Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 1045076

Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack


Maletić, Filip; Hrgetić Mario; Deur, Joško
Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack // Energies, 13 (2020), 3; 540, 16 doi:10.3390/en13030540 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1045076 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack

Autori
Maletić, Filip ; Hrgetić Mario ; Deur, Joško

Izvornik
Energies (1996-1073) 13 (2020), 3; 540, 16

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
electric vehicle ; lithium-ion battery ; estimation ; Kalman filter ; state-of-charge ; state-of-health ; resistance ; open-circuit voltage ; battery capacity

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb

Profili:

Avatar Url Mario Hrgetić (autor)

Avatar Url Joško Deur (autor)

Avatar Url Filip Maletić (autor)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada doi www.mdpi.com

Citiraj ovu publikaciju:

Maletić, Filip; Hrgetić Mario; Deur, Joško
Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack // Energies, 13 (2020), 3; 540, 16 doi:10.3390/en13030540 (međunarodna recenzija, članak, znanstveni)
Maletić, F., Hrgetić Mario & 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, 16 doi:10.3390/en13030540.
@article{article, author = {Maleti\'{c}, Filip and Deur, Jo\v{s}ko}, year = {2020}, pages = {16}, DOI = {10.3390/en13030540}, chapter = {540}, keywords = {electric vehicle, lithium-ion battery, estimation, Kalman filter, state-of-charge, state-of-health, resistance, open-circuit voltage, battery capacity}, journal = {Energies}, doi = {10.3390/en13030540}, volume = {13}, number = {3}, issn = {1996-1073}, title = {Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack}, keyword = {electric vehicle, lithium-ion battery, estimation, Kalman filter, state-of-charge, state-of-health, resistance, open-circuit voltage, battery capacity}, chapternumber = {540} }
@article{article, author = {Maleti\'{c}, Filip and Deur, Jo\v{s}ko}, year = {2020}, pages = {16}, DOI = {10.3390/en13030540}, chapter = {540}, keywords = {electric vehicle, lithium-ion battery, estimation, Kalman filter, state-of-charge, state-of-health, resistance, open-circuit voltage, battery capacity}, journal = {Energies}, doi = {10.3390/en13030540}, volume = {13}, number = {3}, issn = {1996-1073}, title = {Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack}, keyword = {electric vehicle, lithium-ion battery, estimation, Kalman filter, state-of-charge, state-of-health, resistance, open-circuit voltage, battery capacity}, chapternumber = {540} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





    Contrast
    Increase Font
    Decrease Font
    Dyslexic Font