Converter State-Space Model Estimation Using Dynamic Mode Decomposition

2022 IEEE 7th International Energy Conference (ENERGYCON 2022): Proceedings 2022
Pāvels Suskis, Jānis Zaķis, Aleksandrs Suzdaļenko, Huynh Van Khang, Anton Rassolkin, Toomas Vaimann, Raimondas Pomarnacki

Power electronic reliability is an important topic for modern industrial electronics. Each component of a power converter has its lifespan, which is affected by many factors like ambient temperature, humidity, load, and thermal cycles of the system. This study focuses on modeling and identifying a statespace model of a power converter under the degradation of passive components, namely the capacitor and inductor. A statespace model of a buck converter is estimated within the framework by dynamic mode decomposition. The algorithm requires 10 to 16 long historical samples of the state variables and the control signal. The numerical results prove that the suggested algorithm can track the system change in time.

Keywords
power converter, passive component degradation, system identification, reliability
DOI
10.1109/ENERGYCON53164.2022.9830201
Hyperlink
https://ieeexplore.ieee.org/document/9830201

Suskis, P., Zaķis, J., Suzdaļenko, A., Van Khang, H., Rassolkin, A., Vaimann, T., Pomarnacki, R. Converter State-Space Model Estimation Using Dynamic Mode Decomposition. In: 2022 IEEE 7th International Energy Conference (ENERGYCON 2022): Proceedings, Latvia, Riga, 9-12 May, 2022. Piscataway: IEEE, 2022, pp.1-5. ISBN 978-1-6654-7983-7. e-ISBN 978-1-6654-7982-0. Available from: doi:10.1109/ENERGYCON53164.2022.9830201

Publication language
English (en)