Modeling and SOC estimation of lithiumiron phosphate battery consideringcapacity loss

Junhui Li; Fengjie Gao; Gangui Yan; Tianyang Zhang; Jianlin Li

doi:10.1186/s41601-018-0078-0

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Modeling and SOC estimation of lithiumiron phosphate battery consideringcapacity loss

Contents | 更新时间：2026-06-25

- Modeling and SOC estimation of lithiumiron phosphate battery consideringcapacity loss
- Protection and Control of Modern Power Systems Vol. 3, Issue 1, (2018)
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- DOI：10.1186/s41601-018-0078-0
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- Published：2018
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Junhui Li, Fengjie Gao, Gangui Yan, et al. Modeling and SOC estimation of lithiumiron phosphate battery consideringcapacity loss[J]. Protection and Control of Modern Power Systems, 2018, 3(1).
DOI：

Junhui Li, Fengjie Gao, Gangui Yan, et al. Modeling and SOC estimation of lithiumiron phosphate battery consideringcapacity loss[J]. Protection and Control of Modern Power Systems, 2018, 3(1). DOI： 10.1186/s41601-018-0078-0.

摘要

Modeling and state of charge (SOC) estimation of Lithium cells are crucial techniques of the lithium battery management system. The modeling is extremely complicated as the operating status of lithium battery is affected by temperature

current

cycle number

discharge depth and other factors. This paper studies the modeling of lithium iron phosphate battery based on the Thevenin’s equivalent circuit and a method to identify the open circuit voltage

resistance and capacitance in the model is proposed. To improve the accuracy of the lithium battery model

a capacity estimation algorithm considering the capacity loss during the battery’s life cycle. In addition

this paper solves the SOC estimation issue of the lithium battery caused by the uncertain noise using the extended Kalman filtering (EKF) algorithm. A simulation model of actual lithium batteries is designed in Matlab/Simulink and the simulation results verify the accuracy of the model under different operating modes.

Abstract

current

cycle number

discharge depth and other factors. This paper studies the modeling of lithium iron phosphate battery based on the Thevenin’s equivalent circuit and a method to identify the open circuit voltage

resistance and capacitance in the model is proposed. To improve the accuracy of the lithium battery model

a capacity estimation algorithm considering the capacity loss during the battery’s life cycle. In addition

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