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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:

Deep learning enabled state of charge, state of health and remaining useful life estimation for smart battery management system: Methods, implementations, issues and prospects
Molla Shahadat Hossain Lipu, Shaheer Ansari, Md. Sazal Miah, et al.
Journal of Energy Storage (2022) Vol. 55, pp. 105752-105752
Closed Access | Times Cited: 107

Showing 26-50 of 107 citing articles:

Integrated Extended Kalman Filter and Deep Learning Platform for Electric Vehicle Battery Health Prediction
David Chunhu Li, Javio Renja Felix, Y.–K. Chin, et al.
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4354-4354
Open Access | Times Cited: 5
Enhanced battery life prediction with reduced data demand via semi-supervised representation learning
Liang Ma, Jinpeng Tian, Tieling Zhang, et al.
Journal of Energy Chemistry (2024)
Open Access | Times Cited: 5
Advanced data-driven fault diagnosis in lithium-ion battery management systems for electric vehicles: Progress, challenges, and future perspectives
Maher G. M. Abdolrasol, Afida Ayob, Molla Shahadat Hossain Lipu, et al.
eTransportation (2024) Vol. 22, pp. 100374-100374
Closed Access | Times Cited: 5
Prediction of electric vehicle battery state of health estimation using a hybrid deep learning mechanism
Akshat Kant, Manish Kumar, Sajjan Sihag
International Journal of Green Energy (2025), pp. 1-14
Closed Access
Advanced Machine Learning and Deep Learning Approaches for Estimating the Remaining Life of EV Batteries—A Review
Daniel H. de la Iglesia, Carlos Chinchilla Corbacho, Jorge Zakour Dib, et al.
Batteries (2025) Vol. 11, Iss. 1, pp. 17-17
Open Access
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
Lithium-Ion Batteries state of health estimation based on optimized TCN-GRU-WNN
Nan Zhang, Jing Li, Yunfeng Ma, et al.
Energy Reports (2025) Vol. 13, pp. 2502-2515
Closed Access
Hyperparameter-optimized machine learning model for real-time estimation of lithium-ion battery state-of-charge
Walid Touzout, Mohamed Abdessamed Ait Chikh, Fawzi Gougam, et al.
Electrical Engineering (2025)
Closed Access
State-of-Health Prediction of Lithium-Ion Batteries Using Feature Fusion and a Hybrid Neural Network Model
Yang Li, Guoqiang Gao, Kui Chen, et al.
Energy (2025), pp. 135163-135163
Closed Access
Mxenes for Zn-based energy storage devices: Nano-engineering and machine learning
Syed Shoaib Ahmad Shah, Hafiza Komal Zafar, Muhammad Sufyan Javed, et al.
Coordination Chemistry Reviews (2023) Vol. 501, pp. 215565-215565
Closed Access | Times Cited: 15
Artificial Intelligence Approaches for Advanced Battery Management System in Electric Vehicle Applications: A Statistical Analysis towards Future Research Opportunities
Molla Shahadat Hossain Lipu, Md. Sazal Miah, Taskin Jamal, et al.
Vehicles (2023) Vol. 6, Iss. 1, pp. 22-70
Open Access | Times Cited: 15
Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm
Yongfang Guo, Xiangyuan Yu, Yashuang Wang, et al.
Reliability Engineering & System Safety (2023) Vol. 244, pp. 109913-109913
Closed Access | Times Cited: 15
A design methodology to employ digital twins for remaining useful lifetime prediction in electric vehicle batteries
César Tadeu Nasser Medeiros Branco, Jackson Michels Fontanela
SAE technical papers on CD-ROM/SAE technical paper series (2024) Vol. 1
Closed Access | Times Cited: 4
Lithium-ion battery remaining useful life prediction: a federated learning-based approach
Ruirui Zhong, Bingtao Hu, Yixiong Feng, et al.
Energy Ecology and Environment (2024) Vol. 9, Iss. 5, pp. 549-562
Closed Access | Times Cited: 4
Optimizing EV Battery Management: Advanced Hybrid Reinforcement Learning Models for Efficient Charging and Discharging
Sercan Yalçın, Münür Sacit Herdem
Energies (2024) Vol. 17, Iss. 12, pp. 2883-2883
Open Access | Times Cited: 4
A Study on the Differences in Optimized Inputs of Various Data-Driven Methods for Battery Capacity Prediction
Kuo Xin, Jia Fu, Byungcho Choi, et al.
Batteries (2025) Vol. 11, Iss. 1, pp. 26-26
Open Access
Innovations and prognostics in battery degradation and longevity for energy storage systems
Julian Tebbe, Alexander Hartwig, Ali Jamali, et al.
Journal of Energy Storage (2025) Vol. 114, pp. 115724-115724
Open Access
A Novel Online State-of-Health Estimation Method for Lithium-Ion Batteries with Multi-Input Metabolic Long Short-Term Memory Framework
Lin Chen, Deqian Chen, Manping He, et al.
Energies (2025) Vol. 18, Iss. 5, pp. 1037-1037
Open Access
A survey of machine learning applications in advanced transportation systems: Trends, techniques, and future directions
Yuzhong Zhang, Songyang Zhang, Venkata Dinavahi
eTransportation (2025), pp. 100417-100417
Open Access
Enhanced State of Health Prediction for Lithium-Ion Batteries Using a Hybrid Convolutional–Kolmogorov–Arnold Network
Yunxian Cui, Y.T. Feng
International Journal of Electrochemical Science (2025), pp. 101008-101008
Open Access
Review—Optimized Particle Filtering Strategies for High-Accuracy State of Charge Estimation of LIBs
Shunli Wang, Xianyi Jia, Paul Takyi‐Aninakwa, et al.
Journal of The Electrochemical Society (2023) Vol. 170, Iss. 5, pp. 050514-050514
Open Access | Times Cited: 10
State of Health Estimation of Lithium‐ion Batteries Based on Machine Learning with Mechanical‐Electrical Features
Lili Gong, Zhiyuan Zhang, Xueyan Li, et al.
Batteries & Supercaps (2024)
Closed Access | Times Cited: 3
Intelligent SOX Estimation for Automotive Battery Management Systems: State-of-the-Art Deep Learning Approaches, Open Issues, and Future Research Opportunities
Molla Shahadat Hossain Lipu, Tahia Fahrin Karim, Shaheer Ansari, et al.
Energies (2022) Vol. 16, Iss. 1, pp. 23-23
Open Access | Times Cited: 18
Battery Energy Storage Systems for the New Electricity Market Landscape: Modeling, State Diagnostics, Management, and Viability—A Review
Pablo Carrasco Ortega, Pablo Durán Gómez, J Sánchez, et al.
Energies (2023) Vol. 16, Iss. 17, pp. 6334-6334
Open Access | Times Cited: 10
Predictive maintenance in Industry 4.0: a survey of planning models and machine learning techniques
Ida Hector, Rukmani Panjanathan
PeerJ Computer Science (2024) Vol. 10, pp. e2016-e2016
Open Access | Times Cited: 2

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