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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:

Lithium-ion battery state of health estimation using a hybrid model based on a convolutional neural network and bidirectional gated recurrent unit
Yahia Mazzi, Hicham Ben Sassi, Fatima Errahimi
Engineering Applications of Artificial Intelligence (2023) Vol. 127, pp. 107199-107199
Closed Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

An improved convolutional neural network-bidirectional gated recurrent unit algorithm for robust state of charge and state of energy estimation of new energy vehicles of lithium-ion batteries
Fan Wu, Shunli Wang, Donglei Liu, et al.
Journal of Energy Storage (2024) Vol. 82, pp. 110574-110574
Closed Access | Times Cited: 15
Integrating particle swarm optimization with convolutional and long short-term memory neural networks for real vehicle data-based lithium-ion battery health estimation
Weiwei Huo, Y.-R. Chang, T. Luo, et al.
Journal of Energy Storage (2025) Vol. 111, pp. 115427-115427
Closed Access | Times Cited: 1
State of the Art in Electric Batteries’ State-of-Health (SoH) Estimation with Machine Learning: A Review
Giovane Ronei Sylvestrin, Joylan Nunes Maciel, Márcio Luís Munhoz Amorim, et al.
Energies (2025) Vol. 18, Iss. 3, pp. 746-746
Open Access | Times Cited: 1
Health prognosis via feature optimization and convolutional neural network for lithium-ion batteries
Mingqiang Lin, Leisi Ke, Wei Wang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108666-108666
Closed Access | Times Cited: 7
Using transformer and a reweighting technique to develop a remaining useful life estimation method for turbofan engines
Gyeongho Kim, Jae Gyeong Choi, Sunghoon Lim
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108475-108475
Closed Access | Times Cited: 7
Adaptable capacity estimation of lithium-ion battery based on short-duration random constant-current charging voltages and convolutional neural networks
Zuolu Wang, Xiaoyu Zhao, Dong Zhen, et al.
Energy (2024) Vol. 306, pp. 132541-132541
Open Access | Times Cited: 5
Evaluation of Advances in Battery Health Prediction for Electric Vehicles from Traditional Linear Filters to Latest Machine Learning Approaches
Adrienn Dineva
Batteries (2024) Vol. 10, Iss. 10, pp. 356-356
Open Access | Times Cited: 5
Methods for state of health estimation for lithium-ion batteries: An essential review
Houda Rhdifa, Abderazzak Ammar, Omar Bouattane
E3S Web of Conferences (2025) Vol. 601, pp. 00071-00071
Open Access
A hybrid probabilistic battery health management approach for robust inspection drone operations
Jokin Alcibar, Jose Ignacio Aizpurua, Ekhi Zugasti, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 146, pp. 110246-110246
Closed Access
Deep Learning-Driven Estimation and Multi-Objective Optimization of Lithium-Ion Battery Parameters for Enhanced EV/HEV Performance
Nima Khosravi, Adel Oubelaid
Energy (2025), pp. 135147-135147
Closed Access
Prescribing optimal health-aware operation for urban air mobility with deep reinforcement learning
Mina Montazeri, Chetan S. Kulkarni, Olga Fink
Reliability Engineering & System Safety (2025), pp. 110897-110897
Open Access
Economic implications of enhanced stock market analysis using improved forecasting methods
Jason Peng, Yuming Yang
Expert Systems with Applications (2025), pp. 127240-127240
Closed Access
Deep Learning for State of Health Estimation of Lithium-Ion Batteries in Electric Vehicles: A Systematic Review
Chenyuan Liu, Heng Li, Kexin Li, et al.
Energies (2025) Vol. 18, Iss. 6, pp. 1463-1463
Open Access
Battery health prediction using two-dimensional multi-channel ensemble models
Lei Yao, Changsheng Zhao, Yanqiu Xiao, et al.
Journal of Energy Storage (2024) Vol. 86, pp. 111304-111304
Closed Access | Times Cited: 2
A weighted Gaussian process regression model based on improved local outlier factor and its application in state of health estimation of lithium-ion battery
Cheng Qian, Ning He, Lile He, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 138, pp. 109314-109314
Closed Access | Times Cited: 2
Dynamic K-Decay Learning Rate Optimization for Deep Convolutional Neural Network to Estimate the State of Charge for Electric Vehicle Batteries
Neha Bhushan, Saad Mekhilef, Kok Soon Tey, et al.
Energies (2024) Vol. 17, Iss. 16, pp. 3884-3884
Open 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
Robust state of health estimation of commercial lithium-ion batteries based on enhanced hybrid machine learning model for electrified transportation
Deepak Kumar, M. Rizwan, Amrish K. Panwar
Electrical Engineering (2024)
Closed Access | Times Cited: 1
AM-MFF: A multi-feature fusion framework based on attention mechanism for robust and interpretable lithium-ion battery state of health estimation
Sizhe Chen, Jing Liu, Haoliang Yuan, et al.
Applied Energy (2024) Vol. 381, pp. 125116-125116
Closed Access | Times Cited: 1
An innovative multitask learning - long short-term memory neural network for the online anti-aging state of charge estimation of lithium-ion batteries adaptive to varying temperature and current conditions
Junjie Tao, Shunli Wang, Wen Cao, et al.
Energy (2024), pp. 134272-134272
Closed Access | Times Cited: 1
Methodology for Acquiring a Comprehensive Electrical, Thermal and Cycling Degradation Battery Model
Mikel González-Pérez, F.J. Asensio, I. Zamora, et al.
(2024)
Closed Access
Mechanical Behavior and Failure Prediction of Cylindrical Lithium-Ion Batteries Under Mechanical Abuse Using Data-Driven Machine Learning
Xinchun Zhang, Xiao-di Yin, Zixuan Huang, et al.
(2024)
Closed Access
Methodology for Acquiring a Comprehensive Electrical, Thermal and Cycling Degradation Battery Model
Mikel González-Pérez, F.J. Asensio, I. Zamora, et al.
(2024)
Closed Access
Enhancing Model Robustness in Battery Health Prediction through Advanced Input Features
Jamila Hemdani, Laid Degaa, Nassim Rizoug, et al.
(2024), pp. 1-6
Closed Access
PMTT: Parallel multi-scale temporal convolution network and transformer for predicting the time to aging failure of software systems
Kai Jia, Xiao Yu, Chen Zhang, et al.
Journal of Systems and Software (2024) Vol. 217, pp. 112167-112167
Closed Access
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