Publication: Enhanced State of Charge Estimation for Lithiumion Batteries using Polynomial Voltage Approximation
Date
2024
Authors
Karna S.
Satpathy P.R.
Bhowmik P.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
The escalating adoption of electric machinery as a replacement for the fossil fuel-powered counterparts has underscored the critical need for robust energy storage solutions, with lithium-ion (Li-ion) batteries emerging as a cornerstone technology, particularly in electric vehicles (EVs). However, the intrinsic vulnerability of Li-ion batteries to degradation, caused by cyclic charge-discharge operations, poses significant challenges to accurate state of charge (SOC) estimation and capacity assessment, thereby impeding optimal EV performance [12] [16]. This study presents a novel approach to address these challenges by elucidating a direct correlation between battery voltage and SOC. Through rigorous empirical experimentation and advanced mathematical modelling, a polynomial equation is derived to precisely quantify SOC dynamics in response to voltage fluctuations. This framework facilitates real-time capacity estimation, empowering proactive management of EV energy systems [18]. By integrating empirical data with sophisticated mathematical analysis, this research contributes to deeper understanding of Li-ion battery behavior, paving the way for enhanced energy storage management strategies. The findings hold promise for optimizing EV efficiency, reliability, and longevity in the evolving landscape of electric machinery. ? 2024 IEEE.
Description
Keywords
Battery management systems , Battery storage , Benchmarking , Polynomial approximation , Energy , Ion batteries , Lithium ions , Mismatch , Multiple-peak , Partial shading , Photovoltaics , Robust energy , State-of-charge estimation , States of charges , State of charge