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Symmetric cell approach and impedance spectroscopy of high power lithium-ion batteries
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“the fit is often non-unique and it is questionable whether a purely electrical model can capture the physical, chemical and materials properties and processes of a battery”
From Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning (2020) · cites this paper as [26]
Citations
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Metadata
- Authors
- Chen, C. H., Liu, J., & Amine, K.
- Affiliations
- Argonne National Laboratory (US)
- Corresponding author
- Amine, K
- Venue
- Journal of Power Sources
- Publisher
- Elsevier BV
- Published
- 2001-06
- Volume
- 96
- Issue
- 2
- Pages
- 321-328
- ISSN
- 0378-7753 (ISSN-L)
- OpenAlex
- W2071213755
- Cited by
- 347
- References
- 12
- Citations by year
- 2026: 8 · 2025: 4 · 2024: 9 · 2023: 15 · 2022: 22 · 2021: 14 · 2020: 21 · 2019: 21 · 2018: 30 · 2017: 24 · 2016: 15 · 2015: 23 · 2014: 19 · 2013: 15 · 2012: 19
- FWCI
- 22.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Power Sources (publishedVersion)
- Funders
- U.S. Department of Energy
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Battery Materials and Technologies
- Keywords
- high-power lithium-ion batteries, symmetric cells, cell impedance, impedance spectroscopy, charge transfer resistance, storage aging, mixed ionic-electronic conduction, hybrid electric vehicles, 18650 cells
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