Parameter estimation of valve regulated lead acid batteries using metaheuristic evolutionary algorithm

Samantha S. Stephen; Zahi M. Omer; Abbas A. Fardoun; Ala A. Hussein

doi:10.1109/MWSCAS.2016.7870122

Parameter estimation of valve regulated lead acid batteries using metaheuristic evolutionary algorithm

Samantha S. Stephen, Zahi M. Omer, Abbas A. Fardoun, Ala A. Hussein

Department of Electrical and Communication Engineering

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

2 Citations (Scopus)

Abstract

This paper investigates the use of a metaheuristic evolutionary algorithm. The algorithm, known as Bird Mating Optimizer (BMO), allows fault diagnosis and state-of-health estimation by comparing the battery parameters with the values for a brand new battery, in real time, which in turn allows the battery management system (BMS) to improve the energy management and eventually the lifetime of the battery. In this study, the equivalent-circuit model (ECM) parameters of a leadacid battery are extracted from its voltage response using the BMO algorithm. The accuracy of the BMO method is then compared to traditional Least Square (LS) algorithm. The BMO extracted parameters showed close fit to the experimental data.

Original language	English
Title of host publication	2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509009169
DOIs	https://doi.org/10.1109/MWSCAS.2016.7870122
Publication status	Published - Jul 2 2016
Event	59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016 - Abu Dhabi, United Arab Emirates Duration: Oct 16 2016 → Oct 19 2016

Publication series

Name	Midwest Symposium on Circuits and Systems
Volume	0
ISSN (Print)	1548-3746

Other

Other	59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016
Country/Territory	United Arab Emirates
City	Abu Dhabi
Period	10/16/16 → 10/19/16

Keywords

Battery equivalent circuit model (ECM)
Battery modelling
Evolutionary algorithms
Impedance spectrum

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

Access to Document

10.1109/MWSCAS.2016.7870122

Cite this

Stephen, S. S., Omer, Z. M., Fardoun, A. A., & Hussein, A. A. (2016). Parameter estimation of valve regulated lead acid batteries using metaheuristic evolutionary algorithm. In 2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016 [7870122] (Midwest Symposium on Circuits and Systems; Vol. 0). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MWSCAS.2016.7870122

Parameter estimation of valve regulated lead acid batteries using metaheuristic evolutionary algorithm. / Stephen, Samantha S.; Omer, Zahi M.; Fardoun, Abbas A. et al.
2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7870122 (Midwest Symposium on Circuits and Systems; Vol. 0).

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

Stephen, SS, Omer, ZM, Fardoun, AA & Hussein, AA 2016, Parameter estimation of valve regulated lead acid batteries using metaheuristic evolutionary algorithm. in 2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016., 7870122, Midwest Symposium on Circuits and Systems, vol. 0, Institute of Electrical and Electronics Engineers Inc., 59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016, Abu Dhabi, United Arab Emirates, 10/16/16. https://doi.org/10.1109/MWSCAS.2016.7870122

Stephen SS, Omer ZM, Fardoun AA, Hussein AA. Parameter estimation of valve regulated lead acid batteries using metaheuristic evolutionary algorithm. In 2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7870122. (Midwest Symposium on Circuits and Systems). doi: 10.1109/MWSCAS.2016.7870122

@inproceedings{c22d7c01324b4bed80bf831b97e69862,

title = "Parameter estimation of valve regulated lead acid batteries using metaheuristic evolutionary algorithm",

abstract = "This paper investigates the use of a metaheuristic evolutionary algorithm. The algorithm, known as Bird Mating Optimizer (BMO), allows fault diagnosis and state-of-health estimation by comparing the battery parameters with the values for a brand new battery, in real time, which in turn allows the battery management system (BMS) to improve the energy management and eventually the lifetime of the battery. In this study, the equivalent-circuit model (ECM) parameters of a leadacid battery are extracted from its voltage response using the BMO algorithm. The accuracy of the BMO method is then compared to traditional Least Square (LS) algorithm. The BMO extracted parameters showed close fit to the experimental data.",

keywords = "Battery equivalent circuit model (ECM), Battery modelling, Evolutionary algorithms, Impedance spectrum",

author = "Stephen, {Samantha S.} and Omer, {Zahi M.} and Fardoun, {Abbas A.} and Hussein, {Ala A.}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016 ; Conference date: 16-10-2016 Through 19-10-2016",

year = "2016",

month = jul,

day = "2",

doi = "10.1109/MWSCAS.2016.7870122",

language = "English",

series = "Midwest Symposium on Circuits and Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016",

}

TY - GEN

T1 - Parameter estimation of valve regulated lead acid batteries using metaheuristic evolutionary algorithm

AU - Stephen, Samantha S.

AU - Omer, Zahi M.

AU - Fardoun, Abbas A.

AU - Hussein, Ala A.

PY - 2016/7/2

Y1 - 2016/7/2

N2 - This paper investigates the use of a metaheuristic evolutionary algorithm. The algorithm, known as Bird Mating Optimizer (BMO), allows fault diagnosis and state-of-health estimation by comparing the battery parameters with the values for a brand new battery, in real time, which in turn allows the battery management system (BMS) to improve the energy management and eventually the lifetime of the battery. In this study, the equivalent-circuit model (ECM) parameters of a leadacid battery are extracted from its voltage response using the BMO algorithm. The accuracy of the BMO method is then compared to traditional Least Square (LS) algorithm. The BMO extracted parameters showed close fit to the experimental data.

AB - This paper investigates the use of a metaheuristic evolutionary algorithm. The algorithm, known as Bird Mating Optimizer (BMO), allows fault diagnosis and state-of-health estimation by comparing the battery parameters with the values for a brand new battery, in real time, which in turn allows the battery management system (BMS) to improve the energy management and eventually the lifetime of the battery. In this study, the equivalent-circuit model (ECM) parameters of a leadacid battery are extracted from its voltage response using the BMO algorithm. The accuracy of the BMO method is then compared to traditional Least Square (LS) algorithm. The BMO extracted parameters showed close fit to the experimental data.

KW - Battery equivalent circuit model (ECM)

KW - Battery modelling

KW - Evolutionary algorithms

KW - Impedance spectrum

UR - http://www.scopus.com/inward/record.url?scp=85015880183&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85015880183&partnerID=8YFLogxK

U2 - 10.1109/MWSCAS.2016.7870122

DO - 10.1109/MWSCAS.2016.7870122

M3 - Conference contribution

AN - SCOPUS:85015880183

T3 - Midwest Symposium on Circuits and Systems

BT - 2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016

Y2 - 16 October 2016 through 19 October 2016

ER -

Parameter estimation of valve regulated lead acid batteries using metaheuristic evolutionary algorithm

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this