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

Milos Lukic; Paolo Giangrande; Christian Klumpner; Michael Galea

doi:10.1109/VPPC49601.2020.9330955

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

Milos Lukic, Paolo Giangrande, Christian Klumpner, Michael Galea

Department of Mechanical, Materials and Manufacturing Engineering

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

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 language	English
Title of host publication	2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728189598
DOIs	https://doi.org/10.1109/VPPC49601.2020.9330955
Publication status	Published - Nov 2020
Event	17th IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Virtual, Gijon, Spain Duration: 18 Nov 2020 → 16 Dec 2020

Publication series

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

Conference

Conference	17th IEEE Vehicle Power and Propulsion Conference, VPPC 2020
Country/Territory	Spain
City	Virtual, Gijon
Period	18/11/20 → 16/12/20

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

UN SDGs

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

Access to Document

10.1109/VPPC49601.2020.9330955

Cite this

Lukic, M., Giangrande, P., Klumpner, C., & Galea, M. (2020). Novel parameter identification method for lithium-ion batteries based on curve fitting. In 2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings Article 9330955 (2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VPPC49601.2020.9330955

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title = "Novel parameter identification method for lithium-ion batteries based on curve fitting",

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.",

keywords = "Batteries, Energy storage device, Modelling, Parameter identification",

author = "Milos Lukic and Paolo Giangrande and Christian Klumpner and Michael Galea",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 17th IEEE Vehicle Power and Propulsion Conference, VPPC 2020 ; Conference date: 18-11-2020 Through 16-12-2020",

year = "2020",

month = nov,

doi = "10.1109/VPPC49601.2020.9330955",

language = "English",

series = "2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings",

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

booktitle = "2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings",

address = "United States",

}

Lukic, M, Giangrande, P, Klumpner, C & Galea, M 2020, Novel parameter identification method for lithium-ion batteries based on curve fitting. in 2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings., 9330955, 2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 17th IEEE Vehicle Power and Propulsion Conference, VPPC 2020, Virtual, Gijon, Spain, 18/11/20. https://doi.org/10.1109/VPPC49601.2020.9330955

Novel parameter identification method for lithium-ion batteries based on curve fitting. / Lukic, Milos; Giangrande, Paolo; Klumpner, Christian et al.
2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. 9330955 (2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Novel parameter identification method for lithium-ion batteries based on curve fitting

AU - Lukic, Milos

AU - Giangrande, Paolo

AU - Klumpner, Christian

AU - Galea, Michael

PY - 2020/11

Y1 - 2020/11

N2 - 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.

AB - 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.

KW - Batteries

KW - Energy storage device

KW - Modelling

KW - Parameter identification

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U2 - 10.1109/VPPC49601.2020.9330955

DO - 10.1109/VPPC49601.2020.9330955

M3 - Conference contribution

AN - SCOPUS:85101969384

T3 - 2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings

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

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 17th IEEE Vehicle Power and Propulsion Conference, VPPC 2020

Y2 - 18 November 2020 through 16 December 2020

ER -

Lukic M, Giangrande P, Klumpner C, Galea M. Novel parameter identification method for lithium-ion batteries based on curve fitting. In 2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. 9330955. (2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings). doi: 10.1109/VPPC49601.2020.9330955

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

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

UN SDGs

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