Model Development for State-of-Power Estimation of Large-Capacity Nickel-Manganese-Cobalt Oxide-Based Lithium-Ion Cell Validated Using a Real-Life Profile

Abraham Alem Kebede (), Md Sazzad Hosen, Theodoros Kalogiannis, Henok Ayele Behabtu, Towfik Jemal, Joeri Van Mierlo, Thierry Coosemans and Maitane Berecibar
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Abraham Alem Kebede: Mobility, Logistics and Automotive Technology Research Center, Vrije Universiteit Brussels, Pleinlaan 2, 1050 Brussels, Belgium
Md Sazzad Hosen: Mobility, Logistics and Automotive Technology Research Center, Vrije Universiteit Brussels, Pleinlaan 2, 1050 Brussels, Belgium
Theodoros Kalogiannis: Mobility, Logistics and Automotive Technology Research Center, Vrije Universiteit Brussels, Pleinlaan 2, 1050 Brussels, Belgium
Henok Ayele Behabtu: Mobility, Logistics and Automotive Technology Research Center, Vrije Universiteit Brussels, Pleinlaan 2, 1050 Brussels, Belgium
Towfik Jemal: Faculty of Electrical and Computer Engineering, Jimma Institute of Technology, Jimma University, Jimma 378, Ethiopia
Joeri Van Mierlo: Mobility, Logistics and Automotive Technology Research Center, Vrije Universiteit Brussels, Pleinlaan 2, 1050 Brussels, Belgium
Thierry Coosemans: Mobility, Logistics and Automotive Technology Research Center, Vrije Universiteit Brussels, Pleinlaan 2, 1050 Brussels, Belgium
Maitane Berecibar: Mobility, Logistics and Automotive Technology Research Center, Vrije Universiteit Brussels, Pleinlaan 2, 1050 Brussels, Belgium

Energies, 2022, vol. 15, issue 18, 1-15

Abstract: This paper investigates the model development of the state-of-power (SoP) estimation for a 43 Ah large-capacity prismatic nickel-manganese-cobalt oxide (NMC) based lithium-ion cell with a thorough aging investigation of the cells’ internal resistance increase. For a safe operation of the vehicle system, a battery management system (BMS) integrated with SoP estimation functions is crucial. In this study, the developed SoP model used for the estimation of power throughout the lifetime of the cell is coupled with a dual-polarization equivalent-circuit model (DP_ECM) for achieving the precise estimation of desired parameters. The SoP model is developed based on the pulse-trained internal resistance evolution approach, and hence the power is estimated by determining the rate of internal resistance increase. Hybrid pulse power characterization (HPPC) test results are used for extraction of the impedance parameters. In the DP_ECM, Coulomb counting and extended Kalman filter (EKF) state estimation methods are developed for the accurate estimation of the state of charge (SoC) of the cell. The SoP model validation is performed by using both dynamic Worldwide harmonized Light vehicles Test Cycles (WLTC) and static current profiles, achieving promising results with root-mean-square errors (RMSE) of 2% and 1%, respectively.

Keywords: state of power; state of charge; internal resistance increase; battery management system; aging; validation profiles (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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