Paper Info
Title
PV-based Li-ion battery charger with neural MPPT for autonomous sea vehicles
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.
Year
DOI
Venue
2013
10.1109/IECON.2013.6700341
Vienna
Keywords
Field
DocType
dc-dc power convertors,autonomous underwater vehicles,battery chargers,battery powered vehicles,marine power systems,maximum power point trackers,photovoltaic power systems,secondary cells,sunlight,auv,dc-dc boost converter,pv-based li-ion battery charger,actual pv panel current,actual pv panel voltage,energy exploitation optimisation,maximum power point tracking,neural mppt,neural gas network,photovoltaic battery charger,small size marine autonomous sea vehicle,solar irradiance estimation,li-ion battery,mppt,neural networks,pv battery charger,virtual pyranometer
Boost converter,Grid-connected photovoltaic power system,Battery charger,Voltage,Maximum power point tracking,Control engineering,Solar irradiance,Engineering,Electrical engineering,Photovoltaic system,Neural gas
Conference
ISSN
Citations 
PageRank 
1553-572X
2
0.40
References 
Authors
0
4
Name
Order
Citations
PageRank
Maria Carmela Di Piazza1397.44
Luna, M.2103.26
Marcello Pucci313416.40
Gianpaolo Vitale410612.95