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Electrical Engineering
Erschienen in: Electrical Engineering 1/2021

08.08.2020 | Original Paper

Parameter identification based on linear model for buck converters

verfasst von: Lei Ren, Chunying Gong

Erschienen in: Electrical Engineering | Ausgabe 1/2021

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Abstract

Parameter identification is an effective method to monitor the health condition of multiple components in power electronic converters. The hybrid model-based method has been proved to be a universal approach. However, the existing hybrid model of buck converter ignores the winding resistance of filter inductor and non-ideal factors, which will cause errors in the identification results. To solve these problems, leg midpoint voltage is used to replace the input voltage and switching signals, and a linear model is proposed, which can be implemented by fewer sensors. In order to verify the superiority of the linear model, this paper proposes a simple and practical parameter identification method for passive components. Compared with the hybrid model-based method, the proposed method does not need a sensor to measure driving signals and can obtain higher accuracy under non-ideal situations. Simulation and experimental results prove the proposed method to be effective and accurate.
Vorheriger Artikel Extreme learning machine for real-time damping of LFO in power system networks
Nächster Artikel Active-switched boost quasi-Z-source inverter with few components

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Metadaten
Titel
Parameter identification based on linear model for buck converters
verfasst von
Lei Ren
Chunying Gong
Publikationsdatum
08.08.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Electrical Engineering / Ausgabe 1/2021
Print ISSN: 0948-7921
Elektronische ISSN: 1432-0487
DOI
https://doi.org/10.1007/s00202-020-01080-w

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