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dc.contributor.authorSivaranjani, J.
dc.contributor.authorSandeep, B.
dc.contributor.authorOlety, V.R.
dc.contributor.authorNavin, Karanth, P.
dc.date.accessioned2020-03-30T10:18:25Z-
dc.date.available2020-03-30T10:18:25Z-
dc.date.issued2017
dc.identifier.citationProceedings of 2016 Online International Conference on Green Engineering and Technologies, IC-GET 2016, 2017, Vol., , pp.-en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8328-
dc.description.abstractIn devices where rechargeable batteries are used, it is useful to have an estimate of the time taken to complete charging of the battery. It is a non-trivial activity to estimate this time, because this is affected by many factors such as the State of Charge (SOC), State of Health (SOH), temperature and operating conditions of the battery. This is the reason, even in mobile phones, only the percentage charged of the battery is mentioned by the Original Equipment Manufacturers but not the time required to complete the charging. This percentage is usually based on SOC algorithms which are approximate estimate and as the battery ages, this indication is less accurate. This paper focuses on the approach to estimate the charging time of lithium ion battery in accordance with the health of the battery. In this work, the charging time and the capacity of a lithium ion battery over its entire life is recorded into a database. Using this database, the charging profiles and capacity of the battery are modeled as equations. These equations are used for the calculation of charging time of any similar battery at any SOH. The algorithm designed can also be used to warn the consumers about the battery aging details of their device by the calculation of SOH of the battery. This algorithm is formulated based on 32.4V 3Ah lithium ion battery and verified for the same. � 2016 IEEE.en_US
dc.titleIntelligent charging system for dedicated applications using lithium ion batteryen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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