and Applications, EPE 2016 ECCE Europe).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Extended observer-based simultaneous online parameter estimation of inverter-fed squirrel-cage induction machines considering the influence of current and speed measurement errors
AU - Koupeny, J.
AU - Lucke, S.
AU - Mertens, A.
PY - 2016/10/25
Y1 - 2016/10/25
N2 - This paper deals with the online parameter estimation of squirrel-cage induction machines using the Gradient Descent Method and coupled stator and rotor flux observers. Stator resistance, rotor resistance and mutual inductance can be estimated simultaneously in real time. For a non-ambiguous parameter tracking, an additional voltage is superimposed. The influence of inverter nonlinearity, current and speed measurement errors is investigated. The presented approach is applicable to a standard industrial drive, including current measurement and motor speed feedback. The concept is verified by experimental tests for open loop V/f control as well as for field-oriented control.
AB - This paper deals with the online parameter estimation of squirrel-cage induction machines using the Gradient Descent Method and coupled stator and rotor flux observers. Stator resistance, rotor resistance and mutual inductance can be estimated simultaneously in real time. For a non-ambiguous parameter tracking, an additional voltage is superimposed. The influence of inverter nonlinearity, current and speed measurement errors is investigated. The presented approach is applicable to a standard industrial drive, including current measurement and motor speed feedback. The concept is verified by experimental tests for open loop V/f control as well as for field-oriented control.
KW - Estimation technique
KW - Induction motor
KW - Intelligent drive
UR - http://www.scopus.com/inward/record.url?scp=84996790671&partnerID=8YFLogxK
U2 - 10.1109/EPE.2016.7695353
DO - 10.1109/EPE.2016.7695353
M3 - Conference contribution
AN - SCOPUS:84996790671
T3 - 2016 18th European Conference on Power Electronics and Applications, EPE 2016 ECCE Europe
BT - 2016 18th European Conference on Power Electronics and Applications, EPE 2016 ECCE Europe
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th European Conference on Power Electronics and Applications, EPE 2016 ECCE Europe
Y2 - 5 September 2016 through 9 September 2016
ER -