Butler-Volmer equation-based model and its implementation on state of power prediction of high-power lithium titanate batteries considering temperature effects
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SOC represents the capacity state rather than the energy state, so it is no longer sufficient to describe battery behavior in ESS applications where residual energy rather than residual capacity is essential.
“However, since SOC represents the capacity state instead of the energy state, it is no longer sufficient to describe the battery behavior in the ESS applications where the residual energy rather than the residual capacity of batteries is essential [4].”
From A Practical Lithium-Ion Battery Model for State of Energy and Voltage Responses Prediction Incorporating Temperature and Ageing Effects (2018) · cites this paper as [4]
At the same SOC, SOE varies because discharging energy efficiency depends on battery operating conditions.
“At the same SOC, SOE varied on account of that the discharging energy efficiency was dependent on the battery operating conditions.”
From A Practical Lithium-Ion Battery Model for State of Energy and Voltage Responses Prediction Incorporating Temperature and Ageing Effects (2018) · cites this paper as [4]
Neural-network-based SOE prediction methods' estimation exactness highly depended on the training data provided, and their systematic complexity needed to be decreased to reduce hardware costs.
“In [4,14], neural networks were used to predict the battery SOE variation, but the estimat ion exactness highly depended on the training data provided and the systematic co mplexity needed to be decreased to reduce the hardware costs.”
From A Practical Lithium-Ion Battery Model for State of Energy and Voltage Responses Prediction Incorporating Temperature and Ageing Effects (2018) · cites this paper as [4]
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- Authors
- Jiang, J., Liu, S., Ma, Z., Wang, L. Y., & Wu, K.
- Affiliations
- Beijing Jiaotong University (CN)
- Wayne State University (US)
- CITIC Group (China) (CN)
- Corresponding author
- Liu, Sijia
- Venue
- Energy
- Publisher
- Elsevier BV
- Published
- 2016-12
- Volume
- 117
- Pages
- 58-72
- ISSN
- 0360-5442 (ISSN-L)
- OpenAlex
- W2543815595
- Cited by
- 47
- References
- 27
- Citations by year
- 2026: 5 · 2025: 1 · 2024: 5 · 2023: 4 · 2022: 11 · 2021: 5 · 2020: 5 · 2019: 3 · 2018: 4 · 2017: 4
- FWCI
- 3.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Energy (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Natural Science Foundation of China (51477009)
- Fundamental Research Funds for the Central Universities (E16JB00060)
- 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
- Butler-Volmer equation, lithium titanate batteries, high-power batteries, temperature effects, state of charge, complex method, terminal voltage estimation, battery state estimation, robustness analysis
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