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Thuy Nguyen Vinh
Thai Nguyen University of Technology
Computer Science & IT Electrical & Electronics Engineering

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State of charge estimation for lithium-ion batteries connected in series using two sigma point Kalman filters Chi Nguyen Van; Thuy Nguyen Vinh
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1334-1349

Abstract

This paper proposes a method to estimate state of charge (SoC) for Lithium-ion battery pack (LIB) with ???? series-connected cells. The cell’s model is represented by a second-order equivalent circuit model taking into account the measurement disturbances and the current sensor bias. By using two sigma point Kalman filters (SPKF), the SoC of cells in the pack is calculated by the sum of the pack’s average SoC estimated by the first SPKF and SoC differences estimated by the second SPKF. The advantage of this method is the SoC estimation algorithm performed only two times instead of ???? times in each sampling time interval, so the computational burden is reduced. The test of the proposed SoC estimation algorithm for 7 samsung ICR18650 Lithium-ion battery cells connected in series is implemented in the continuous charge and discharge scenario in one hour time. The estimated SoCs of the cells in the pack are quite accurate, the 3-sigma criterion of estimated SoC error distributions is 0.5%.
Co-Authors Chi Nguyen Van