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@INPROCEEDINGS{Zimmer:1049195,
author = {Zimmer, Marcel and De Din, Edoardo and Carta, Daniele and
Benigni, Andrea},
title = {{P}ower {E}lectronics {P}arameter {E}stimation by
{P}hysics-{I}nformed {G}aussian {P}rocesses},
publisher = {IEEE},
reportid = {FZJ-2025-05277},
pages = {1-6},
year = {2025},
abstract = {Non-invasive parameter estimation of power electronics
enables condition and health monitoring, enhances control
strategies, and thus, guarantees reliable and stable
operation of power converters. In this work, we propose the
application of Physics-Informed Gaussian Processes (PIGP)
for parameter estimation of power electronic converters. We
provide a detailed model-building scheme allowing
non-invasive characterisation of power converters. In
particular, we show that the proposed approach can be
applied independently of the particular noise level without
the need for data pre-processing. Tested with a DC-DC buck
converter in a simulation scenario, we show that the
proposed approach is immune to measurement noise and can be
executed with low sampling rates. This allows fast, possibly
online, execution and thus tracking of converter parameter
changes due to thermal effects or aging during operation.},
month = {Oct},
date = {2025-10-14},
organization = {IECON 2025 – 51st Annual Conference
of the IEEE Industrial Electronics
Society, Madrid (Spain), 14 Oct 2025 -
17 Oct 2025},
cin = {ICE-1},
cid = {I:(DE-Juel1)ICE-1-20170217},
pnm = {1121 - Digitalization and Systems Technology for
Flexibility Solutions (POF4-112) / 1122 - Design, Operation
and Digitalization of the Future Energy Grids (POF4-112) /
1123 - Smart Areas and Research Platforms (POF4-112)},
pid = {G:(DE-HGF)POF4-1121 / G:(DE-HGF)POF4-1122 /
G:(DE-HGF)POF4-1123},
typ = {PUB:(DE-HGF)8},
doi = {10.1109/IECON58223.2025.11221137},
url = {https://juser.fz-juelich.de/record/1049195},
}