Publication:
Enhanced State of Charge Estimation for Lithiumion Batteries using Polynomial Voltage Approximation

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dc.citedby0
dc.contributor.authorKarna S.en_US
dc.contributor.authorSatpathy P.R.en_US
dc.contributor.authorBhowmik P.en_US
dc.contributor.authorid59527815400en_US
dc.contributor.authorid57195339278en_US
dc.contributor.authorid57196457126en_US
dc.date.accessioned2025-03-03T07:45:09Z
dc.date.available2025-03-03T07:45:09Z
dc.date.issued2024
dc.description.abstractThe escalating adoption of electric machinery as a replacement for the fossil fuel-powered counterparts has underscored the critical need for robust energy storage solutions, with lithium-ion (Li-ion) batteries emerging as a cornerstone technology, particularly in electric vehicles (EVs). However, the intrinsic vulnerability of Li-ion batteries to degradation, caused by cyclic charge-discharge operations, poses significant challenges to accurate state of charge (SOC) estimation and capacity assessment, thereby impeding optimal EV performance [12] [16]. This study presents a novel approach to address these challenges by elucidating a direct correlation between battery voltage and SOC. Through rigorous empirical experimentation and advanced mathematical modelling, a polynomial equation is derived to precisely quantify SOC dynamics in response to voltage fluctuations. This framework facilitates real-time capacity estimation, empowering proactive management of EV energy systems [18]. By integrating empirical data with sophisticated mathematical analysis, this research contributes to deeper understanding of Li-ion battery behavior, paving the way for enhanced energy storage management strategies. The findings hold promise for optimizing EV efficiency, reliability, and longevity in the evolving landscape of electric machinery. ? 2024 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ODICON62106.2024.10797595
dc.identifier.scopus2-s2.0-85216028808
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85216028808&doi=10.1109%2fODICON62106.2024.10797595&partnerID=40&md5=ddf4d5531b99f31a321de7d6ad71a69e
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36846
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle3rd Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology, ODICON 2024
dc.subjectBattery management systems
dc.subjectBattery storage
dc.subjectBenchmarking
dc.subjectPolynomial approximation
dc.subjectEnergy
dc.subjectIon batteries
dc.subjectLithium ions
dc.subjectMismatch
dc.subjectMultiple-peak
dc.subjectPartial shading
dc.subjectPhotovoltaics
dc.subjectRobust energy
dc.subjectState-of-charge estimation
dc.subjectStates of charges
dc.subjectState of charge
dc.titleEnhanced State of Charge Estimation for Lithiumion Batteries using Polynomial Voltage Approximationen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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