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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 the incremental capacity and wavelet neural networks with genetic algorithm
Chun Chang, Qiyue Wang, Jiuchun Jiang, et al.
Journal of Energy Storage (2021) Vol. 38, pp. 102570-102570
Closed Access | Times Cited: 125

Showing 26-50 of 125 citing articles:

Aging mechanisms, prognostics and management for lithium-ion batteries: Recent advances
Yujie Wang, Haoxiang Xiang, Yin‐Yi Soo, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 207, pp. 114915-114915
Closed Access | Times Cited: 12
Capacity estimation of lithium-ion batteries with uncertainty quantification based on temporal convolutional network and Gaussian process regression
R. Zhang, Chunhui Ji, Xing Zhou, et al.
Energy (2024) Vol. 297, pp. 131154-131154
Closed Access | Times Cited: 11
State of health estimation of lithium-ion battery based on CNN–WNN–WLSTM
Qiongrong Yao, Xianhua Song, Wei Xie
Complex & Intelligent Systems (2024) Vol. 10, Iss. 2, pp. 2919-2936
Open Access | Times Cited: 8
A hybrid neural network based on variational mode decomposition denoising for predicting state-of-health of lithium-ion batteries
Zifan Yuan, Tian Tian, Fuchong Hao, et al.
Journal of Power Sources (2024) Vol. 609, pp. 234697-234697
Closed Access | Times Cited: 8
A CMMOG-based lithium-battery SOH estimation method using multi-task learning framework
Chaolong Zhang, Liang Tu, Zhong Yang, et al.
Journal of Energy Storage (2024) Vol. 107, pp. 114884-114884
Closed Access | Times Cited: 8
Multi-objective optimization estimation of state of health for lithium-ion battery based on constant current charging profile
Wenzhen Hu, Chuang Zhang, Suzhen Liu, et al.
Journal of Energy Storage (2024) Vol. 83, pp. 110785-110785
Closed Access | Times Cited: 7
An encoder-decoder model based on deep learning for state of health estimation of lithium-ion battery
Qingrui Gong, Ping Wang, Ze Cheng
Journal of Energy Storage (2021) Vol. 46, pp. 103804-103804
Closed Access | Times Cited: 50
Modified particle filtering‐based robust estimation for a networked control system corrupted by impulsive noise
Xuehai Wang, Feng Ding
International Journal of Robust and Nonlinear Control (2021) Vol. 32, Iss. 2, pp. 830-850
Closed Access | Times Cited: 48
Moving data window-based partially-coupled estimation approach for modeling a dynamical system involving unmeasurable states
Ting Cui, Feng Ding, Tasawar Hayat
ISA Transactions (2021) Vol. 128, pp. 437-452
Closed Access | Times Cited: 41
Gradient Parameter Estimation of a Class of Nonlinear Systems Based on the Maximum Likelihood Principle
Chen Zhang, Haibo Liu, Yan Ji
International Journal of Control Automation and Systems (2022) Vol. 20, Iss. 5, pp. 1393-1404
Closed Access | Times Cited: 36
A hybrid data-driven method for rapid prediction of lithium-ion battery capacity
Jiabei He, Yi Tian, Lifeng Wu
Reliability Engineering & System Safety (2022) Vol. 226, pp. 108674-108674
Closed Access | Times Cited: 35
A Data-Driven Model Framework Based on Deep Learning for Estimating the States of Lithium-Ion Batteries
Qingrui Gong, Ping Wang, Ze Cheng
Journal of The Electrochemical Society (2022) Vol. 169, Iss. 3, pp. 030532-030532
Closed Access | Times Cited: 29
A novel based-performance degradation Wiener process model for real-time reliability evaluation of lithium-ion battery
Yun Zhu, Si‐Wei Liu, Kexiang Wei, et al.
Journal of Energy Storage (2022) Vol. 50, pp. 104313-104313
Closed Access | Times Cited: 28
Electric vehicle battery capacity degradation and health estimation using machine-learning techniques: a review
Kaushik Das, Roushan Kumar
Clean Energy (2023) Vol. 7, Iss. 6, pp. 1268-1281
Open Access | Times Cited: 20
Joint Estimation of State of Charge and State of Energy of Lithium-Ion Batteries Based on Optimized Bidirectional Gated Recurrent Neural Network
Liping Chen, Yingjie Song, António M. Lopes, et al.
IEEE Transactions on Transportation Electrification (2023) Vol. 10, Iss. 1, pp. 1605-1616
Closed Access | Times Cited: 19
Mathematical modelling of electrochemical, thermal and degradation processes in lithium-ion cells—A comprehensive review
Rohit Mehta, Amit Gupta
Renewable and Sustainable Energy Reviews (2023) Vol. 192, pp. 114264-114264
Closed Access | Times Cited: 17
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
Reconstruction of the incremental capacity trajectories from current-varying profiles for lithium-ion batteries
Xiaopeng Tang, Yujie Wang, Qi Liu, et al.
iScience (2021) Vol. 24, Iss. 10, pp. 103103-103103
Open Access | Times Cited: 38
CL-Net: ConvLSTM-Based Hybrid Architecture for Batteries’ State of Health and Power Consumption Forecasting
Noman Khan, Ijaz Ul Haq, Fath U Min Ullah, et al.
Mathematics (2021) Vol. 9, Iss. 24, pp. 3326-3326
Open Access | Times Cited: 35
State of health estimation of lithium-ion battery using energy accumulation-based feature extraction and improved relevance vector regression
Cheng Qian, Ning He, Lile He, et al.
Journal of Energy Storage (2023) Vol. 68, pp. 107754-107754
Closed Access | Times Cited: 14
A Novel Long Short-Term Memory Approach for Online State-of-Health Identification in Lithium-Ion Battery Cells
Mike R. Kopp, Alexander Fill, Marco Ströbel, et al.
Batteries (2024) Vol. 10, Iss. 3, pp. 77-77
Open Access | Times Cited: 4
Feature selection strategy optimization for lithium-ion battery state of health estimation under impedance uncertainties
Xinghao Du, Jinhao Meng, Yassine Amirat, et al.
Journal of Energy Chemistry (2024) Vol. 101, pp. 87-98
Open Access | Times Cited: 4
Battery state of health estimation using a novel BiLSTM-Mamba2 network with differential voltage features and transfer learning
Yunong Liu, Yuefeng Liu, Hongyu Shen, et al.
Journal of Energy Storage (2025) Vol. 110, pp. 115347-115347
Closed Access
Rough Estimation and Error Compensation: Empirical-Data-Driven Lightweight State of Health Estimation for Lithium-Ion Batteries
Pengya Fang, Anhao Zhang, Han Zhang, et al.
(2025)
Closed Access
Deep learning model-based real-time state-of-health estimation of lithium-ion batteries under dynamic operating conditions
Telu Tang, Xiangguo Yang, Muheng Li, et al.
Energy (2025), pp. 134697-134697
Closed Access

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