Forward-Flyback Resonant Topology with Edge AI for MPPT Control in Solar Power Generation

Distributed energy systems open up a vast field of research in power electronics. Local solar power generation requires DC-DC converters that adapt the energy generated by the panels to on-site distribution buses. In addition, the control of the power converter to obtain the maximum possible energy from the solar source is crucial for the correct deployment of these distributed grids. In this work, system-level solutions are proposed for this application as follows: On the one hand, the use of novel resonant forward-flyback converters allows for a higher energy density than that of a conventional flyback and more relaxed withstand voltages on the switching elements. On the other hand, the implementation of maximum power point tracking algorithms for solar energy using Edge AI enables the deployment of algorithms that maximize the energy obtained locally. These improvements are shown by means of a prototype demonstrator, using cutting-edge microcontrollers and the implementation of a DC-DC power converter based on the proposed topology.

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Publication Details

Journal
Journal of Low Power Electronics and Applications
Published
2026-04-12
DOI
https://doi.org/10.3390/jlpea16020013
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Forward-Flyback Resonant Topology with Edge AI for MPPT Control in Solar Power Generation

Juan Cruz-Cozar, Noel Rodríguez, Diego Pedro Morales, Javier Mendez et al.
Journal of Low Power Electronics and Applications
Photovoltaic System Optimization Techniques
article

Forward-Flyback Resonant Topology with Edge AI for MPPT Control in Solar Power Generation

Juan Cruz-Cozar, Noel Rodríguez, Diego Pedro Morales, Javier Mendez, Alberto Martín-Martín, Jorge Perez-Martinez, Miguel Martínez Molina
article en

Abstract

Distributed energy systems open up a vast field of research in power electronics. Local solar power generation requires DC-DC converters that adapt the energy generated by the panels to on-site distribution buses. In addition, the control of the power converter to obtain the maximum possible energy from the solar source is crucial for the correct deployment of these distributed grids. In this work, system-level solutions are proposed for this application as follows: On the one hand, the use of novel resonant forward-flyback converters allows for a higher energy density than that of a conventional flyback and more relaxed withstand voltages on the switching elements. On the other hand, the implementation of maximum power point tracking algorithms for solar energy using Edge AI enables the deployment of algorithms that maximize the energy obtained locally. These improvements are shown by means of a prototype demonstrator, using cutting-edge microcontrollers and the implementation of a DC-DC power converter based on the proposed topology.

Journal of Low Power Electronics and ApplicationsVol. 16(2)
Infineon Technologies (Germany) (DE), Universidad de Granada (ES), Leipzig University (DE)
Key Digital Technologies Joint Undertaking, Infineon Technologies
Affordable and clean energy
Openalex Percentile: Top 30%
Photovoltaic System Optimization Techniques
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