Investigating Empirical Mode Decomposition in the Parameter Estimation of a Three-Section Winding Model

Daniel Marc Banks, Johannes Cornelius Bekker () and Hendrik Johannes Vermeulen
Additional contact information
Daniel Marc Banks: Department of Electrical and Electronic Engineering, Stellenbosch University, Stellenbosch 7600, South Africa
Johannes Cornelius Bekker: Department of Electrical and Electronic Engineering, Stellenbosch University, Stellenbosch 7600, South Africa
Hendrik Johannes Vermeulen: Department of Electrical and Electronic Engineering, Stellenbosch University, Stellenbosch 7600, South Africa

Energies, 2023, vol. 16, issue 4, 1-16

Abstract: Parameter estimation represents an important aspect of modeling electromagnetic systems, and a wide range of parameter estimation strategies has been explored in literature. Most parameter estimation methodologies make use of either time-domain or frequency-domain responses as measured from the terminals of the device under test. Very limited research has, however, been conducted into exploring the use of modal decomposition strategies on the time-domain waveforms for parameter estimation applications. In this paper, the use of Empirical Mode Decomposition for estimating the parameters of a three-section lumped parameter transformer model is explored. A novel approach is proposed to define the optimization cost function in terms of the intrinsic modes of simulated time-domain waveforms. The results are compared with results obtained using classical time-domain and frequency-domain approaches. It is shown through an impulse response test that weighting the modes obtained from the Inferred Empirical Mode Decomposition approach presented in this work offers advantages in terms of accurately representing the target model transfer function dynamics and can assist in interpreting the various dynamic modes associated with the target model.

Keywords: winding model; parameter estimation; particle swarm; empirical mode decomposition (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/4/1668/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/4/1668/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:4:p:1668-:d:1060818

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().