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

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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publication2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509009169
DOIs
Publication statusPublished - Jul 2 2016
Event59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016 - Abu Dhabi, United Arab Emirates
Duration: Oct 16 2016Oct 19 2016

Publication series

NameMidwest Symposium on Circuits and Systems
Volume0
ISSN (Print)1548-3746

Other

Other59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period10/16/1610/19/16

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

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