Please use this identifier to cite or link to this item: http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/10915
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJayasinghe, A.E.-
dc.contributor.authorFernando, N.-
dc.contributor.authorKumarawadu, S.-
dc.contributor.authorWang, L.-
dc.contributor.authorKarunadasa, J.P.-
dc.date.accessioned2024-12-16T03:46:34Z-
dc.date.available2024-12-16T03:46:34Z-
dc.date.issued2024-
dc.identifier.urihttp://repo.lib.jfn.ac.lk/ujrr/handle/123456789/10915-
dc.description.abstractThis paper investigates Equivalent Circuit Model (ECM) based Impedance Spectroscopy to assess the state of Lithium-Ion Battery (LIB) Degradation. ECM parameter identi- fication under different ageing mechanisms has been considered. The proposed technique is investigated using reference Elec- trochemical Impedance Spectroscopy (EIS) data obtained via a simulated LIB electrochemical model in the Python PyBAMM package. A Genetic Algorithm (GA) based optimization strategy is used to identify the ECM parameters for different ageing mechanisms with calendar ageing. The results show that the ECM is capable of capturing the LIB dynamics over a wide frequency range in addition to identifying the ECM parameter variations for specific degradation mechanisms.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectLithium-ion batteryen_US
dc.subjectBattery Modellingen_US
dc.subjectEquivalent Circuit Modelen_US
dc.subjectElectrochemical Impedance Spectroscopyen_US
dc.titleAssessment of Lithium-Ion Battery Degradation and its impact on ECM using Simulated Impedance Spectroscopyen_US
dc.typeConference paperen_US
dc.identifier.doi10.1109/ECCEEurope62508.2024.10751891en_US
Appears in Collections:Engineering Technology



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.