Capacitance estimation algorithm based on DC-link voltage ripples using hybrid machine learning techniques in power electronics converters

doi:10.1016/j.rineng.2025.106216

Capacitance estimation algorithm based on DC-link voltage ripples using hybrid machine learning techniques in power electronics converters

2025-07-09

0

OA

AI

A

AL-Wesabi Ibrahim *

A

Abdullrahman A. Al-Shamma’a

H

Hassan M. Hussein Farh

R

Riadh Al Dwood

G

Grant Charles Mwakipunda

许

许加柱 (Jiazhu Xu) *

DOI：10.1016/j.rineng.2025.106216

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Abstract

En 中文

• Analyses of research on monitoring the operational stability of capacitors. • Determined the most frequently utilized parameters for predicting capacitor failure. • The estimation of capacitance and series resistance provides precise results. • Percentage of errors of various existing methods against ANN-GB-LR have been compared • Hybrid ANN-GB-LR Data Driven Methods gives promising results in condition monitoring of capacitors.

Keywords:

DC-link capacitors

Condition monitoring

Machine learning techniques

Hybrid artificial neural networks- gradient boosting- linear regression model

Capacitance estimation algorithm based on DC-link voltage ripples using hybrid machine learning techniques in power electronics converters

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