The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
An improved feedforward-long short-term memory modeling method for the whole-life-cycle state of charge prediction of lithium-ion batteries considering current-voltage-temperature variation
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Cites
Hu, X., Xu, L., Lin, X., & Pecht, M. (2020) · Joule · doi:10.1016/j.joule.2019.11.018 · Cited by 1,320
Feng, X., Weng, C., He, X., Han, X., Lu, L., Ren, D., & Ouyang, M. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2927120 · Cited by 505
A review on various temperature-indication methods for Li-ion batteries
Raijmakers, L. H. J., Danilov, D. L., Eichel, R.-A., & Notten, P. H. L. (2019) · Applied Energy · doi:10.1016/j.apenergy.2019.02.078 · Cited by 424
Liu, K., Li, Y., Hu, X., Lucu, M., & Widanage, W. D. (2020) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2941747 · Cited by 384
Modified Gaussian Process Regression Models for Cyclic Capacity Prediction of Lithium-Ion Batteries
Liu, K., Hu, X., Wei, Z., Li, Y., & Jiang, Y. (2019) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2019.2944802 · Cited by 358
Xiong, R., Li, L., Li, Z., Yu, Q., & Mu, H. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.03.053 · Cited by 326
Zhu, J., Dewi Darma, M. S., Knapp, M., Sørensen, D. R., Heere, M., Fang, Q., Wang, X., Dai, H., Mereacre, L., Senyshyn, A., et al. (2020) · Journal of Power Sources · doi:10.1016/j.jpowsour.2019.227575 · Cited by 313
Jiang, C., Wang, S., Wu, B., Fernandez, C., Xiong, X., & Coffie-Ken, J. (2021) · Energy · doi:10.1016/j.energy.2020.119603 · Cited by 272
Self-citationTian, J., Xiong, R., & Yu, Q. (2019) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2018.2798606 · Cited by 267
Sun, D., Yu, X., Wang, C., Zhang, C., Huang, R., Zhou, Q., Amietszajew, T., & Bhagat, R. (2021) · Energy · doi:10.1016/j.energy.2020.119025 · Cited by 242
Cited by
Gu, X., See, K. W., Li, P., Shan, K., Wang, Y., Zhao, L., Lim, K. C., & Zhang, N. (2023) · Energy · doi:10.1016/j.energy.2022.125501 · Cited by 373
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
D.V.S.R., S., Badachi, C., & Green II, R. C. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.108420 · Cited by 98
Qian, L., Xuan, L., & Chen, J. (2023) · Frontiers in Energy Research · doi:10.3389/fenrg.2023.1218580 · Cited by 38
“In the literature (Wang et al., 2022b) and (Wang et al.”
BackgroundXue, J., Ma, W., Feng, X., Guo, P., Guo, Y., Hu, X., & Chen, B. (2023) · Energy · doi:10.1016/j.energy.2023.129279 · Cited by 36
Metadata
- Authors
- Wang, S., Takyi-Aninakwa, P., Jin, S., Yu, C., Fernandez, C., & Stroe, D.-I.
- Venue
- Energy
- Publisher
- Elsevier BV
- Published
- 2022-09
- Volume
- 254
- Pages
- 124224
- ISSN
- 0360-5442 (ISSN-L)
- OpenAlex
- W4280503334
- Cited by
- 355
- References
- 57
- FWCI
- 22.17
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: An improved feedforward-long short-term memory modeling method for the whole-life-cycle state of charge prediction of lithium-ion batteries considering current-voltage-temperature variation. https://app.cochat.ai/papers/10.1016/j.energy.2022.124224
- The paper
- Wang, S., Takyi-Aninakwa, P., Jin, S., Yu, C., Fernandez, C., & Stroe, D.-I. (2022). An improved feedforward-long short-term memory modeling method for the whole-life-cycle state of charge prediction of lithium-ion batteries considering current-voltage-temperature variation. Energy. https://doi.org/10.1016/j.energy.2022.124224
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.
