The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve
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Integrity signals
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Cites
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Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“However, those models are all developed with the charging and discharging curve as input.”
From Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning (2020) · cites this paper as [34]
In the citing paper
“Although GPR has been used in the literature in the context of Li-ion batteries17,33,34, we depart from those pioneering works by employing impedance spectra as input, as well employing ARD to shed light on salient frequencies.”
From Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning (2020) · cites this paper as [34]
In the citing paper
“Processed external features are normally extracted from differential charging curves under constant current rate, such as IC/DV curves [77,78] and voltage gradient curves (dV/dt) [79,80].”
From Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019) · cites this paper as [80]
Citations
Cites
Gaussian Processes for Regression
Williams, C. K. I., & Rasmussen, C. E. (1995) · Aston Publications Explorer (Aston University) · Cited by 1,121
Prognostics methods for battery health monitoring using a bayesian framework
Saha, B., Goebel, K., Poll, S., & Christophersen, J. (2009) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2008.2005965 · Cited by 831
Gaussian process regression for forecasting battery state of health
Richardson, R. R., Osborne, M. A., & Howey, D. A. (2017) · Journal of Power Sources · doi:10.1016/j.jpowsour.2017.05.004 · Cited by 732
Nuhic, A., Terzimehic, T., Soczka-Guth, T., Buchholz, M., & Dietmayer, K. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.11.146 · Cited by 664
Hu, C. K., Youn, B. D., & Chung, J. (2011) · Applied Energy · doi:10.1016/j.apenergy.2011.08.002 · Cited by 561
Weng, C., Cui, Y., Sun, J., & Peng, H. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.02.012 · Cited by 561
Wu, J., Zhang, C., & Chen, Z. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.04.057 · Cited by 531
Self-citationTosun, N. (2005) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-004-2386-y · Cited by 471
Eddahech, A., Briat, O., Bertrand, N., Delétage, J.-Y., & Vinassa, J.-M. (2012) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2012.04.050 · Cited by 462
Liu, D., Pang, J., Zhou, J., Peng, Y., & Pecht, M. (2013) · Microelectronics Reliability · doi:10.1016/j.microrel.2013.03.010 · Cited by 443
Research works printed but not linked: 1
- Cheng, 2015, Residual lifetime prediction for lithium-ion battery based on functional principal component analysis and Bayesian approach, Energy, 90, 1983, 10.1016/j.energy.2015.07.022 · DOI
Cited by
Sorted by citations
Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review
Li, Y., Liu, K., Foley, A. M., Zülke, A., Berecibar, M., Nanini-Maury, E., Van Mierlo, J., & Hoster, H. E. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.109254 · Cited by 1,193
“Processed external features are normally extracted from differential charging curves under constant current rate, such as IC/DV curves [77,78] and voltage gradient curves (dV/dt) [79,80].”
BackgroundZhang, Y., Tang, Q., Zhang, Y., Wang, J., Stimming, U., & Lee, A. A. (2020) · Nature Communications · doi:10.1038/s41467-020-15235-7 · Cited by 889
“We use a zero mean function and a linear (LIN) covariance function Although GPR has been used in the literature in the context of Li-ion batteries 17,33,34 , we depart from those pioneering works by employing impedance spectra as input, as well employing ARD to shed light on salient frequencies.”
MethodLiu, K., Shang, Y., Ouyang, Q., & Widanage, W. D. (2020) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2020.2973876 · Cited by 838
Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation
Zhu, J., Wang, Y., Huang, Y., Gopaluni, R. B., Cao, Y., Heere, M., Mühlbauer, M. J., Mereacre, L., Dai, H., Liu, X., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29837-w · Cited by 835
Self-citationRandom forest regression for online capacity estimation of lithium-ion batteries
Li, Y., Zou, C., Berecibar, M., Nanini-Maury, E., Chan, J. C.-W., van den Bossche, P., Van Mierlo, J., & Omar, N. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.09.182 · Cited by 727
Metadata
- Authors
- Yang, D., Zhang, X., Pan, R., Wang, Y., & Chen, Z.
- Affiliations
- University of Science and Technology of China (CN)
- Corresponding author
- Chen, Zonghai
- Venue
- Journal of Power Sources
- Publisher
- Elsevier BV
- Published
- 2018-04
- Volume
- 384
- Pages
- 387-395
- ISSN
- 0378-7753 (ISSN-L)
- OpenAlex
- W2793702125
- Cited by
- 765
- References
- 33
- Citations by year
- 2026: 65 · 2025: 101 · 2024: 124 · 2023: 144 · 2022: 116 · 2021: 98 · 2020: 71 · 2019: 35 · 2018: 11
- FWCI
- 28.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Power Sources (publishedVersion)
- Funders
- National Natural Science Fund of China (61375079)
- CPSF-CAS Joint Foundation for Excellent Postdoctoral Fellow (2017LH007)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Keywords
- state of health estimation, lithium-ion batteries, Gaussian process regression, charging curves, battery degradation, grey relational analysis
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.
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