Enhanced Gain Quadratic–Cubic Network Based Boost Converter for Renewable Energy Applications

ABSTRACT High voltage gain DC–DC converters are essential for renewable energy sources such as photovoltaic (PV) and fuel cells, which generally produce low voltages and require efficient step‐up conversion for grid interfacing. However, conventional high‐gain converters typically suffer from the factors of extreme duty ratios, high switch voltage stress, no common ground, and pulsating input current. To overcome these limitations, an enhanced gain quadratic–cubic network based boost converter (EGQCNBC) is proposed. The cubic gain topology converter offers enhanced voltage gain and reduced switch voltage stress. In particular, the cubic gain topology employed in this converter helps to achieve higher voltage gain without extreme duty ratios, making it suitable for PV and fuel cell applications. In addition, the converter ensures a common ground and continuous input current by utilizing a reduced component count. Steady‐state analysis is performed for both ideal and non‐ideal cases, with the respective voltage gain equations derived and compared with the recently reported high‐gain DC–DC converters. Also, small‐signal modeling, loss analysis, and efficiency assessment are carried out. The simulation is carried out using PSIM and is validated through experimental investigation using a 200 W laboratory prototype. The experimental results show that it achieves a voltage gain of 7.92 at a 0.4263 duty ratio with an efficiency of 94%, and the dynamic behavior of the hardware confirms the successful operation of the EGQCNBC.

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Publication Details

Journal
International Journal of Circuit Theory and Applications
Published
2025-10-15
DOI
https://doi.org/10.1002/cta.70178
Citations
1
Primary Topic
Advanced DC-DC Converters
Type
article
Field-Weighted Citation Impact
0.73
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article

Enhanced Gain Quadratic–Cubic Network Based Boost Converter for Renewable Energy Applications

M. M. Rajan Singaravel, Kumaravel Sundaramoorthy, V. Srimaheswaran
1 citations
International Journal of Circuit Theory and Applications
Advanced DC-DC Converters
0.73
article

Enhanced Gain Quadratic–Cubic Network Based Boost Converter for Renewable Energy Applications

M. M. Rajan Singaravel, Kumaravel Sundaramoorthy, V. Srimaheswaran
article en
1 citations

Abstract

ABSTRACT High voltage gain DC–DC converters are essential for renewable energy sources such as photovoltaic (PV) and fuel cells, which generally produce low voltages and require efficient step‐up conversion for grid interfacing. However, conventional high‐gain converters typically suffer from the factors of extreme duty ratios, high switch voltage stress, no common ground, and pulsating input current. To overcome these limitations, an enhanced gain quadratic–cubic network based boost converter (EGQCNBC) is proposed. The cubic gain topology converter offers enhanced voltage gain and reduced switch voltage stress. In particular, the cubic gain topology employed in this converter helps to achieve higher voltage gain without extreme duty ratios, making it suitable for PV and fuel cell applications. In addition, the converter ensures a common ground and continuous input current by utilizing a reduced component count. Steady‐state analysis is performed for both ideal and non‐ideal cases, with the respective voltage gain equations derived and compared with the recently reported high‐gain DC–DC converters. Also, small‐signal modeling, loss analysis, and efficiency assessment are carried out. The simulation is carried out using PSIM and is validated through experimental investigation using a 200 W laboratory prototype. The experimental results show that it achieves a voltage gain of 7.92 at a 0.4263 duty ratio with an efficiency of 94%, and the dynamic behavior of the hardware confirms the successful operation of the EGQCNBC.

International Journal of Circuit Theory and Applications
National Institute of Technology Calicut (IN), ITPEnergised Group (India) (IN)
Openalex Percentile: Top 22%
Advanced DC-DC Converters
0.73
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