SOC estimation of lithium-ion battery at low temperature

Author(s): Wenkang Gao, Shenghui Wang, Xipeng Miao
School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun, 130012, China
International Journal of Smart Grid and Clean Energy, vol. 11, no. 4, October 2022: pp. 135-140
ISSN: 2315-4462 (Print)
ISSN: 2373-3594 (Online)
Digital Object Identifier: 10.12720/sgce.11.4.135-140
Abstract: The evolution of interfacial compatibility, stability of electronic impedance, ion migration mechanisms at grain boundaries and molecular dynamics properties within lithium-ion batteries under low-temperature conditions greatly challenges the prediction of the state of charge. In the present study, considering that the lithium-ion battery is susceptible to the operating temperature environment, an improved second-order RC equivalent circuit model is developed, and the parameters of the temperature model are identified by the least squares method to verify the accuracy of the model parameters. The extended Kalman filter algorithm is used to estimate the SOC value. The improved model and algorithm have high accuracy in a low-temperature environment, which is a method for battery SOC prediction under low-temperature conditions of lithium-ion batteries and an effective guarantee for stable operation and safe use of lithium-ion batteries at low temperatures.

Keywords: Lithium-ion battery, SOC, Extended Kalman filter, low temperature
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