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State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review

Charging (batteries); Classification (of information); Disaster prevention; Electric discharges; Electric vehicles; Estimation; Ions; Life cycle; Lithium-ion batteries; Data-driven approach; Data-driven methods; High energy densities; Mathematical equations; Model based approach; Model-based method;...

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Main Authors: How D.N.T., Hannan M.A., Hossain Lipu M.S., Ker P.J.
Other Authors: 57212923888
Format: Review
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-249032023-05-29T15:28:34Z State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review How D.N.T. Hannan M.A. Hossain Lipu M.S. Ker P.J. 57212923888 7103014445 36518949700 37461740800 Charging (batteries); Classification (of information); Disaster prevention; Electric discharges; Electric vehicles; Estimation; Ions; Life cycle; Lithium-ion batteries; Data-driven approach; Data-driven methods; High energy densities; Mathematical equations; Model based approach; Model-based method; State of charge; State-of-charge estimation; Battery management systems Lithium-ion battery is an appropriate choice for electric vehicle (EV) due to its promising features of high voltage, high energy density, low self-discharge and long lifecycles. The successful operation of EV is highly dependent on the operation of battery management system (BMS). State of charge (SOC) is one of the vital paraments of BMS which signifies the amount of charge left in a battery. A good estimation of SOC leads to long battery life and prevention of catastrophe from battery failure. Besides, an accurate and robust SOC estimation has great significance towards an efficient EV operation. However, SOC estimation is a complex process due to its dependency on various factors such as battery age, ambient temperature, and many unknown factors. This review presents the recent SOC estimation methods highlighting the model-based and data-driven approaches. Model-based methods attempt to model the battery behavior incorporating various factors into complex mathematical equations in order to accurately estimate the SOC while the data-driven methods adopt an approach of learning the battery's behavior by running complex algorithms with a large amount of measured battery data. The classifications of model-based and data-driven based SOC estimation are explained in terms of estimation model/algorithm, benefits, drawbacks, and estimation error. In addition, the review highlights many factors and challenges and delivers potential recommendations for the development of SOC estimation methods in EV applications. All the highlighted insights of this review will hopefully lead to increased efforts toward the enhancement of SOC estimation method of lithium-ion battery for the future high-Tech EV applications. � 2013 IEEE. Final 2023-05-29T07:28:33Z 2023-05-29T07:28:33Z 2019 Review 10.1109/ACCESS.2019.2942213 2-s2.0-85076262905 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076262905&doi=10.1109%2fACCESS.2019.2942213&partnerID=40&md5=e6b8e1add9ea15ec9781d8e1ae4f8f09 https://irepository.uniten.edu.my/handle/123456789/24903 7 8843918 136116 136136 All Open Access, Gold Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Charging (batteries); Classification (of information); Disaster prevention; Electric discharges; Electric vehicles; Estimation; Ions; Life cycle; Lithium-ion batteries; Data-driven approach; Data-driven methods; High energy densities; Mathematical equations; Model based approach; Model-based method; State of charge; State-of-charge estimation; Battery management systems
author2 57212923888
author_facet 57212923888
How D.N.T.
Hannan M.A.
Hossain Lipu M.S.
Ker P.J.
format Review
author How D.N.T.
Hannan M.A.
Hossain Lipu M.S.
Ker P.J.
spellingShingle How D.N.T.
Hannan M.A.
Hossain Lipu M.S.
Ker P.J.
State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review
author_sort How D.N.T.
title State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review
title_short State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review
title_full State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review
title_fullStr State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review
title_full_unstemmed State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review
title_sort state of charge estimation for lithium-ion batteries using model-based and data-driven methods: a review
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806424324635099136
score 13.222552

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