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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:

Transfer Learning-Based Hybrid Remaining Useful Life Prediction for Lithium-Ion Batteries Under Different Stresses
Dawei Pan, Hengfeng Li, Shaojun Wang
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-10
Closed Access | Times Cited: 63

Showing 1-25 of 63 citing articles:

Improved singular filtering-Gaussian process regression-long short-term memory model for whole-life-cycle remaining capacity estimation of lithium-ion batteries adaptive to fast aging and multi-current variations
Shunli Wang, Fan Wu, Paul Takyi‐Aninakwa, et al.
Energy (2023) Vol. 284, pp. 128677-128677
Open Access | Times Cited: 211
Semi-supervised learning for explainable few-shot battery lifetime prediction
Nanlin Guo, Sihui Chen, Jun Tao, et al.
Joule (2024) Vol. 8, Iss. 6, pp. 1820-1836
Closed Access | Times Cited: 29
Machine learning for battery systems applications: Progress, challenges, and opportunities
Zahra Nozarijouybari, Hosam K. Fathy
Journal of Power Sources (2024) Vol. 601, pp. 234272-234272
Closed Access | Times Cited: 27
A hybrid deep learning approach for remaining useful life prediction of lithium-ion batteries based on discharging fragments
Yunpeng Liu, Bo Hou, Moin Ahmed, et al.
Applied Energy (2024) Vol. 358, pp. 122555-122555
Closed Access | Times Cited: 16
A Hybrid Battery Equivalent Circuit Model, Deep Learning, and Transfer Learning for Battery State Monitoring
Su Shaosen, Wei Li, Jianhui Mou, et al.
IEEE Transactions on Transportation Electrification (2022) Vol. 9, Iss. 1, pp. 1113-1127
Closed Access | Times Cited: 67
Augmented model-based framework for battery remaining useful life prediction
Adam Thelen, Meng Li, Chao Hu, et al.
Applied Energy (2022) Vol. 324, pp. 119624-119624
Open Access | Times Cited: 50
Early prediction of lithium-ion battery cycle life based on voltage-capacity discharge curves
Xiong Wei, Gang Xu, Yumei Li, et al.
Journal of Energy Storage (2023) Vol. 62, pp. 106790-106790
Open Access | Times Cited: 33
A Novel Transfer Ensemble Learning Framework for Remaining Useful Life Prediction Under Multiple Working Conditions
Jilun Tian, Yuchen Jiang, Jiusi Zhang, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 23
Prognostics and health management for predictive maintenance: A review
Chao Huang, Siqi Bu, Hiu Hung Lee, et al.
Journal of Manufacturing Systems (2024) Vol. 75, pp. 78-101
Closed Access | Times Cited: 12
RUL Prediction of Lithium-Ion Battery in Early-Cycle Stage Based on Similar Sample Fusion Under Lebesgue Sampling Framework
Guangzheng Lyu, Heng Zhang, Qiang Miao
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 20
Equivalent circuit simulated deep network architecture and transfer learning for remaining useful life prediction of lithium-ion batteries
Cong Dai Nguyen, Suk Joo Bae
Journal of Energy Storage (2023) Vol. 71, pp. 108042-108042
Closed Access | Times Cited: 20
A novel hybrid model for lithium-ion batteries lifespan prediction with high accuracy and interpretability
Xiaoxian Pang, Wei Yang, Chengyun Wang, et al.
Journal of Energy Storage (2023) Vol. 61, pp. 106728-106728
Closed Access | Times Cited: 18
Scalability, Explainability and Performance of Data-Driven Algorithms in Predicting the Remaining Useful Life: A Comprehensive Review
Somayeh Bakhtiari Ramezani, Logan Cummins, Brad Killen, et al.
IEEE Access (2023) Vol. 11, pp. 41741-41769
Open Access | Times Cited: 16
Rapid Test and Assessment of Lithium-Ion Battery Cycle Life Based on Transfer Learning
Yuhao Zhu, Xin Gu, Kailong Liu, et al.
IEEE Transactions on Transportation Electrification (2024) Vol. 10, Iss. 4, pp. 9133-9143
Closed Access | Times Cited: 6
Advancing RUL prediction in mechanical systems: A hybrid deep learning approach utilizing non-full lifecycle data
Tianjiao Lin, Liuyang Song, Lingli Cui, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102524-102524
Closed Access | Times Cited: 6
Machine learning for full lifecycle management of lithium-ion batteries
Qiangxiang Zhai, Hongmin Jiang, Nengbing Long, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 202, pp. 114647-114647
Closed Access | Times Cited: 5
Hybrid Data-Driven Approach for Predicting the Remaining Useful Life of Lithium-Ion Batteries
Y. G. Li, Lei Li, Runze Mao, et al.
IEEE Transactions on Transportation Electrification (2023) Vol. 10, Iss. 2, pp. 2789-2805
Closed Access | Times Cited: 14
Probabilistic neural network-based flexible estimation of lithium-ion battery capacity considering multidimensional charging habits
Qingbo Li, Jun Zhong, Jinqiao Du, et al.
Energy (2024) Vol. 294, pp. 130881-130881
Closed Access | Times Cited: 4
Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Neural Network and Adaptive Unscented Kalman Filter
Lingtao Wu, Wenhao Guo, Yuben Tang, et al.
Electronics (2024) Vol. 13, Iss. 13, pp. 2619-2619
Open Access | Times Cited: 4
A review of Bayesian-filtering-based techniques in RUL prediction for Lithium-Ion batteries
May Htet Htet Khine, Cheong Kim, Nattapol Aunsri
Journal of Energy Storage (2025) Vol. 111, pp. 115371-115371
Closed Access
A survey on few-shot learning for remaining useful life prediction
Renpeng Mo, Han Zhou, Hongpeng Yin, et al.
Reliability Engineering & System Safety (2025), pp. 110850-110850
Closed Access
Generalizing capacity estimation for cross-domain lithium-ion batteries with deep multi-domain adaptation
Yubo Zhang, Youyuan Wang, Zhiwei Shen, et al.
Journal of Energy Storage (2025) Vol. 115, pp. 115947-115947
Closed Access
RUL Prediction Method for Electrical Connectors With Intermittent Faults Based on an Attention-LSTM Model
Xianzhe Cheng, Kehong Lv, Yong Zhang, et al.
IEEE Transactions on Components Packaging and Manufacturing Technology (2023) Vol. 13, Iss. 5, pp. 628-637
Closed Access | Times Cited: 12
Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Iterative Transfer Learning and Mogrifier LSTM
Zihan Li, Fang Bai, Hongfu Zuo, et al.
Batteries (2023) Vol. 9, Iss. 9, pp. 448-448
Open Access | Times Cited: 12
Remaining useful life prediction of lithium battery based on ACNN-Mogrifier LSTM-MMD
Zihan Li, Li Ai, Fang Bai, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 016101-016101
Closed Access | Times Cited: 12
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