Review of Battery State-of-Charge Estimation Algorithms

Kaustubh Kaushik; Devang Sureka; H. V.Gururaja Rao

doi:10.1007/978-981-16-1642-6_29

Review of Battery State-of-Charge Estimation Algorithms

Kaustubh Kaushik
, Devang Sureka
, H. V.Gururaja Rao^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

State of charge (SOC) is an important parameter used by a battery management system (BMS). Accurate and robust algorithms ensure the safe and reliable functioning of cells or batteries. Thus far, the algorithms developed depend mainly on the current and voltage data received from individual cells or the entire battery. To ensure battery safety usage and reduce the average lifecycle cost, accurate state of charge (SOC), tracking algorithms for real-time implementation are essential in different applications. This paper aims to compare SOC estimation algorithms and modular algorithms that employ more than one traditional SOC estimation method. This paper aims to describe the basic theoretical concepts involved in the standard algorithms. It also discusses more accurate algorithms suited for online implementation, which is favorable for real applications.

Original language	English
Title of host publication	Advances in Renewable Energy and Electric Vehicles - Select Proceedings of AREEV 2020
Editors	Sanjeevikumar Padmanaban, Nagesh Prabhu, Suryanarayana K.
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	375-387
Number of pages	13
ISBN (Print)	9789811616419
DOIs	https://doi.org/10.1007/978-981-16-1642-6_29
Publication status	Published - 2022
Event	International Conference on Advances in Renewable Energy and Electric Vehicles, AREEV 2020 - Nitte, India Duration: 22-12-2020 → 23-12-2020

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	767
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	International Conference on Advances in Renewable Energy and Electric Vehicles, AREEV 2020
Country/Territory	India
City	Nitte
Period	22-12-20 → 23-12-20

All Science Journal Classification (ASJC) codes

Industrial and Manufacturing Engineering

Access to Document

10.1007/978-981-16-1642-6_29

Cite this

Kaushik, K., Sureka, D., & Rao, H. V. G. (2022). Review of Battery State-of-Charge Estimation Algorithms. In S. Padmanaban, N. Prabhu, & S. K. (Eds.), Advances in Renewable Energy and Electric Vehicles - Select Proceedings of AREEV 2020 (pp. 375-387). (Lecture Notes in Electrical Engineering; Vol. 767). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-1642-6_29

Kaushik, Kaustubh ; Sureka, Devang ; Rao, H. V.Gururaja. / Review of Battery State-of-Charge Estimation Algorithms. Advances in Renewable Energy and Electric Vehicles - Select Proceedings of AREEV 2020. editor / Sanjeevikumar Padmanaban ; Nagesh Prabhu ; Suryanarayana K. Springer Science and Business Media Deutschland GmbH, 2022. pp. 375-387 (Lecture Notes in Electrical Engineering).

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title = "Review of Battery State-of-Charge Estimation Algorithms",

abstract = "State of charge (SOC) is an important parameter used by a battery management system (BMS). Accurate and robust algorithms ensure the safe and reliable functioning of cells or batteries. Thus far, the algorithms developed depend mainly on the current and voltage data received from individual cells or the entire battery. To ensure battery safety usage and reduce the average lifecycle cost, accurate state of charge (SOC), tracking algorithms for real-time implementation are essential in different applications. This paper aims to compare SOC estimation algorithms and modular algorithms that employ more than one traditional SOC estimation method. This paper aims to describe the basic theoretical concepts involved in the standard algorithms. It also discusses more accurate algorithms suited for online implementation, which is favorable for real applications.",

author = "Kaustubh Kaushik and Devang Sureka and Rao, \{H. V.Gururaja\}",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Advances in Renewable Energy and Electric Vehicles, AREEV 2020 ; Conference date: 22-12-2020 Through 23-12-2020",

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series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

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Kaushik, K, Sureka, D & Rao, HVG 2022, Review of Battery State-of-Charge Estimation Algorithms. in S Padmanaban, N Prabhu & S K. (eds), Advances in Renewable Energy and Electric Vehicles - Select Proceedings of AREEV 2020. Lecture Notes in Electrical Engineering, vol. 767, Springer Science and Business Media Deutschland GmbH, pp. 375-387, International Conference on Advances in Renewable Energy and Electric Vehicles, AREEV 2020, Nitte, India, 22-12-20. https://doi.org/10.1007/978-981-16-1642-6_29

Review of Battery State-of-Charge Estimation Algorithms. / Kaushik, Kaustubh; Sureka, Devang; Rao, H. V.Gururaja.
Advances in Renewable Energy and Electric Vehicles - Select Proceedings of AREEV 2020. ed. / Sanjeevikumar Padmanaban; Nagesh Prabhu; Suryanarayana K. Springer Science and Business Media Deutschland GmbH, 2022. p. 375-387 (Lecture Notes in Electrical Engineering; Vol. 767).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - State of charge (SOC) is an important parameter used by a battery management system (BMS). Accurate and robust algorithms ensure the safe and reliable functioning of cells or batteries. Thus far, the algorithms developed depend mainly on the current and voltage data received from individual cells or the entire battery. To ensure battery safety usage and reduce the average lifecycle cost, accurate state of charge (SOC), tracking algorithms for real-time implementation are essential in different applications. This paper aims to compare SOC estimation algorithms and modular algorithms that employ more than one traditional SOC estimation method. This paper aims to describe the basic theoretical concepts involved in the standard algorithms. It also discusses more accurate algorithms suited for online implementation, which is favorable for real applications.

AB - State of charge (SOC) is an important parameter used by a battery management system (BMS). Accurate and robust algorithms ensure the safe and reliable functioning of cells or batteries. Thus far, the algorithms developed depend mainly on the current and voltage data received from individual cells or the entire battery. To ensure battery safety usage and reduce the average lifecycle cost, accurate state of charge (SOC), tracking algorithms for real-time implementation are essential in different applications. This paper aims to compare SOC estimation algorithms and modular algorithms that employ more than one traditional SOC estimation method. This paper aims to describe the basic theoretical concepts involved in the standard algorithms. It also discusses more accurate algorithms suited for online implementation, which is favorable for real applications.

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ER -

Review of Battery State-of-Charge Estimation Algorithms

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