Novel parameter identification method for lithium-ion batteries based on curve fitting

Milos Lukic, Paolo Giangrande, Christian Klumpner, Michael Galea

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

This paper describes a new curve-fitting lithium-ion battery parameter identification method for equivalent circuit models. The current pulse/relaxation test is carried out and the corresponding terminal voltage is used for extracting the battery model parameters. Analysis and fitting of the waveform is performed for both pulse and relaxation periods without assuming the initial conditions of the associated RC branches. This approach is demonstrated for 2nd order model using commercial battery cell and model results are presented and compared against experimental finding revealing a good agreement.

Original languageEnglish
Title of host publication2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728189598
DOIs
Publication statusPublished - Nov 2020
Event17th IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Virtual, Gijon, Spain
Duration: 18 Nov 202016 Dec 2020

Publication series

Name2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings

Conference

Conference17th IEEE Vehicle Power and Propulsion Conference, VPPC 2020
Country/TerritorySpain
CityVirtual, Gijon
Period18/11/2016/12/20

Keywords

  • Batteries
  • Energy storage device
  • Modelling
  • Parameter identification

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Aerospace Engineering
  • Automotive Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Modelling and Simulation

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