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Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack
Energies, 13 (2020), 3; 540-556. https://doi.org/10.3390/en13030540
Maletić, Filip; Hrgetić, Mario; Deur, Joško

Institucijski repozitorij: Repozitorij Fakulteta strojarstva i brodogradnje Sveučilišta u Zagrebu

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Maletić, F., Hrgetić, M. i Deur, J. (2020). Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack. Energies, 13. (3), 540-556. doi: 10.3390/en13030540

Maletić, Filip, et al. "Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack." Energies, vol. 13, br. 3, 2020, str. 540-556. https://doi.org/10.3390/en13030540

Maletić, Filip, Mario Hrgetić i Joško Deur. "Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack." Energies 13, br. 3 (2020): 540-556. https://doi.org/10.3390/en13030540

Maletić, F., Hrgetić, M. i Deur, J. (2020) 'Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack', Energies, 13(3), str. 540-556. doi: 10.3390/en13030540

Maletić F, Hrgetić M, Deur J. Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack. Energies [Internet]. 22.01.2020. [pristupljeno 25.11.2024.];13(3):540-556. doi: 10.3390/en13030540

F. Maletić, M. Hrgetić i J. Deur, "Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack", Energies, vol. 13, br. 3, str. 540-556, Siječanj 2020. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:235:353571. [Citirano: 25.11.2024.]

Za citiranje koristite ovu mrežnu adresu: https://urn.nsk.hr/urn:nbn:hr:235:353571
Podaci o radu
Naslov (engleski)Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack
AutorFilip Maletić
AutorMario Hrgetić
AutorJoško Deur
Autorova ustanovaSveučilište u Zagrebu
Fakultet strojarstva i brodogradnje
(Zavod za robotiku i automatizaciju proizvodnih sustava)
(Katedra za strojarsku automatiku)
Znanstveno / umjetničko
područje, polje i grana		TEHNIČKE ZNANOSTI
Strojarstvo
Sažetak (engleski)
Accurate, real-time estimation of battery state-of-charge (SoC) and state-of-health represents a crucial task of modern battery management systems. Due to nonlinear and battery degradation-dependent behavior of output voltage, the design of these estimation algorithms should be based on nonlinear parameter-varying models. The paper first describes the experimental setup that consists of commercially available electric scooter equipped with telemetry measurement equipment. Next, dual extended Kalman filter-based (DEKF) estimator of battery SoC, internal resistances, and parameters of open-circuit voltage (OCV) vs. SoC characteristic is presented under the assumption of fixed polarization time constant vs. SoC characteristic. The DEKF is upgraded with an adaptation mechanism to capture the battery OCV hysteresis without explicitly modelling it. Parameterization of an explicit hysteresis model and its inclusion in the DEKF is also considered. Finally, a slow time scale, sigma-point Kalman filter-based capacity estimator is designed and inter-coupled with the DEKF. A convergence detection algorithm is proposed to ensure that the two estimators are coupled automatically only after the capacity estimate has converged. The overall estimator performance is experimentally validated for real electric scooter driving cycles.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaEnergies
Brojčani podacivol. 13, br. 3, str. 540-556
p-ISSN1996-1073
DOIhttps://doi.org/10.3390/en13030540
URN:NBNurn:nbn:hr:235:353571
Datum objave publikacije2020-01-22
URL dokumentahttps://www.mdpi.com/1996-1073/13/3/540
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Imenovanje 4.0 međunarodna (CC BY 4.0)
Datum i vrijeme pohrane2024-07-05 11:54:13