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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

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Showing 1-25 of 30 citing articles:

State of health and remaining useful life prediction of lithium-ion batteries based on a disturbance-free incremental capacity and differential voltage analysis method
Fei Xia, Kangan Wang, Jiajun Chen
Journal of Energy Storage (2023) Vol. 64, pp. 107161-107161
Closed Access | Times Cited: 68
Machine learning enables rapid state of health estimation of each cell within battery pack
Quanqing Yu, Yuwei Nie, Shanshan Guo, et al.
Applied Energy (2024) Vol. 375, pp. 124165-124165
Closed Access | Times Cited: 16
A hybrid method for prognostics of lithium-ion batteries capacity considering regeneration phenomena
Huixing Meng, Mengyao Geng, Jinduo Xing, et al.
Energy (2022) Vol. 261, pp. 125278-125278
Closed Access | Times Cited: 58
An intelligent fault diagnosis method for lithium-ion battery pack based on empirical mode decomposition and convolutional neural network
Lei Yao, Jie Zheng, Yanqiu Xiao, et al.
Journal of Energy Storage (2023) Vol. 72, pp. 108181-108181
Closed Access | Times Cited: 25
Online two-dimensional filter for anti-interference aging features extraction to accurately predict the battery health
Fei Xia, Chao Tang, Jiajun Chen
Measurement (2024) Vol. 234, pp. 114758-114758
Closed Access | Times Cited: 9
SOH and RUL prediction of lithium batteries based on fusions of RLOESS filtered electrochemical and thermal features by bidirectional gated recurrent unit network
Fei Xia, Yun Yu, Jiajun Chen
Journal of Energy Storage (2024) Vol. 102, pp. 114134-114134
Closed Access | Times Cited: 8
Remaining useful life prediction for lithium-ion batteries with an improved grey particle filter model
Zhicun Xu, Naiming Xie, Kailing Li
Journal of Energy Storage (2023) Vol. 78, pp. 110081-110081
Closed Access | Times Cited: 17
An improved dung beetle optimizer- hybrid kernel least square support vector regression algorithm for state of health estimation of lithium-ion batteries based on variational model decomposition
Tao Zhu, Shunli Wang, Yongcun Fan, et al.
Energy (2024) Vol. 306, pp. 132464-132464
Closed Access | Times Cited: 8
Estimating the state of health of lithium-ion batteries based on a probability density function
Zhicheng Lin, Yongxiang Cai, Wei Liu, et al.
International Journal of Electrochemical Science (2023) Vol. 18, Iss. 6, pp. 100137-100137
Open Access | Times Cited: 15
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
M. S. Reza, M. A. Hannan, Muhamad Mansor, et al.
Journal of Energy Storage (2024) Vol. 98, pp. 113056-113056
Closed Access | Times Cited: 4
A multi-strategy attention regression network for joint prediction of state of health and remaining useful life of lithium-ion batteries using only charging data
Weiguo Feng, Z. T. Sun, Y. L. Han, et al.
Journal of Power Sources (2025) Vol. 636, pp. 236507-236507
Closed Access
Prediction of the Remaining Useful Life of Lithium–Ion Batteries Based on Mode Decomposition and ED-LSTM
Bowen Song, Guangzhao Yue, Dong Guo, et al.
Batteries (2025) Vol. 11, Iss. 3, pp. 86-86
Open Access
State of health and remaining useful life estimation of lithium-ion battery based on parallel deep learning methods
Sichen Zhu, Chaoran Li, Ping Ping Ruan, et al.
International Journal of Electrochemical Science (2025), pp. 100988-100988
Open Access
RUL-Mamba: Mamba-based remaining useful life prediction for lithium-ion batteries
Jiahui Huang, Lei Liu, Hongwei Zhao, et al.
Journal of Energy Storage (2025) Vol. 120, pp. 116376-116376
Closed Access
Capacity estimation of lithium-ion battery with multi-task autoencoder and empirical mode decomposition
Q. Q. Sun, Fangshu Cui, Mingrui Shi
Measurement (2024) Vol. 236, pp. 115146-115146
Closed Access | Times Cited: 2
An efficient state-of-health estimation method for lithium-ion batteries based on feature-importance ranking strategy and hybrid kernel extreme learning machine algorithm
Songhao Yang, Hongwu Qin, Zhenqi Liu, et al.
Journal of Energy Storage (2024) Vol. 103, pp. 114260-114260
Closed Access | Times Cited: 2
Selecting Suitable Battery Technologies for Untethered Robot
Tom Verstraten, Md Sazzad Hosen, Maitane Berecibar, et al.
Energies (2023) Vol. 16, Iss. 13, pp. 4904-4904
Open Access | Times Cited: 6
Lithium-ion battery health state estimation based on feature reconstruction and optimized least squares support vector machine
Tiezhou Wu, Jian Kang, Junchao Zhu, et al.
Journal of Electrochemical Energy Conversion and Storage (2024) Vol. 22, Iss. 1
Closed Access | Times Cited: 1
Battery state of health estimation using an AutoGluon-tabular model incorporating uncertainty quantification
Xiaoyuan Zhang, Mengnan Liu, Yingying Liu
Journal of Energy Storage (2024) Vol. 101, pp. 113920-113920
Closed Access | Times Cited: 1
A remaining useful life estimation method based on long short-term memory and federated learning for electric vehicles in smart cities
Xuejiao Chen, Zhaonan Chen, Mu Zhang, et al.
PeerJ Computer Science (2023) Vol. 9, pp. e1652-e1652
Open Access | Times Cited: 3
New energy electric vehicle battery health state prediction based on vibration signal characterization and clustering
Liping Lu, Huiying Zhai, Yun Gao
Heliyon (2023) Vol. 10, Iss. 1, pp. e23420-e23420
Open Access | Times Cited: 3
Battery state of health estimation using variable separation algorithm based on quasi-Newton
Cheng Wang, Jing Chen, Lianyuan Cheng, et al.
Ionics (2024) Vol. 30, Iss. 8, pp. 4617-4629
Closed Access
Strong robust state of health estimation of lithium-ion batteries based on aging feature mechanism analysis and improved mixed kernel least squares support vector regression model
Renjun Feng, Shunli Wang, Chunmei Yu, et al.
Ionics (2024)
Closed Access
A unified GPR model based on transfer learning for SOH prediction of lithium-ion batteries
Li Cai
Journal of Process Control (2024) Vol. 144, pp. 103337-103337
Closed Access
Robust estimation of lithium-ion battery state of health based on electro-thermal features and machine learning
Kui Chen, Yang Luo, Zhou Long, et al.
Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy (2024)
Closed Access
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