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PV-based Li-ion battery charger with neural MPPT for autonomous sea vehicles

Conference Paper
Publication Date:
2013
abstract:
In this paper a photovoltaic (PV) battery charger based on a DC-DC boost converter for a small size marine autonomous vehicle (AUV) is developed. The proposed solution employs a neural-based technique to estimate the solar irradiance on the basis of the actual PV panel voltage and current. This information is then used to perform an effective maximum power point tracking (MPPT) to optimise the energy exploitation of the solar panel. In particular the growing Neural Gas Network is used. The design and set up of the PV charger is presented together with experimental results assessing its performance.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
PV Battery charger; Li-ion battery; MPPT; Neural Networks; Virtual pyranometer
List of contributors:
Vitale, Gianpaolo; DI PIAZZA, MARIA CARMELA; Pucci, Marcello; Luna, Massimiliano
Authors of the University:
DI PIAZZA MARIA CARMELA
LUNA MASSIMILIANO
PUCCI MARCELLO
VITALE GIANPAOLO
Handle:
https://iris.cnr.it/handle/20.500.14243/252005
Book title:
Proceedings of the 39th Annual Conference of the IEEE Industrial Electronics Society - IECON 2013
Published in:
PROCEEDINGS OF THE ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY
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http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6700341
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