Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/5925
Title: Adaptive techniques used for lifetime estimation of lithium-ion batteries
Authors: Khayat, Nachaat
Karami, Nabil
Affiliations: Faculty of Engineering 
Faculty of Engineering 
Issue Date: 2016-01-17
Part of: 2016 3rd International Conference on Electrical, Electronics, Computer Engineering and their Applications, EECEA 2016
Start page: 98
End page: 103
Conference: International Conference on Electrical, Electronics, Computer Engineering and their Applications, EECEA 2016 ( 3rd : 21-23 April, 2016 : Beirut, Lebanon )
Abstract: 
A review on the different studies made on the lifetime estimation of the Lithium-Ion batteries. As lithium batteries are one off the main components of many instruments nowadays. This paper reviews and summaries the main studies and researches made to estimate the lifetime, the SOC (State-Of-charge) and the SOH (State Of Health - ability of a battery to display its discharge rate over its lifetime) of this battery model. This is a crucial study because the battery end-of-service-lifetime is important to prevent any sudden power shortages. Four adaptive systems will be illustrated in this article, The Accelerated Lifetime testing Method, the Kalman filter, the Artificial Neural Network, the fuzzy logic systems and the accelerated aging tests.
URI: https://scholarhub.balamand.edu.lb/handle/uob/5925
ISBN: 9781467369428
DOI: 10.1109/EECEA.2016.7470773
Ezproxy URL: Link to full text
Type: Conference Paper
Appears in Collections:Department of Electrical Engineering

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