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dc.contributor.authorSingh, Pratik Kumar-
dc.contributor.authorKasi, Venkata Ramana-
dc.contributor.authorKobaku, Tarakanath-
dc.contributor.authorJeyasenthil, R.-
dc.contributor.authorAgarwal, Vivek-
dc.contributor.authorNarlapati, Chandrasekhar Azad-
dc.date.accessioned2025-12-10T10:14:06Z-
dc.date.available2025-12-10T10:14:06Z-
dc.date.issued2024-
dc.identifier.citation10.1109/PEDES61459.2024.10961182en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/3529-
dc.descriptionNITWen_US
dc.description.abstractThere is an increase in the demand for Li-ion batteries particularly in Electric Vehicles (EVs). Identifying the Li-ion battery parameters will help in estimating the state of charge (SOC) accurately. In this paper, Li-ion battery is represented with one RC equivalent circuit. The charging/discharging behaviour of the generic battery in MATLAB-SIMULINK is used to get the relation between open circuit voltage and SOC. The circuit parameters are determined using neural network. The performance of the identified parameters is verified with the generic battery in MATLAB.en_US
dc.language.isoenen_US
dc.publisherProceedings of the International Conference on Power Electronics, Drives, and Energy Systems for Industrial Growth, PEDESen_US
dc.subjectBattery parametersen_US
dc.subjectElectric network parametersen_US
dc.titleIdentification of Li-Ion Battery Parameters Using Neural Networksen_US
dc.typeOtheren_US
Appears in Collections:Electrical Engineering

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