UniSa - IRIS Institutional Research Information System

Parametric Identification of the Dynamic Photovoltaic Model by a Physics-Informed Neural Network

Parameter identification in photovoltaic modules is essential for control, monitoring and diagnostic purposes. This paper shows the preliminary results obtained in the identification of the parameters of the non-linear dynamic model of a photovoltaic module by using a physics informed neural network. The model includes the series and the shunt resistance and a voltage-dependent non-linear capacitor modeling the semiconductor's dynamic behavior. It is shown that, by integrating simulation data...

AN EXPERIMENTAL TEST BENCH FOR THE THERMAL CONDITIONING ANALYSIS OF ABSORPTION AND DESORPTION CYCLES OF HYDROGEN WITHIN METAL HYDRIDES (MH) STORAGE TANKS

Hydrogen storage is one of the key issues to its spread on a large scale; among the different methods, storing hydrogen in the form of metal hydrides is certainly a promising technology due to several aspects, including the lack of hydrogen compression. However, this process is not mature yet and further studies are needed to make this storage system competitive; in particular, due to thermal behavior of metal hydrides during the absorption/desorption phases, the heat management of the storag...

Modular DC/DC Boost Converter for Efficient and Ripple-Free Conversion in Fuel Cell-Based Powertrains

The need to reduce emissions in the transport sector is making fuel-cell electric vehicles an option of increasing interest. However, several problems are still associated with this type of vehicles, including high costs and reliability. This paper discusses the issues related to the effects of the current ripple on PEM-type fuel cells and how a simple converter control strategy can be adopted to mitigate it. The study considers an interleaved boost converter in relation to its modular archit...

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