The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
On the use of electrochemical impedance spectroscopy to characterize and model the aging phenomena of lithium-ion batteries: a critical review
Open accessAbstract
Electrochemical Impedance Spectroscopy (EIS) is a powerful non-invasive technique used to characterize Lithium-ion cells. Its application allows to identify and track the evolutions of cell degradation processes within a short testing time. This review collects all the available works which have used EIS spectra either to characterize Li-ion cell degradation or to develop Electric Circuit Models (ECMs). The objectives of this work are: (i) to highlight the influence of different aging test conditions on the EIS spectra; (ii) to find the correlations between EIS spectra variations and the underlying degradation mechanisms and (iii) to list the available options to formulate ECMs from EIS spectra of aged cells. After an exhaustive analysis of the state-of-the-art, a critical review is presented to discuss the existing links between degradation mechanisms and the most reliable solutions to model them.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Ageing mechanisms in lithium-ion batteries
Vetter, J., Novák, P., Wagner, M. R., Veit, C., Möller, K.-C., Besenhard, J. O., Winter, M., Wohlfahrt-Mehrens, M., Vogler, C., & Hammouche, A. (2005) · Journal of Power Sources · doi:10.1016/j.jpowsour.2005.01.006 · Cited by 3,987
Degradation diagnostics for lithium ion cells
Birkl, C. R., Roberts, M. R., McTurk, E., Bruce, P. G., & Howey, D. A. (2017) · Journal of Power Sources · doi:10.1016/j.jpowsour.2016.12.011 · Cited by 1,945
Critical review of state of health estimation methods of Li-ion batteries for real applications
Berecibar, M., Gandiaga, I., Villarreal, I., Omar, N., Van Mierlo, J., & Van den Bossche, P. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.11.042 · Cited by 1,126
Synthesize battery degradation modes via a diagnostic and prognostic model
Dubarry, M., Truchot, C., & Liaw, B. Y. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.07.016 · Cited by 1,065
Waag, W., Käbitz, S., & Sauer, D. U. (2013) · Applied Energy · doi:10.1016/j.apenergy.2012.09.030 · Cited by 987
Characterizing aging effects of lithium ion batteries by impedance spectroscopy
Tröltzsch, U., Kanoun, O., & Tränkler, H.-R. (2006) · Electrochimica Acta · doi:10.1016/j.electacta.2005.02.148 · Cited by 427
Galeotti, M., Cinà, L., Giammanco, C., Cordiner, S., & Di Carlo, A. (2015) · Energy · doi:10.1016/j.energy.2015.05.148 · Cited by 412
Cited by
Hu, W., Peng, Y., Wei, Y., & Yang, Y. (2023) · The Journal of Physical Chemistry C · doi:10.1021/acs.jpcc.3c00033 · Cited by 429
Liu, Y., Wang, L., Li, D., & Wang, K. (2023) · Protection and Control of Modern Power Systems · doi:10.1186/s41601-023-00314-w · Cited by 279
Zhao, W., Zhao, C., Wu, H., Li, L., & Zhang, C. (2024) · Journal of Energy Storage · doi:10.1016/j.est.2023.110409 · Cited by 265
Physics-Based Battery Model Parametrisation from Impedance Data
Hallemans, N., Courtier, N. E., Please, C. P., Planden, B., Dhoot, R., Timms, R., Chapman, S. J., Howey, D., & Duncan, S. R. (2025) · Journal of The Electrochemical Society · doi:10.1149/1945-7111/add41b · Cited by 34
Xing, Q., Sun, X., Fu, Y., & Wang, K. (2025) · Ionics · doi:10.1007/s11581-024-05982-8 · Cited by 20
Metadata
- Authors
- Iurilli, P., Brivio, C., & Wood, V.
- Venue
- Journal of Power Sources
- Publisher
- Elsevier BV
- Published
- 2021-09
- Volume
- 505
- Pages
- 229860
- ISSN
- 0378-7753 (ISSN-L)
- OpenAlex
- W3170241467
- Cited by
- 405
- References
- 7
- FWCI
- 15.71
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: On the use of electrochemical impedance spectroscopy to characterize and model the aging phenomena of lithium-ion batteries: a critical review. https://app.cochat.ai/papers/10.1016/j.jpowsour.2021.229860
- The paper
- Iurilli, P., Brivio, C., & Wood, V. (2021). On the use of electrochemical impedance spectroscopy to characterize and model the aging phenomena of lithium-ion batteries: a critical review. Journal of Power Sources. https://doi.org/10.1016/j.jpowsour.2021.229860
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
