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Data-driven state of charge estimation of lithium-ion batteries: Algorithms, implementation factors, limitations and future trends

Author Affiliations
National University of Malaysia, Universiti Tenaga Nasional, American International University-Bangladesh
Published InJournal of Cleaner Production
Year2020
Citations365

Abstract

Global carbon emissions caused by fossil fuels and diesel-based vehicles have urged the necessity to move toward the development of electric vehicles and related battery storage systems. Lithium-ion batteries are the ideal candidate for electric vehicle due to their superior performance with regard to high energy density and long lifespan. The state of charge of lithium-ion batteries is one of the crucial evaluation indicators of the battery management system that confirms the extended battery life, better charging-discharging profiles, and safe driving of electric vehicles. However, the accuracy of the state of charge is influenced by several issues such as battery aging cycles, noise effects, and temperature impacts. Therefore, this review presents a detailed classification of the recent data-driven state of…
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