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

Agus Hasan*, Martin Skriver, Tor Arne Johansen

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Publikation: Bidrag til bog/antologi/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Resumé

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.

OriginalsprogEngelsk
TitelProceedings of the IEEE Conference on Control Technology and Applications, CCTA 2018
ForlagIEEE
Publikationsdato26. okt. 2018
Sider1403-1408
ISBN (Trykt)978-1-5386-7699-8
ISBN (Elektronisk)978-1-5386-7698-1
DOI
StatusUdgivet - 26. okt. 2018
Begivenhed2nd IEEE Conference on Control Technology and Applications, CCTA 2018 - Copenhagen, Danmark
Varighed: 21. aug. 201824. aug. 2018

Konference

Konference2nd IEEE Conference on Control Technology and Applications, CCTA 2018
LandDanmark
ByCopenhagen
Periode21/08/201824/08/2018
SponsorIEEE Control Systems Society

Fingeraftryk

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

Citer dette

Hasan, A., Skriver, M., & Johansen, T. A. (2018). Exogenous kalman filter for state-of-charge estimation in lithium-ion batteries. I Proceedings of the IEEE Conference on Control Technology and Applications, CCTA 2018 (s. 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. s. 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. i Proceedings of the IEEE Conference on Control Technology and Applications, CCTA 2018. IEEE, s. 1403-1408, 2nd IEEE Conference on Control Technology and Applications, CCTA 2018, Copenhagen, Danmark, 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. s. 1403-1408.

Publikation: Bidrag til bog/antologi/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

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N2 - 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.

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. I Proceedings of the IEEE Conference on Control Technology and Applications, CCTA 2018. IEEE. 2018. s. 1403-1408 https://doi.org/10.1109/CCTA.2018.8511577