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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.

Requested Article:

A method for estimating the aging state of lithium‐ion batteries based on a multi‐linear integrated model
Hanlei Sun, Dongfang Yang, Licheng Wang, et al.
International Journal of Energy Research (2022) Vol. 46, Iss. 15, pp. 24091-24104
Closed Access | Times Cited: 60

Showing 1-25 of 60 citing articles:

Electrochemical Impedance Spectroscopy: A New Chapter in the Fast and Accurate Estimation of the State of Health for Lithium-Ion Batteries
Ming Zhang, Yanshuo Liu, Dezhi Li, et al.
Energies (2023) Vol. 16, Iss. 4, pp. 1599-1599
Open Access | Times Cited: 142
Online estimation of SOH for lithium-ion battery based on SSA-Elman neural network
Yu Guo, Dongfang Yang, Yang Zhang, et al.
Protection and Control of Modern Power Systems (2022) Vol. 7, Iss. 1
Open Access | Times Cited: 136
A Review of SOH Prediction of Li-Ion Batteries Based on Data-Driven Algorithms
Ming Zhang, Dongfang Yang, Jiaxuan Du, et al.
Energies (2023) Vol. 16, Iss. 7, pp. 3167-3167
Open Access | Times Cited: 130
Electrochemical Impedance Spectroscopy Based on the State of Health Estimation for Lithium-Ion Batteries
Dezhi Li, Dongfang Yang, Liwei Li, et al.
Energies (2022) Vol. 15, Iss. 18, pp. 6665-6665
Open Access | Times Cited: 125
A hybrid neural network model with improved input for state of charge estimation of lithium-ion battery at low temperatures
Zhenhua Cui, Le Kang, Liwei Li, et al.
Renewable Energy (2022) Vol. 198, pp. 1328-1340
Closed Access | Times Cited: 124
Sensing as the key to the safety and sustainability of new energy storage devices
Zhenxiao Yi, Zhaoliang Chen, Kai Yin, et al.
Protection and Control of Modern Power Systems (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 111
Developments and Applications of Artificial Intelligence in Music Education
Xiaofei Yu, Ning Ma, Lei Zheng, et al.
Technologies (2023) Vol. 11, Iss. 2, pp. 42-42
Open Access | Times Cited: 79
Prediction of the Remaining Useful Life of Supercapacitors at Different Temperatures Based on Improved Long Short-Term Memory
Ning Ma, Huaixian Yin, Kai Wang
Energies (2023) Vol. 16, Iss. 14, pp. 5240-5240
Open Access | Times Cited: 77
State of health estimation of lithium-ion batteries based on Mixers-bidirectional temporal convolutional neural network
Jingyi Gao, Dongfang Yang, Shi Wang, et al.
Journal of Energy Storage (2023) Vol. 73, pp. 109248-109248
Closed Access | Times Cited: 77
Self-Powered Electronic Skin for Remote Human–Machine Synchronization
Ming Zhang, Wanli Wang, Guoting Xia, et al.
ACS Applied Electronic Materials (2023) Vol. 5, Iss. 1, pp. 498-508
Closed Access | Times Cited: 75
Application of Nanogenerators in the Field of Acoustics
Xiaofei Yu, Yuchao Shang, Lei Zheng, et al.
ACS Applied Electronic Materials (2023) Vol. 5, Iss. 9, pp. 5240-5248
Closed Access | Times Cited: 70
Summary of Health-State Estimation of Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy
Xinwei Sun, Yang Zhang, Yongcheng Zhang, et al.
Energies (2023) Vol. 16, Iss. 15, pp. 5682-5682
Open Access | Times Cited: 65
Triboelectric nanogenerators: the beginning of blue dream
Wanli Wang, Dongfang Yang, Xiaoran Yan, et al.
Frontiers of Chemical Science and Engineering (2023) Vol. 17, Iss. 6, pp. 635-678
Closed Access | Times Cited: 61
Application of nanogenerators in acoustics based on artificial intelligence and machine learning
Xiaofei Yu, Tengtian Ai, Kai Wang
APL Materials (2024) Vol. 12, Iss. 2
Open Access | Times Cited: 59
Revealing the degradation patterns of lithium-ion batteries from impedance spectroscopy using variational auto-encoders
Yanshuo Liu, Qiang Li, Kai Wang
Energy storage materials (2024) Vol. 69, pp. 103394-103394
Closed Access | Times Cited: 58
State of health estimation of lithium-ion batteries based on modified flower pollination algorithm-temporal convolutional network
Hao Zhang, Jingyi Gao, Le Kang, et al.
Energy (2023) Vol. 283, pp. 128742-128742
Closed Access | Times Cited: 48
Prediction of Health Level of Multiform Lithium Sulfur Batteries Based on Incremental Capacity Analysis and an Improved LSTM
Hao Zhang, Hanlei Sun, Le Kang, et al.
Protection and Control of Modern Power Systems (2024) Vol. 9, Iss. 2, pp. 21-31
Open Access | Times Cited: 24
Application of triboelectric nanogenerator in self-powered motion detection devices: A review
Hongyuan Jiang, Xin Lv, Kai Wang
APL Materials (2024) Vol. 12, Iss. 7
Open Access | Times Cited: 22
A novel hybrid deep learning model for accurate state of charge estimation of Li-Ion batteries for electric vehicles under high and low temperature
Muhammad Hamza Zafar, Noman Mujeeb Khan, Mohamad Abou Houran, et al.
Energy (2024) Vol. 292, pp. 130584-130584
Open Access | Times Cited: 21
Progress in estimating the state of health using transfer learning–based electrochemical impedance spectroscopy of lithium-ion batteries
Guangheng Qi, Guangwen Du, Kai Wang
Ionics (2025) Vol. 31, Iss. 3, pp. 2337-2349
Closed Access | Times Cited: 1
A state‐of‐health estimation method considering capacity recovery of lithium batteries
Yu Guo, Peng Yu, Chao Zhu, et al.
International Journal of Energy Research (2022) Vol. 46, Iss. 15, pp. 23730-23745
Closed Access | Times Cited: 66
Electrodeless Nanogenerator for Dust Recover
Wanli Wang, Dongfang Yang, Zhenxing Huang, et al.
Energy Technology (2022) Vol. 10, Iss. 12
Closed Access | Times Cited: 57
Zinc doping effect on the structural and electrochemical properties of LaCoO3 perovskite as a material for hybrid supercapacitor electrodes
Fawzi Hadji, Mahmoud Omari, M. Mebarki, et al.
Journal of Alloys and Compounds (2023) Vol. 942, pp. 169047-169047
Closed Access | Times Cited: 35
A novel state of health prediction method for battery system in real-world vehicles based on gated recurrent unit neural networks
Jichao Hong, Kerui Li, Fengwei Liang, et al.
Energy (2023) Vol. 289, pp. 129918-129918
Closed Access | Times Cited: 30
Aging mechanisms, prognostics and management for lithium-ion batteries: Recent advances
Yujie Wang, Haoxiang Xiang, Yin‐Yi Soo, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 207, pp. 114915-114915
Closed Access | Times Cited: 12
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