@inproceedings{441a552b4f2b480b85c4533bd21ff845,
title = "Fault Recovery Method for Power Electronic Converters Based on Accelerator-Embedded Digital Twin",
abstract = "This paper presents a digital twin (DT)-based fault recovery method for power electronic converter systems. The method employs a prediction accelerator with a DT model for each subsystem of the converter system and feeds back the predicted system state to the controller. The paper demonstrates that the method can recover from faults such as load and input voltage variations in realtime and can integrate with hardware in the loop for future applications and comparing with other advanced control methods. The paper also highlights the benefits of the method in terms of scalability, replaceability and modularity for power electronic systems.",
keywords = "advanced control, digital twin, faster-than-RT simulation, fault recovery, power converter",
author = "Jiaqin Sun and Giampaolo Buticchi and Jing Li and He Zhang and Sandro Guenter and Jiajun Yang",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023 ; Conference date: 16-10-2023 Through 19-10-2023",
year = "2023",
doi = "10.1109/IECON51785.2023.10312499",
language = "English",
series = "IECON Proceedings (Industrial Electronics Conference)",
publisher = "IEEE Computer Society",
booktitle = "IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society",
address = "United States",
}