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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:

SOH estimation for lithium-ion batteries: An improved GPR optimization method based on the developed feature extraction
Ye He, Wenyuan Bai, Lulu Wang, et al.
Journal of Energy Storage (2024) Vol. 83, pp. 110678-110678
Closed Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

SOH estimation of lithium-ion batteries based on multi-feature deep fusion and XGBoost
Jing Sun, Chaoqun Fan, huiyi yan
Energy (2024) Vol. 306, pp. 132429-132429
Closed Access | Times Cited: 9
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
State of Health Estimation for Lithium-Ion Batteries Using Enhanced Whale Optimization Algorithm for Feature Selection and Support Vector Regression Model
Rui Wang, Xiaowei Xu, Qi Zhou, et al.
Processes (2025) Vol. 13, Iss. 1, pp. 158-158
Open Access
State of Health Estimation of Lithium-Ion Batteries Based on Feature Optimization and Data-Driven Models
G. G. Mu, Qingguo Wei, Yonghong Xu, et al.
Energy (2025), pp. 134578-134578
Closed Access
A decade of machine learning in lithium-ion battery state estimation: a systematic review
Zaina Al-Hashimi, Taha Khamis, Mouaz Al Kouzbary, et al.
Ionics (2025) Vol. 31, Iss. 3, pp. 2351-2377
Closed Access
A review of feature extraction toward health state estimation of lithium-ion batteries
Qingwei Li, Wenli Xue
Journal of Energy Storage (2025) Vol. 112, pp. 115453-115453
Closed Access
A Novel Method for Estimating the State of Health of Lithium-Ion Batteries Based on Physics-Informed Neural Network
Yuxuan Deng, Changqing Du, Zhong Ren
Batteries (2025) Vol. 11, Iss. 2, pp. 49-49
Open Access
Practical State of Health Prediction for Lithium-Ion Batteries Under Complex Dynamic Discharge Scenarios
Xiaowen Sun, Zhiyuan Wei, Binhui Liu, et al.
(2025)
Closed Access
Correlation Analysis of Automotive Battery State-of-Health Indicators for Advanced Battery Management Systems
Thomas Long, Haifang Shang, Xiaoqi Liu, et al.
SAE technical papers on CD-ROM/SAE technical paper series (2025) Vol. 1
Closed Access
Physics-informed Machine Learning for Accurate SOH Estimation of Lithium-ion Batteries Considering Various Temperatures and Operating Conditions
Chunsong Lin, Xianguo Tuo, Longxing Wu, et al.
Energy (2025), pp. 134937-134937
Closed Access
State of health estimation for lithium-ion batteries based on fragmented charging data and improved gated recurrent unit neural network
Zheng Chen, Peng Yue, Jiangwei Shen, et al.
Journal of Energy Storage (2025) Vol. 115, pp. 115952-115952
Closed Access
Study on lithium-ion battery state of health estimation through multiobjective feature selection and multivariate analysis
Xuebin Li, Jin Zhao, Yang Luchun, et al.
Energy Reports (2025) Vol. 13, pp. 3035-3049
Closed Access
CTBANet: A new method for state of health estimation of lithium-ion batteries
Qinglin Zhu, Xiangfeng Zeng, Zhongren Wang, et al.
Journal of Energy Storage (2025) Vol. 117, pp. 116134-116134
Closed Access
State of health estimation for lithium-ion batteries based on optimal feature subset algorithm
Jing Sun, Haitao Wang
Energy (2025), pp. 135685-135685
Closed Access
State of health estimation embedded with hardware accelerator based on long short-term memory combined with Bayesian optimization considering extracted health indicator in charging conditions
Sangwoo Cho, Dong‐Ho Han, Jaewon Kim, et al.
Journal of Energy Storage (2024) Vol. 90, pp. 111897-111897
Closed Access | Times Cited: 3
Joint prediction of state of health and remaining useful life for lithium-ion batteries based on health features optimization and multi-model fusion
Zheng Di, Shuo Man, Xifeng Guo, et al.
Ionics (2024) Vol. 30, Iss. 10, pp. 6239-6252
Closed Access | Times Cited: 3
Capacity Estimation for Lithium-ion Batteries Based on Heterogeneous Stacking Model with Feature Fusion.
G. G. Mu, Qingguo Wei, Yonghong Xu, et al.
Energy (2024), pp. 133881-133881
Closed Access | Times Cited: 3
Li-ion battery state of health prediction through metaheuristic algorithms and genetic programming
Xuebin Li, Zhao Jin, Shengqun Li, et al.
Energy Reports (2024) Vol. 12, pp. 368-380
Closed Access | Times Cited: 2
Improved Deep Extreme Learning Machine for State of Health Estimation of Lithium-Ion Battery
Yan Chen, Junli Meng, Shunyang Ming, et al.
International Journal of Energy Research (2024) Vol. 2024, pp. 1-22
Open Access | Times Cited: 2
A battery SOH estimation method based on entropy domain features and semi-supervised learning under limited sample conditions
Yaming Liu, Jiaxin Ding, Yingjie Cai, et al.
Journal of Energy Storage (2024) Vol. 106, pp. 114822-114822
Closed Access | Times Cited: 2
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
State of Health Estimation of Lithium-Ion Batteries Using Fusion Health Indicator by PSO-ELM Model
Jun Chen, Yan Liu, Jun Yong, et al.
Batteries (2024) Vol. 10, Iss. 11, pp. 380-380
Open 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
State of health estimation for lithium-ion batteries based on voltage segment and transformer
Xing Shu, Hao Yang, Xi Liu, et al.
Journal of Energy Storage (2024) Vol. 108, pp. 115200-115200
Closed Access | Times Cited: 1
A Novel On-board SOH Estimation Method for Lithium-ion Batteries with Hybrid Feature Approach
Huseyin Yigit Cem Altintas
(2024)
Open Access
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