The University of Southampton
University of Southampton Institutional Repository

Identification of dynamic model parameters for lithium-ion batteries used in hybrid electric vehicles

Identification of dynamic model parameters for lithium-ion batteries used in hybrid electric vehicles
Identification of dynamic model parameters for lithium-ion batteries used in hybrid electric vehicles
This paper presents an electrical equivalent circuit model for lithium-ion batteries usedfor hybrid electric vehicles (HEV). The model has two RC networks characterizing battery activation and concentration polarization process. The parameters of the model are identified using combined experimental and Extended Kalman Filter (EKF) recursive methods. The open-circuit voltage and ohmic resistance of the battery are directly measured and calculated from experimental measurements, respectively. The rest of the coupled dynamic parameters, i.e. the RC network parameters, are estimated using the EKF method. Experimental and simulation results are presented to demonstrate the efficacy of the proposed circuit model and parameter identification techniques for simulating battery dynamics
Zhang, C.P.
b31ce4c0-283b-426c-ba3f-dd3b1da32a5d
Liu, J.Z.
517a8f8f-b56f-4eeb-9adc-c15d611a2e34
Sharkh, S.M.
c8445516-dafe-41c2-b7e8-c21e295e56b9
Zhang, C.P.
b31ce4c0-283b-426c-ba3f-dd3b1da32a5d
Liu, J.Z.
517a8f8f-b56f-4eeb-9adc-c15d611a2e34
Sharkh, S.M.
c8445516-dafe-41c2-b7e8-c21e295e56b9

Zhang, C.P., Liu, J.Z. and Sharkh, S.M. (2009) Identification of dynamic model parameters for lithium-ion batteries used in hybrid electric vehicles. International Symposium on Electric Vehicles (ISEV), Beijing, China. 01 Sep 2009. 11 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

This paper presents an electrical equivalent circuit model for lithium-ion batteries usedfor hybrid electric vehicles (HEV). The model has two RC networks characterizing battery activation and concentration polarization process. The parameters of the model are identified using combined experimental and Extended Kalman Filter (EKF) recursive methods. The open-circuit voltage and ohmic resistance of the battery are directly measured and calculated from experimental measurements, respectively. The rest of the coupled dynamic parameters, i.e. the RC network parameters, are estimated using the EKF method. Experimental and simulation results are presented to demonstrate the efficacy of the proposed circuit model and parameter identification techniques for simulating battery dynamics

Text
Identification_of_Dynamic_Model_Parameters_for.pdf - Accepted Manuscript
Download (100kB)

More information

Published date: 2009
Venue - Dates: International Symposium on Electric Vehicles (ISEV), Beijing, China, 2009-09-01 - 2009-09-01

Identifiers

Local EPrints ID: 73265
URI: http://eprints.soton.ac.uk/id/eprint/73265
PURE UUID: e648768c-e82a-4f78-85d4-1c9b445a1ad5
ORCID for S.M. Sharkh: ORCID iD orcid.org/0000-0001-7335-8503

Catalogue record

Date deposited: 04 Mar 2010
Last modified: 14 Mar 2024 02:38

Export record

Contributors

Author: C.P. Zhang
Author: J.Z. Liu
Author: S.M. Sharkh ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×