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Non-Intrusive parameter identification of a three-phase rectifier based on an optimization approach

Authors :
Jordi-Roger Riba
Manuel Moreno-Eguilaz
Carlos Candelo-Zuluaga
Gabriel Rojas-Duenas
Universitat Politècnica de Catalunya. Doctorat en Enginyeria Elèctrica
Universitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica
Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
Universitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group
Source :
UPCommons. Portal del coneixement obert de la UPC, Universitat Politècnica de Catalunya (UPC), IECON
Publication Year :
2020
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2020.

Abstract

Six-pulse diode rectifiers are widely used in many power conversion systems. In this work a non-intrusive approach for parameter identification of such power device is presented and its accuracy and performance is evaluated from experimental data. This parameter identification approach is focused on generating accurate discrete simulation models of three-phase rectifiers, although it can also be applied for health condition monitoring and diagnosis purposes. The approach presented in this paper is based on applying the non-linear least squares (NLS) algorithm following an optimization strategy to identify the parameters of a white-box model of the analyzed power devices. This approach analyzes the currents and voltages measured at the input/output terminals, thus performing a non-invasive acquisition of such signals, which is compatible with sealed systems. The method proposed in this paper can also be applied to many other power devices needing accurate simulation models or applying health condition strategies, switched power supplies or power converters.

Details

Language :
English
Database :
OpenAIRE
Journal :
UPCommons. Portal del coneixement obert de la UPC, Universitat Politècnica de Catalunya (UPC), IECON
Accession number :
edsair.doi.dedup.....02bbb8cd558a02c13ef8de43a98a21c8
Full Text :
https://doi.org/10.1109/IECON43393.2020.9254824