Levenberg-Marquardt Algorithm-Based Neural Network Smart Control Strategy for a Low-Input Current Ripple and High-Voltage Gain Power Converter in Fuel-Cells Energy Systems

Küçük Resim Yok

Tarih

2025

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Ieee-Inst Electrical Electronics Engineers Inc

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

A crucial aspect of DC-DC converters employed in renewable energy sources such as fuel cells is their ability to exhibit substantial increases in DC voltage and maintain an efficient structure while minimizing input current ripple. These factors play a pivotal role in enhancing the longevity of these energy sources and ensuring their compatibility with high-voltage AC and DC grids. This study introduces a high-gain DC-DC step-up converter that incorporates a continuous input current cell and a switched capacitor voltage-boosting output cell to address these requirements. The control process of this proposed converter is executed using an artificial neural network based on the Levenberg-Marquardt learning algorithm. The primary difference in this research lies in obtaining the artificial neural network-based controller directly from the circuit's characteristic equations, rather than generating it through another controller. A feedback control strategy has been formulated, where the artificial neural network consistently produces duty increment values based on the reference voltage. Additionally, the network's input includes not only the reference signal but also the circuit input voltage and output current value. As a result, the stability of the circuit's output voltage is maintained against variations in input voltage and load changes. A laboratory-designed workbench underwent testing, and the experimental results substantiated the theoretical inquiries and simulation outcomes.

Açıklama

Anahtar Kelimeler

Fuel cell, smart control, artificial neural network, artificial neural network, grid-connected power converter, grid-connected power converter, low- input current cell, low- input current cell, high-voltage gain cell, high-voltage gain cell

Kaynak

Ieee Access

WoS Q Değeri

Q2

Scopus Q Değeri

Q1

Cilt

13

Sayı

Künye