Exogenous kalman filter for state-of-charge estimation in lithium-ion batteries

Agus Hasan*, Martin Skriver, Tor Arne Johansen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper presents State-of-Charge (SoC) estimation of lithium-ion batteries using eXogenous Kalman filter (XKF). The state-space equation for the lithium-ion battery is obtained from the equivalent circuit model (ECM). It has linear process equations and a nonlinear output voltage equation. The estimation is done using a cascade of nonlinear observer and a linearized Kalman filter. The method is tested using experimental data of a lithium-ion-phosphate (LiFePO4) battery under dynamic stress test (DST) and federal urban driving schedule (FUDS). The results are compared with existing Kalman filters.

Original languageEnglish
Title of host publicationProceedings of the IEEE Conference on Control Technology and Applications, CCTA 2018
PublisherIEEE
Publication date26. Oct 2018
Pages1403-1408
ISBN (Print)978-1-5386-7699-8
ISBN (Electronic)978-1-5386-7698-1
DOIs
Publication statusPublished - 26. Oct 2018
Event2nd IEEE Conference on Control Technology and Applications, CCTA 2018 - Copenhagen, Denmark
Duration: 21. Aug 201824. Aug 2018

Conference

Conference2nd IEEE Conference on Control Technology and Applications, CCTA 2018
CountryDenmark
CityCopenhagen
Period21/08/201824/08/2018
SponsorIEEE Control Systems Society

Fingerprint

Kalman filters
Equivalent circuits
Phosphates
Lithium
Ions
Electric potential
Lithium-ion batteries

Cite this

Hasan, A., Skriver, M., & Johansen, T. A. (2018). Exogenous kalman filter for state-of-charge estimation in lithium-ion batteries. In Proceedings of the IEEE Conference on Control Technology and Applications, CCTA 2018 (pp. 1403-1408). IEEE. https://doi.org/10.1109/CCTA.2018.8511577
Hasan, Agus ; Skriver, Martin ; Johansen, Tor Arne. / Exogenous kalman filter for state-of-charge estimation in lithium-ion batteries. Proceedings of the IEEE Conference on Control Technology and Applications, CCTA 2018. IEEE, 2018. pp. 1403-1408
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abstract = "This paper presents State-of-Charge (SoC) estimation of lithium-ion batteries using eXogenous Kalman filter (XKF). The state-space equation for the lithium-ion battery is obtained from the equivalent circuit model (ECM). It has linear process equations and a nonlinear output voltage equation. The estimation is done using a cascade of nonlinear observer and a linearized Kalman filter. The method is tested using experimental data of a lithium-ion-phosphate (LiFePO4) battery under dynamic stress test (DST) and federal urban driving schedule (FUDS). The results are compared with existing Kalman filters.",
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Hasan, A, Skriver, M & Johansen, TA 2018, Exogenous kalman filter for state-of-charge estimation in lithium-ion batteries. in Proceedings of the IEEE Conference on Control Technology and Applications, CCTA 2018. IEEE, pp. 1403-1408, 2nd IEEE Conference on Control Technology and Applications, CCTA 2018, Copenhagen, Denmark, 21/08/2018. https://doi.org/10.1109/CCTA.2018.8511577

Exogenous kalman filter for state-of-charge estimation in lithium-ion batteries. / Hasan, Agus; Skriver, Martin; Johansen, Tor Arne.

Proceedings of the IEEE Conference on Control Technology and Applications, CCTA 2018. IEEE, 2018. p. 1403-1408.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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AB - This paper presents State-of-Charge (SoC) estimation of lithium-ion batteries using eXogenous Kalman filter (XKF). The state-space equation for the lithium-ion battery is obtained from the equivalent circuit model (ECM). It has linear process equations and a nonlinear output voltage equation. The estimation is done using a cascade of nonlinear observer and a linearized Kalman filter. The method is tested using experimental data of a lithium-ion-phosphate (LiFePO4) battery under dynamic stress test (DST) and federal urban driving schedule (FUDS). The results are compared with existing Kalman filters.

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Hasan A, Skriver M, Johansen TA. Exogenous kalman filter for state-of-charge estimation in lithium-ion batteries. In Proceedings of the IEEE Conference on Control Technology and Applications, CCTA 2018. IEEE. 2018. p. 1403-1408 https://doi.org/10.1109/CCTA.2018.8511577