Digital Twin for Degradation Parameters Identification of DC-DC Converters Based on Bayesian Optimization

Shaowei Chen, Shengyue Wang, Pengfei Wen, Shuai Zhao

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

19 Citationer (Scopus)

Abstract

Power electronic circuits have been widely used in various fields, and the requirements for their stability and reliability has increased. Therefore, a degradation parameters identification method of the DC-DC power converters is proposed. The main idea of this method is to use a digital twin to build a DC-DC converter. Under steady and transient operating conditions, the power electronic circuits are simulated to deduce the law of output voltage and inductance current variation of the boost and buck converter, and the operation state of the physical entity is estimated. Degradation characteristic parameters, such as capacitance, inductance, parasitic resistance, and MOSFET on-state resistance, are selected and identified based on the Bayesian optimization. The simulation results verify the validity of the method.

OriginalsprogEngelsk
Titel2021 IEEE International Conference on Prognostics and Health Management, ICPHM 2021
ForlagIEEE
Publikationsdato7 jun. 2021
ISBN (Elektronisk)9781665419703
DOI
StatusUdgivet - 7 jun. 2021
Begivenhed2021 IEEE International Conference on Prognostics and Health Management, ICPHM 2021 - Detroit, USA
Varighed: 7 jun. 20219 jun. 2021

Konference

Konference2021 IEEE International Conference on Prognostics and Health Management, ICPHM 2021
Land/OmrådeUSA
ByDetroit
Periode07/06/202109/06/2021

Bibliografisk note

Publisher Copyright:
© 2021 IEEE.

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