Modeling and SOC estimation of lithium iron phosphate battery considering capacity loss
Open accessAbstract
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.
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When the SOC is 90-100%, the sensitivity of DC internal resistance is the largest.
“When the SOC is 90-100%, the sensitivity of DC internal resistance is the largest [29].”
From The Influence of Temperature on the Capacity of Lithium Ion Batteries with Different Anodes (2021) · cites this paper as [29]
Section 3.1 says that SOC affects the battery model’s resistance parameters and describes estimating resistance at different SOCs. It does not say that DC internal resistance is most sensitive at 90–100% SOC. Searches for that range and for resistance sensitivity found no passage establishing the claimed ranking; page numbers were not available in our copy. (LLM, conf=0.74)
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Research works printed but not linked: 17
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Cited by
Sorted by citations
The Influence of Temperature on the Capacity of Lithium Ion Batteries with Different Anodes
Lv, S., Wang, X., Lu, W., Zhang, J., & Ni, H. (2021) · Energies · doi:10.3390/en15010060 · Cited by 99 · see citing works
- Authors
- Li, J., Gao, F., Yan, G., Zhang, T., & Li, J.
- Affiliations
- Northeast Electric Power University (CN)
- State Grid Shandong Electric Power Company (China) (CN)
- Corresponding author
- Li, Junhui
- Venue
- Protection and Control of Modern Power Systems
- Published
- 2018-02-27
- Volume
- 3
- Issue
- 1
- ISSN
- 2367-0983 (ISSN-L)
- 2367-2617
- OpenAlex
- W2798194826
- Cited by
- 29
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 2 · 2022: 4 · 2021: 8 · 2020: 5 · 2019: 4 · 2018: 2
- FWCI
- 2.52
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Protection and Control of Modern Power Systems (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Industrial Innovation of Jilin Province Development and Reform Commission (2017C017-2)
- Jilin Provincial ‘13th Five-Year Plan’ Science and Technology Project ([2016]88)
- Open Fund of State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems (DGB51201700424)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Keywords
- lithium iron phosphate batteries, state of charge estimation, battery modeling, Thevenin equivalent circuit, capacity fade, battery management systems, extended Kalman filter, parameter estimation
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