State-of-charge estimation for a single Lithium battery cell using Extended Kalman Filter

Ala Al Haj Hussein; Issa Batarseh

doi:10.1109/PES.2011.6039679

State-of-charge estimation for a single Lithium battery cell using Extended Kalman Filter

Ala Al Haj Hussein, Issa Batarseh

Department of Electrical and Communication Engineering

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

18 Citations (Scopus)

Abstract

An accurate state-of-charge (SOC) estimation is desired in most battery systems. It increases the reliability of the system and extends the lifetime of the battery. This paper proposes an Extended Kalman Filter (EKF) algorithm to estimate the SOC of a Lithium battery cell. To implement the SOC algorithm, an improved Lithium battery cell model is used. The results of the model and EKF algorithm show the effectiveness and ease of implementation of the proposed technique.

Original language	English
Title of host publication	2011 IEEE PES General Meeting
Subtitle of host publication	The Electrification of Transportation and the Grid of the Future
DOIs	https://doi.org/10.1109/PES.2011.6039679
Publication status	Published - Dec 9 2011
Event	2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future - Detroit, MI, United States Duration: Jul 24 2011 → Jul 28 2011

Publication series

Name	IEEE Power and Energy Society General Meeting
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Other

Other	2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future
Country/Territory	United States
City	Detroit, MI
Period	7/24/11 → 7/28/11

Keywords

Extended Kalman Filter (EKF)
State-of-charge (SOC)
hysteresis voltage
relaxation

ASJC Scopus subject areas

Energy Engineering and Power Technology
Nuclear Energy and Engineering
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/PES.2011.6039679

Cite this

State-of-charge estimation for a single Lithium battery cell using Extended Kalman Filter. / Hussein, Ala Al Haj; Batarseh, Issa.
2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future. 2011. 6039679 (IEEE Power and Energy Society General Meeting).

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

Hussein, AAH & Batarseh, I 2011, State-of-charge estimation for a single Lithium battery cell using Extended Kalman Filter. in 2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future., 6039679, IEEE Power and Energy Society General Meeting, 2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future, Detroit, MI, United States, 7/24/11. https://doi.org/10.1109/PES.2011.6039679

@inproceedings{4fb40069f99f43fda3e66a4b527a6572,

title = "State-of-charge estimation for a single Lithium battery cell using Extended Kalman Filter",

abstract = "An accurate state-of-charge (SOC) estimation is desired in most battery systems. It increases the reliability of the system and extends the lifetime of the battery. This paper proposes an Extended Kalman Filter (EKF) algorithm to estimate the SOC of a Lithium battery cell. To implement the SOC algorithm, an improved Lithium battery cell model is used. The results of the model and EKF algorithm show the effectiveness and ease of implementation of the proposed technique.",

keywords = "Extended Kalman Filter (EKF), State-of-charge (SOC), hysteresis voltage, relaxation",

author = "Hussein, {Ala Al Haj} and Issa Batarseh",

year = "2011",

month = dec,

day = "9",

doi = "10.1109/PES.2011.6039679",

language = "English",

isbn = "9781457710018",

series = "IEEE Power and Energy Society General Meeting",

booktitle = "2011 IEEE PES General Meeting",

note = "2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future ; Conference date: 24-07-2011 Through 28-07-2011",

}

TY - GEN

T1 - State-of-charge estimation for a single Lithium battery cell using Extended Kalman Filter

AU - Hussein, Ala Al Haj

AU - Batarseh, Issa

PY - 2011/12/9

Y1 - 2011/12/9

N2 - An accurate state-of-charge (SOC) estimation is desired in most battery systems. It increases the reliability of the system and extends the lifetime of the battery. This paper proposes an Extended Kalman Filter (EKF) algorithm to estimate the SOC of a Lithium battery cell. To implement the SOC algorithm, an improved Lithium battery cell model is used. The results of the model and EKF algorithm show the effectiveness and ease of implementation of the proposed technique.

AB - An accurate state-of-charge (SOC) estimation is desired in most battery systems. It increases the reliability of the system and extends the lifetime of the battery. This paper proposes an Extended Kalman Filter (EKF) algorithm to estimate the SOC of a Lithium battery cell. To implement the SOC algorithm, an improved Lithium battery cell model is used. The results of the model and EKF algorithm show the effectiveness and ease of implementation of the proposed technique.

KW - Extended Kalman Filter (EKF)

KW - State-of-charge (SOC)

KW - hysteresis voltage

KW - relaxation

UR - http://www.scopus.com/inward/record.url?scp=82855172235&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=82855172235&partnerID=8YFLogxK

U2 - 10.1109/PES.2011.6039679

DO - 10.1109/PES.2011.6039679

M3 - Conference contribution

AN - SCOPUS:82855172235

SN - 9781457710018

T3 - IEEE Power and Energy Society General Meeting

BT - 2011 IEEE PES General Meeting

T2 - 2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future

Y2 - 24 July 2011 through 28 July 2011

ER -

State-of-charge estimation for a single Lithium battery cell using Extended Kalman Filter

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this