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W4386323732 abstract "Lithium iron phosphate batteries are the most promising energy storage systems for automotive applications thanks to their low cost, good energy density and high safety. However, they exhibit a pronounced hysteresis between charge and discharge voltage curves that significantly complicates the estimation of the battery States of Charge and Health. A state estimation algorithm based on the Unscented Kalman filter is developed in this work to estimate the State of Charge and the resistance State of Health (SoH <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>R</inf> ) of a Lithium-iron-phosphate battery. The hysteresis is modeled by a first-order charge relaxation equation. Moreover, a custom simulation platform is developed to test the estimation algorithm in automotive applications obtaining a State of Charge estimation error lower than 1% and a voltage estimation RMS error of only 1.94 mV when the battery cell is exercised with the UDDS load profile." @default.
W4386323732 created "2023-09-01" @default.
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W4386323732 date "2023-06-19" @default.
W4386323732 modified "2023-09-27" @default.
W4386323732 title "Unscented Kalman Filter based Coestimation of SoC and SoH<sub>R</sub> in Lithium Battery with Hysteresis" @default.
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W4386323732 doi "https://doi.org/10.1109/isie51358.2023.10228166" @default.
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