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State‐of‐charge estimation with aging effect and correction for lithium‐ion battery
Abstract
This study proposes Lithium‐ion battery aging correction state‐of‐charge (SOC) estimation techniques. Although the battery is aging, the SOC error estimation system maintains the setting range using a low‐cost 8 bit micro‐controller. The proposed method can track and correct the open‐circuit voltage against capacity in the battery management system by comparing the capacity error with the coulomb counting and look‐up table methods. The experimental results verify that the SOC estimation error is still lower than 3.5% after 1000 cycles. The SOC estimation verification platform verifies the Sanyo UR18650 W lithium battery. After 300 accelerated aging cycle charge–discharge tests, the test results showed that the SOC prediction precision for an aged battery is as high as 2.67%.
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“Additionally, as batteries age and their characteristics evolve, the modeling performance for SOC estimation may decline[26], highlighting the need for adaptive models.”
From Advancements in the estimation of the state of charge of lithium-ion battery: a comprehensive review of traditional and deep learning approaches (2025) · cites this paper as [26]
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References 14 · Cited by 53
Research works printed but not linked: 4
- Lee Y.S., 2002, Lithium ion battery model and fuzzy neural approach for estimating battery state‐of‐charge, 1789
- Li I.H., 2007, A merged fuzzy neural network and its application in battery state‐of‐charge estimation, IEEE Trans., 22, 697
- Li I.H., 2005, A novel learning structure of fuzzy neural networks using reduced‐form genetic algorithms, 219
- Ranjbar A.H., 2012, Online estimation of state of charge in lithium‐ion batteries using impulse response concept, IEEE Trans., 3, 360
Metadata
- Authors
- Cheng, M., Lee, Y., Liu, M., & Sun, C.
- Affiliations
- Fu Jen Catholic University (TW)
- Industrial Technology Research Institute (TW)
- Corresponding author
- Lee, Yuang‐Shung
- ORCID
- Liu, Min
- Venue
- IET Electrical Systems in Transportation
- Published
- 2015-06
- Volume
- 5
- Issue
- 2
- Pages
- 70-76
- ISSN
- 2042-9738 (ISSN-L)
- OpenAlex
- W1992439863
- Cited by
- 53
- References
- 14
- Citations by year
- 2026: 5 · 2025: 3 · 2024: 2 · 2023: 3 · 2022: 7 · 2021: 11 · 2019: 4 · 2018: 6 · 2017: 8 · 2016: 4
- FWCI
- 4.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IET Electrical Systems in Transportation (publishedVersion)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Keywords
- state of charge estimation, lithium-ion battery aging, Coulomb counting, look-up table, battery management systems, accelerated aging, low-cost microcontroller
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- CoChat. (2026). Citation check: State‐of‐charge estimation with aging effect and correction for lithium‐ion battery. https://app.cochat.ai/papers/10.1049/iet-est.2013.0007
- The paper
- Cheng, M., Lee, Y., Liu, M., & Sun, C. (2015). State‐of‐charge estimation with aging effect and correction for lithium‐ion battery. IET Electrical Systems in Transportation. https://doi.org/10.1049/iet-est.2013.0007