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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:

Online diagnosis of state of health for lithium-ion batteries based on short-term charging profiles
Xing Shu, Guang Li, Yuanjian Zhang, et al.
Journal of Power Sources (2020) Vol. 471, pp. 228478-228478
Open Access | Times Cited: 91

Showing 1-25 of 91 citing articles:

A review on online state of charge and state of health estimation for lithium-ion batteries in electric vehicles
Zuolu Wang, Guojin Feng, Dong Zhen, et al.
Energy Reports (2021) Vol. 7, pp. 5141-5161
Open Access | Times Cited: 294
A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery
Xin Sui, Shan He, Søren Byg Vilsen, et al.
Applied Energy (2021) Vol. 300, pp. 117346-117346
Open Access | Times Cited: 276
State of Charge Estimation of Lithium-Ion Battery for Electric Vehicles Using Machine Learning Algorithms
Chandran Venkatesan, Chandrashekhar K. Patil, Alagar Karthick, et al.
World Electric Vehicle Journal (2021) Vol. 12, Iss. 1, pp. 38-38
Open Access | Times Cited: 239
Artificial Neural Networks, Gradient Boosting and Support Vector Machines for electric vehicle battery state estimation: A review
Aaruththiran Manoharan, Mumtaj Begam, Vimal Rau Aparow, et al.
Journal of Energy Storage (2022) Vol. 55, pp. 105384-105384
Closed Access | Times Cited: 188
Battery health estimation with degradation pattern recognition and transfer learning
Zhongwei Deng, Xianke Lin, Jianwei Cai, et al.
Journal of Power Sources (2022) Vol. 525, pp. 231027-231027
Closed Access | Times Cited: 184
A novel method for state of health estimation of lithium-ion batteries based on improved LSTM and health indicators extraction
Yan Ma, Ce Shan, Jinwu Gao, et al.
Energy (2022) Vol. 251, pp. 123973-123973
Closed Access | Times Cited: 179
General Discharge Voltage Information Enabled Health Evaluation for Lithium-Ion Batteries
Zhongwei Deng, Xiao Hu, Xianke Lin, et al.
IEEE/ASME Transactions on Mechatronics (2020) Vol. 26, Iss. 3, pp. 1295-1306
Open Access | Times Cited: 174
Predictive Battery Health Management With Transfer Learning and Online Model Correction
Yunhong Che, Zhongwei Deng, Xianke Lin, et al.
IEEE Transactions on Vehicular Technology (2021) Vol. 70, Iss. 2, pp. 1269-1277
Closed Access | Times Cited: 173
State of health estimation for lithium-ion batteries based on temperature prediction and gated recurrent unit neural network
Zheng Chen, Hongqian Zhao, Yuanjian Zhang, et al.
Journal of Power Sources (2021) Vol. 521, pp. 230892-230892
Open Access | Times Cited: 142
A Flexible State-of-Health Prediction Scheme for Lithium-Ion Battery Packs With Long Short-Term Memory Network and Transfer Learning
Xing Shu, Jiangwei Shen, Guang Li, et al.
IEEE Transactions on Transportation Electrification (2021) Vol. 7, Iss. 4, pp. 2238-2248
Open Access | Times Cited: 129
State of health prediction of lithium-ion batteries based on machine learning: Advances and perspectives
Xing Shu, Shuhang Shen, Jiangwei Shen, et al.
iScience (2021) Vol. 24, Iss. 11, pp. 103265-103265
Open Access | Times Cited: 124
Machine learning for predicting battery capacity for electric vehicles
Jingyuan Zhao, Heping Ling, Jin Liu, et al.
eTransportation (2022) Vol. 15, pp. 100214-100214
Closed Access | Times Cited: 108
Estimation of the state of health (SOH) of batteries using discrete curvature feature extraction
Hui Hwang Goh, Zhentao Lan, Dongdong Zhang, et al.
Journal of Energy Storage (2022) Vol. 50, pp. 104646-104646
Closed Access | Times Cited: 100
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: 95
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: 81
A hybrid neural network model with attention mechanism for state of health estimation of lithium-ion batteries
Aihua Tang, Yihan Jiang, Quanqing Yu, et al.
Journal of Energy Storage (2023) Vol. 68, pp. 107734-107734
Closed Access | Times Cited: 78
An overview of data-driven battery health estimation technology for battery management system
Minzhi Chen, Guijun Ma, Weibo Liu, et al.
Neurocomputing (2023) Vol. 532, pp. 152-169
Closed Access | Times Cited: 73
State-of-health estimation of lithium-ion batteries based on improved long short-term memory algorithm
Gong Ya-dong, Xiaoyong Zhang, Dianzhu Gao, et al.
Journal of Energy Storage (2022) Vol. 53, pp. 105046-105046
Closed Access | Times Cited: 69
State of health estimation for lithium-ion battery based on particle swarm optimization algorithm and extreme learning machine
Kui Chen, Jiali Li, Kai Liu, et al.
Green Energy and Intelligent Transportation (2024) Vol. 3, Iss. 1, pp. 100151-100151
Open Access | Times Cited: 24
On the feature selection for battery state of health estimation based on charging–discharging profiles
Yuanyuan Li, Daniel‐Ioan Stroe, Yuhua Cheng, et al.
Journal of Energy Storage (2020) Vol. 33, pp. 102122-102122
Closed Access | Times Cited: 120
Stage of Charge Estimation of Lithium-Ion Battery Packs Based on Improved Cubature Kalman Filter With Long Short-Term Memory Model
Xing Shu, Guang Li, Yuanjian Zhang, et al.
IEEE Transactions on Transportation Electrification (2020) Vol. 7, Iss. 3, pp. 1271-1284
Open Access | Times Cited: 86
Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles
Lidiya Komsiyska, Tobias Buchberger, Simon Diehl, et al.
Energies (2021) Vol. 14, Iss. 18, pp. 5989-5989
Open Access | Times Cited: 85
Synthetic state of charge estimation for lithium-ion batteries based on long short-term memory network modeling and adaptive H-Infinity filter
Zheng Chen, Hongqian Zhao, Xing Shu, et al.
Energy (2021) Vol. 228, pp. 120630-120630
Open Access | Times Cited: 83
Review on State of Health estimation methodologies for lithium-ion batteries in the context of circular economy
Akash Basia, Zineb Simeu-Abazi, Eric Gascard, et al.
CIRP journal of manufacturing science and technology (2021) Vol. 32, pp. 517-528
Open Access | Times Cited: 78
State of charge prediction framework for lithium-ion batteries incorporating long short-term memory network and transfer learning
Yu Liu, Xing Shu, Hanzhengnan Yu, et al.
Journal of Energy Storage (2021) Vol. 37, pp. 102494-102494
Closed Access | Times Cited: 72
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