Circuit Parameter Identification of Degrading DC-DC Converters Based on Physics-informed Neural Network

Shaowei Chen, Jinling Zhang, Shengyue Wang, Pengfei Wen, Shuai Zhao

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

4 Citationer (Scopus)

Abstract

Power Electronic Systems (PES) is widely used in energy sectors such as renewable energy and aerospace. It is very important to design a reliable PES health monitoring system. This paper provides a new condition monitoring method based on Physics-informed Neural Network (PINN). Although the actual PES has a complex topology and is in a dynamically changing operating environment, the operation process does not violate the circuit physical models. Considering the charge and discharge process in the DC-DC converter, the physical formula is derived through the state-space average method. Then the physical formula is added to the deep learning model of LSTM as prior knowledge, to estimate the degradation parameters of the DC-DC converter. The uncertainty method is used to determine the weighting coefficients for data fitting and physical information fitting tasks. The PINN method can improve the estimation accuracy and generalization ability of the model in the case of limited data, which is conducive to the realization of the condition monitoring of complex PES. It is significant to improve the reliability of new energy vehicles and military equipment.

OriginalsprogEngelsk
TitelProceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022
RedaktørerChuan Li, Gianluca Valentino, Ling Kang, Diego Cabrera, Dejan Gjorgjevikj
Antal sider9
ForlagIEEE Signal Processing Society
Publikationsdato2022
Sider260-268
ISBN (Elektronisk)9781665479547
DOI
StatusUdgivet - 2022
Begivenhed2022 Prognostics and Health Management Conference, PHM-London 2022 - London, Storbritannien
Varighed: 27 maj 202229 maj 2022

Konference

Konference2022 Prognostics and Health Management Conference, PHM-London 2022
Land/OmrådeStorbritannien
ByLondon
Periode27/05/202229/05/2022
Sponsoret al., femto-st - Sciences and Technologies, IEEE, Le Cnam, London South Bank University, Université Paris-Saclay
NavnProceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022

Bibliografisk note

Publisher Copyright:
© 2022 IEEE.

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