Moving horizon parameter estimation of permanent magnet synchronous machines

Xinyue Li, Ralph Kennel

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

2 Zitate (Scopus)

Abstract

In this paper a general moving horizon estimation (MHE) scheme for online parameter estimation of permanent magnet synchronous machines (PMSMs) is investigated. The optimization problem is solved with the generalized Gauss-Newton method and the real-time iteration approach, which enables the real time implementation of the moving horizon estimation. Furthermore, the proposed estimator is compared with state-of-the-art observers, i.e. extended Kalman filter (EKF) and unscented Kalman filter (UKF), under two test cases. The proposed estimation scheme shows superior performance at the steady state and during the transient both in simulation as well as in experiment.

OriginalspracheEnglisch
Titel2019 21st European Conference on Power Electronics and Applications, EPE 2019 ECCE Europe
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9789075815313
DOIs
PublikationsstatusVeröffentlicht - Sept. 2019
Veranstaltung21st European Conference on Power Electronics and Applications, EPE 2019 ECCE Europe - Genova, Italien
Dauer: 3 Sept. 20195 Sept. 2019

Publikationsreihe

Name2019 21st European Conference on Power Electronics and Applications, EPE 2019 ECCE Europe

Konferenz

Konferenz21st European Conference on Power Electronics and Applications, EPE 2019 ECCE Europe
Land/GebietItalien
OrtGenova
Zeitraum3/09/195/09/19

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