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Comparative analysis between recursive least squares state space (RLSS) and nonlinear least squares (NLS) methods for parameter identification in buck converters applied to solar energy systems
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  • André Luiz Silva Crivellari,
  • André Salume Lima Ferreira Leão,
  • Bartolomeu F.dos Santos Junior,
  • Roberto F. Coelho,
  • Lenon Schmitz,
  • Denizar C. Martins,
  • Walbermark M.dos Santos
André Luiz Silva Crivellari
Universidade Federal do Espirito Santo

Corresponding Author:[email protected]

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André Salume Lima Ferreira Leão
Universidade Federal do Espirito Santo
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Bartolomeu F.dos Santos Junior
Universidade Federal do Piaui
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Roberto F. Coelho
Universidade Federal de Santa Catarina
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Lenon Schmitz
Universidade Federal de Santa Catarina
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Denizar C. Martins
Universidade Federal de Santa Catarina
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Walbermark M.dos Santos
Universidade Federal do Espirito Santo
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Abstract

The lifespan of a converter depends on component reliability. In non-redundant designs like buck converters, a single component failure can shut down the circuit. Capacitors are more prone to failure than inductors or semiconductors. Monitoring parameters such as equivalent series resistance, rather than manual data, better assesses a converter’s useful life. This article compares two parameter estimation methods: recursive state space and non-linear least squares, with R² values and residuals analysis ensuring reliable results that closely correlate with real converter values.
30 Sep 2024Submitted to International Journal of Circuit Theory and Applications
01 Oct 2024Submission Checks Completed
01 Oct 2024Assigned to Editor
01 Oct 2024Review(s) Completed, Editorial Evaluation Pending
04 Oct 2024Reviewer(s) Assigned