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Fuzzy-Based Charging-Discharging Controller for Lithium-Ion Battery in Microgrid Applications

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dc.citedby17
dc.contributor.authorFaisal M.en_US
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorKer P.J.en_US
dc.contributor.authorHossain Lipu M.S.en_US
dc.contributor.authorUddin M.N.en_US
dc.contributor.authorid57215018777en_US
dc.contributor.authorid7103014445en_US
dc.contributor.authorid37461740800en_US
dc.contributor.authorid36518949700en_US
dc.contributor.authorid55663372800en_US
dc.date.accessioned2023-05-29T09:06:56Z
dc.date.available2023-05-29T09:06:56Z
dc.date.issued2021
dc.descriptionCharging time; Controllers; Lithium-ion batteries; Microgrids; Battery performance; Battery state of charge; Control techniques; Improved fuzzy models; Mathematical calculations; Overcharging protection; Real-time application; Sensing components; Battery management systemsen_US
dc.description.abstractThis article presents the fuzzy-based charging-discharging control technique of lithium-ion battery storage in microgrid application. Considering available power, load demand, and battery state-of-charge (SOC), the proposed fuzzy-based scheme enables the storage to charge or discharge within the safe operating region. Various controlling techniques have been implemented to evaluate and control the battery performance, which has the limitation of controlling overcharging or overdischarging, complexity in control, and longer charging time. Besides, a fuzzy controller is less complex and faster, as it obviates the extra sensing components, requires no additional deep discharging and overcharging protection, and easy to implement due to the absence of mathematical calculation. The numerical simulations with the load demand and the generations demonstrate the effectiveness of the proposed charging-discharging controller strategy. The efficacy of the proposed controller is tested under certain load variations for real-time application. The obtained experimental result shows that the developed model can control the battery charging-discharging efficiently. Moreover, it is also seen from the output that the battery SOC does not go beyond the limit of the respective safe battery operating region (20%-80%). Thus, the main contribution of this research is to develop an improved fuzzy model and, thus, implement the system for real-time application to control the charging-discharging of the battery. � 1972-2012 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9403934
dc.identifier.doi10.1109/TIA.2021.3072875
dc.identifier.epage4195
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85104270880
dc.identifier.spage4187
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85104270880&doi=10.1109%2fTIA.2021.3072875&partnerID=40&md5=4d4ac1851f1223fdadef7dfbbbb2a8ba
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26121
dc.identifier.volume57
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleIEEE Transactions on Industry Applications
dc.titleFuzzy-Based Charging-Discharging Controller for Lithium-Ion Battery in Microgrid Applicationsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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