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

Author

Di Piazza, M.C. ; Luna, M. ; Pucci, M. ; Vitale, G.

Author_Institution

Ist. di Studi sui Sist. Intell. per l´Autom. (ISSIA), Palermo, Italy

fYear

2013

fDate

10-13 Nov. 2013

Firstpage

7267

Lastpage

7273

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.

Keywords

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; Batteries; Maximum power point trackers; Neural networks; Neurons; Steady-state; Training; Vehicles; Li-ion battery; MPPT; Neural Networks; PV Battery charger; Virtual pyranometer;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE

Conference_Location

Vienna

ISSN

1553-572X

Type

conf

DOI

10.1109/IECON.2013.6700341

Filename

6700341