Development of a fuzzy logic-based solar charge controller for charging lead-acid batteries

Authors
Castillo Sequera, José LuisUniversity of Alcalá Author; Paredes Larroca, Fabricio; Saettone Olschewski, Erich; Quino Favero, Javier; Rosales Huamaní, Jimmy Aurelio
Identifiers
Permanent link (URI): http://hdl.handle.net/10017/42731
DOI: 10.1007/978-3-030-33614-1_12
ISSN: 2194-5357
Date
2019-10-24
Embargo end date
2020-10-24
Affiliation
Universidad de Alcalá. Departamento de Ciencias de la Computación
Bibliographic citation
Paredes Larroca, F., Settone Olschewski, E., Quino Favero, J., Rosales Huamani, J. & Castillo Sequera, J.L. 2020, “Development of a fuzzy logic-based solar charge controller for charging lead-acid batteries”, in Proceedings of CSEI 2019, Advances and Applications in Computer Science, Electronics and Industrial Engineering, part of the AISC, vol. 1078, pp. 168-183
Keywords
Fuzzy logic
Controller
Battery charger
Description / Notes
Este documento se considera que es una ponencia de congresos en lugar de un artículo.
International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2019), Oct. 28-31 2019, Ambato (Ecuador)
Document type
info:eu-repo/semantics/conferenceObject
Version
info:eu-repo/semantics/acceptedVersion
Publisher's version
https://doi.org/10.1007/978-3-030-33614-1_12
Rights
Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
© 2020 Springer
Access rights
info:eu-repo/semantics/openAccess
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Abstract
The design and implementation of a solar charge controller for lead-acid batteries is intended to supplement a component of the water purification module of the water treatment unit for natural disaster relief. This unit contains a solar panel system that supplies power to the module by charging batteries through a controller comprising an Atmega 328 processor. The solar panel feeds voltage to the batteries through fuzzy logic-based software, which allows up to 6 A DC to pass through the controller's power circuit. Consequently, the battery was charged in less time (an average of 7 h to reach maximum capacity), wherein battery lifespan is related to the charge wave frequency. Thus, our software may be adapted in different control algorithms without having to change hardware.
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