The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Remaining useful life prediction of lithium-ion battery with unscented particle filter technique
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Citations
Cites
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“Through battery health monitoring, state-of-charge (SOC) and state-of-health (SOH) for batteries could be estimated which provide useful information to the battery management systems (BMSs) [7].”
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Lithium-ion battery life prognostic health management system using particle filtering framework
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Cited by
Data-driven prediction of battery cycle life before capacity degradation
Severson, K. A., Attia, P. M., Jin, N., Perkins, N., Jiang, B., Yang, Z., Chen, M. H., Aykol, M., Herring, P. K., Fraggedakis, D., et al. (2019) · Nature Energy · doi:10.1038/s41560-019-0356-8 · Cited by 3,228
Wang, Y., Tian, J., Sun, Z., Wang, L., Xu, R., Li, M., & Chen, Z. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.110015 · Cited by 1,377
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Self-citation
Metadata
- Authors
- Miao, Q., Xie, L., Cui, H., Liang, W., & Pecht, M.
- Venue
- Microelectronics Reliability
- Publisher
- Elsevier BV
- Published
- 2013-06
- Volume
- 53
- Issue
- 6
- Pages
- 805-810
- ISSN
- 0026-2714 (ISSN-L)
- OpenAlex
- W2085942406
- Cited by
- 481
- References
- 20
- FWCI
- 27.15
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
