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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:

State of health estimation of lithium-ion battery based on improved ant lion optimization and support vector regression
Qianglong Li, Dezhi Li, Kun Zhao, et al.
Journal of Energy Storage (2022) Vol. 50, pp. 104215-104215
Closed Access | Times Cited: 223

Showing 1-25 of 223 citing articles:

A combined state-of-charge estimation method for lithium-ion battery using an improved BGRU network and UKF
Zhenhua Cui, Le Kang, Liwei Li, et al.
Energy (2022) Vol. 259, pp. 124933-124933
Closed Access | Times Cited: 148
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: 148
Data-driven lithium-ion batteries capacity estimation based on deep transfer learning using partial segment of charging/discharging data
Jiachi Yao, Te Han
Energy (2023) Vol. 271, pp. 127033-127033
Closed Access | Times Cited: 144
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: 141
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: 129
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: 129
Perspectives and challenges for future lithium-ion battery control and management
Yujie Wang, Xingchen Zhang, Kaiquan Li, et al.
eTransportation (2023) Vol. 18, pp. 100260-100260
Closed Access | Times Cited: 105
Aging state prediction for supercapacitors based on heuristic kalman filter optimization extreme learning machine
Dezhi Li, Shuo Li, Shubo Zhang, et al.
Energy (2022) Vol. 250, pp. 123773-123773
Closed Access | Times Cited: 99
Data-Driven ICA-Bi-LSTM-Combined Lithium Battery SOH Estimation
Hanlei Sun, Jianrui Sun, Kun Zhao, et al.
Mathematical Problems in Engineering (2022) Vol. 2022, pp. 1-8
Open Access | Times Cited: 97
A data-driven method for extracting aging features to accurately predict the battery health
Rui Xiong, Yue Sun, Chenxu Wang, et al.
Energy storage materials (2023) Vol. 57, pp. 460-470
Closed Access | Times Cited: 92
Temperature prediction of lithium‐ion batteries based on electrochemical impedance spectrum: A review
Dezhi Li, Licheng Wang, Chongxiong Duan, et al.
International Journal of Energy Research (2022) Vol. 46, Iss. 8, pp. 10372-10388
Closed Access | Times Cited: 90
An in-depth study of the electrical characterization of supercapacitors for recent trends in energy storage system
Sambit Satpathy, Neeraj Kumar Misra, Dhirendra kumar Shukla, et al.
Journal of Energy Storage (2022) Vol. 57, pp. 106198-106198
Closed Access | Times Cited: 86
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: 83
State of health estimation of lithium-ion battery with improved radial basis function neural network
Ji Wu, Leichao Fang, Guangzhong Dong, et al.
Energy (2022) Vol. 262, pp. 125380-125380
Closed Access | Times Cited: 82
Hybrid Methods Using Neural Network and Kalman Filter for the State of Charge Estimation of Lithium-Ion Battery
Zhenhua Cui, Jiyong Dai, Jianrui Sun, et al.
Mathematical Problems in Engineering (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 74
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: 70
Convolutional autoencoder-based SOH estimation of lithium-ion batteries using electrochemical impedance spectroscopy
Josue Obregon, Yu-Ri Han, Chang Won Ho, et al.
Journal of Energy Storage (2023) Vol. 60, pp. 106680-106680
Closed Access | Times Cited: 69
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: 64
Battery prognostics and health management from a machine learning perspective
Jingyuan Zhao, Xuning Feng, Quanquan Pang, et al.
Journal of Power Sources (2023) Vol. 581, pp. 233474-233474
Closed Access | Times Cited: 64
State of health estimation for lithium battery random charging process based on CNN-GRU method
Yuxuan Zheng, Jiaxiang Hu, Jianjun Chen, et al.
Energy Reports (2023) Vol. 9, pp. 1-10
Open Access | Times Cited: 43
A review on rapid state of health estimation of lithium-ion batteries in electric vehicles
Zuolu Wang, Xiaoyu Zhao, Lei Fu, et al.
Sustainable Energy Technologies and Assessments (2023) Vol. 60, pp. 103457-103457
Open Access | Times Cited: 42
A review of expert hybrid and co-estimation techniques for SOH and RUL estimation in battery management system with electric vehicle application
Turki Alsuwian, Shaheer Ansari, Muhammad Ammirrul Atiqi Mohd Zainuri, et al.
Expert Systems with Applications (2024) Vol. 246, pp. 123123-123123
Closed Access | Times Cited: 38
Research on the remaining useful life prediction method for lithium-ion batteries by fusion of feature engineering and deep learning
Bo Zhao, Weige Zhang, Yanru Zhang, et al.
Applied Energy (2024) Vol. 358, pp. 122325-122325
Closed Access | Times Cited: 34
Li-ion battery capacity prediction using improved temporal fusion transformer model
William Gomez, Fu‐Kwun Wang, Jia‐Hong Chou
Energy (2024) Vol. 296, pp. 131114-131114
Closed Access | Times Cited: 26
An enhanced real-time human pose estimation method based on modified YOLOv8 framework
Chengang Dong, Guodong Du
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 23
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