Fuzzy logic-based maximum power point tracking solar battery charge controller with backup stand-by AC generator
This paper presents a Fuzzy-based Maximum Power Point Tracking Solar Battery Charge Controller with backup stand-by AC generator. This study is developed to provide a maximum power point tracking battery charge controller using fuzzy logic algorithm for isolated areas that uses solar panels and AC g...
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Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2019-10-01.
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LEADER | 02859 am a22003613u 4500 | ||
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001 | ijeecs16917_12989 | ||
042 | |a dc | ||
100 | 1 | 0 | |a Madrigal, Gilfred Allen |e author |
100 | 1 | 0 | |e contributor |
700 | 1 | 0 | |a Cuevas, Kristin Gail |e author |
700 | 1 | 0 | |a Hora, Vivien |e author |
700 | 1 | 0 | |a Jimenez, Kristine Mae |e author |
700 | 1 | 0 | |a Manato, John Niño |e author |
700 | 1 | 0 | |a Porlaje, Mary Joy |e author |
700 | 1 | 0 | |a Fortaleza, Benedicto |e author |
245 | 0 | 0 | |a Fuzzy logic-based maximum power point tracking solar battery charge controller with backup stand-by AC generator |
260 | |b Institute of Advanced Engineering and Science, |c 2019-10-01. | ||
500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/16917 | ||
520 | |a This paper presents a Fuzzy-based Maximum Power Point Tracking Solar Battery Charge Controller with backup stand-by AC generator. This study is developed to provide a maximum power point tracking battery charge controller using fuzzy logic algorithm for isolated areas that uses solar panels and AC generators. Fuzzy Logic Toolbox in MATLAB and Arduino IDE were used in implementing fuzzy logic algorithm. Fuzzy logic is a mathematical system where something can be represented in continuous values between 0 and 1. It basically represents systems based on human reasoning. The hardware comprises of four components - the switched mode power supply, the source switching circuit, buck-boost converter and the diversion load controller. The pre-testing conducted based on the methodology indicates that the proposed charge controller is efficient in maximizing the input power that enters the charge controller under different conditions. The current efficiency rate of the charge controller is 96.02%. The average battery charging time for a fully-discharged 12V Lead-Acid Battery using AC source, DC source and both AC and DC sources are 2 hours and 30 minutes, 8 hours and 15 minutes and 5 hours and 30 minutes, respectively, while discharging took 3 hours and 40 minutes with two 30-watt floodlight load. | ||
540 | |a Copyright (c) 2019 Institute of Advanced Engineering and Science | ||
540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
546 | |a eng | ||
690 | |a Power Electronics | ||
690 | |a Maximum Power Point Tracking (MPPT); Fuzzy Logic; Buck-Boost Converter; Charge Controller | ||
655 | 7 | |a info:eu-repo/semantics/article |2 local | |
655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
655 | 7 | |2 local | |
786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 16, No 1: October 2019; 136-146 | |
786 | 0 | |n 2502-4760 | |
786 | 0 | |n 2502-4752 | |
786 | 0 | |n 10.11591/ijeecs.v16.i1 | |
787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/16917/12989 | |
856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/16917/12989 |z Get fulltext |