State-of-Charge Estimation of NMC-based Li-ion Battery Based on Continuous Transfer Function Model and Extended Kalman Filter

Farshid Naseri, Erik Schaltz, Daniel Ion Stroe, Alejandro Gismero, Ebrahim Farjah, Sepehr Karimi

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Abstrakt

Lithium-ion (Li) battery based on nickel-manganese-cobalt (NMC) cathode has emerged as one of the most successful battery types for powertrain of Electric Vehicles (EVs). The effective management of the NMC-based battery relies on accurate estimation of its State-of-Charge (SoC) in the Battery Management System (BMS). In this paper, an effective system identification approach is applied to establish the battery model using a Continuous Transfer Function (CTF) model. The Akaike information criterion (AIC) is applied to obtain the suitable model structure considering the accuracy and real-time efficiency of the model. Then, the SoC Estimation is fulfilled based on the developed model and the Extended Kalman Filter (EKF) algorithm. The correct performance of the proposed method is evaluated and confirmed using experimental data of 3.4 Ah 3.7 V NMC-based battery cells. Likewise, the feasibility of embedded implementation is proven through some Hardware-in-the-Loop (HiL) tests.

OriginalsprogEngelsk
Titel2021 12th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2021
Antal sider5
ForlagIEEE Signal Processing Society
Publikationsdato2 feb. 2021
Artikelnummer9405847
ISBN (Trykt)978-1-6654-4772-0
ISBN (Elektronisk)978-1-6654-0366-5
DOI
StatusUdgivet - 2 feb. 2021
Begivenhed12th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2021 - Tabriz, Iran
Varighed: 2 feb. 20214 feb. 2021

Konference

Konference12th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2021
LandIran
ByTabriz
Periode02/02/202104/02/2021
Navn2021 12th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2021

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