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Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation

Authors :
Muhammad Umair Ali
Amad Zafar
Sarvar Hussain Nengroo
Sadam Hussain
Muhammad Junaid Alvi
Hee-Je Kim
Source :
Energies, Vol 12, Iss 3, p 446 (2019)
Publication Year :
2019
Publisher :
MDPI AG, 2019.

Abstract

Energy storage system (ESS) technology is still the logjam for the electric vehicle (EV) industry. Lithium-ion (Li-ion) batteries have attracted considerable attention in the EV industry owing to their high energy density, lifespan, nominal voltage, power density, and cost. In EVs, a smart battery management system (BMS) is one of the essential components; it not only measures the states of battery accurately, but also ensures safe operation and prolongs the battery life. The accurate estimation of the state of charge (SOC) of a Li-ion battery is a very challenging task because the Li-ion battery is a highly time variant, non-linear, and complex electrochemical system. This paper explains the workings of a Li-ion battery, provides the main features of a smart BMS, and comprehensively reviews its SOC estimation methods. These SOC estimation methods have been classified into four main categories depending on their nature. A critical explanation, including their merits, limitations, and their estimation errors from other studies, is provided. Some recommendations depending on the development of technology are suggested to improve the online estimation.

Details

Language :
English
ISSN :
19961073
Volume :
12
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Energies
Publication Type :
Academic Journal
Accession number :
edsdoj.71f9714bb9d4d659e89115326c826af
Document Type :
article
Full Text :
https://doi.org/10.3390/en12030446