Online Parameter Identification for Multiport Magnetic Networks Energy Routers

A bstract-Multiport magnetic network energy router (MMNER) is attractive for DC micro grids with the advantages of high-power density and electrical isolation. Parameter identification is essential for MMNER since the parameters may change with aging and thus deteriorates the output performances. This paper proposes a forgetting factor recursive least squares (FFRLS) method-based parameter identification. By constructing the model system equations with the introduction of forgetting factor and solving them using the recursive least squares method, the equivalent connection inductance parameter identification results are finally obtained. The proposed FFRLS method can effectively identify parameters of MMNER, and accordingly improve the reliability of power control for MMNER. Besides, the simulation results show that the error of identified parameters (average value) are all within 1%, proving the effectiveness of this method.

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Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/icpre62586.2024.10768295
Primary Topic
Wireless Power Transfer Systems
Type
article
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article

Online Parameter Identification for Multiport Magnetic Networks Energy Routers

Yongqing Lv, Fujin Deng, Sayed Abulanwar, Zhiyong Li
Wireless Power Transfer Systems
article

Online Parameter Identification for Multiport Magnetic Networks Energy Routers

Yongqing Lv, Fujin Deng, Sayed Abulanwar, Zhiyong Li
article en

Abstract

A bstract-Multiport magnetic network energy router (MMNER) is attractive for DC micro grids with the advantages of high-power density and electrical isolation. Parameter identification is essential for MMNER since the parameters may change with aging and thus deteriorates the output performances. This paper proposes a forgetting factor recursive least squares (FFRLS) method-based parameter identification. By constructing the model system equations with the introduction of forgetting factor and solving them using the recursive least squares method, the equivalent connection inductance parameter identification results are finally obtained. The proposed FFRLS method can effectively identify parameters of MMNER, and accordingly improve the reliability of power control for MMNER. Besides, the simulation results show that the error of identified parameters (average value) are all within 1%, proving the effectiveness of this method.

Mansoura University (EG), Southeast University (CN)
Affordable and clean energy
Openalex Percentile: Top 80%
Wireless Power Transfer Systems
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