Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

State of health prediction of lithium-ion batteries based on machine learning: Advances and perspectives
Xing Shu, Shuhang Shen, Jiangwei Shen, et al.
iScience (2021) Vol. 24, Iss. 11, pp. 103265-103265
Open Access | Times Cited: 124

Showing 1-25 of 124 citing articles:

Application of Electrochemical Impedance Spectroscopy to Degradation and Aging Research of Lithium-Ion Batteries
Wenxuan Hu, Yufan Peng, Yimin Wei, et al.
The Journal of Physical Chemistry C (2023) Vol. 127, Iss. 9, pp. 4465-4495
Closed Access | Times Cited: 159
Flexible battery state of health and state of charge estimation using partial charging data and deep learning
Jinpeng Tian, Rui Xiong, Weixiang Shen, et al.
Energy storage materials (2022) Vol. 51, pp. 372-381
Closed Access | Times Cited: 154
Connecting battery technologies for electric vehicles from battery materials to management
Gang Zhao, Xiaolin Wang, Michael Negnevitsky
iScience (2022) Vol. 25, Iss. 2, pp. 103744-103744
Open Access | Times Cited: 102
Semi-supervised estimation of capacity degradation for lithium ion batteries with electrochemical impedance spectroscopy
Rui Xiong, Jinpeng Tian, Weixiang Shen, et al.
Journal of Energy Chemistry (2022) Vol. 76, pp. 404-413
Closed Access | Times Cited: 94
Lithium-Ion Battery Management System for Electric Vehicles: Constraints, Challenges, and Recommendations
A.K.M. Ahasan Habib, Mohammad Kamrul Hasan, Ghassan F. Issa, et al.
Batteries (2023) Vol. 9, Iss. 3, pp. 152-152
Open Access | Times Cited: 77
State of health estimation for lithium-ion battery based on energy features
Dongliang Gong, Ying Gao, Yalin Kou, et al.
Energy (2022) Vol. 257, pp. 124812-124812
Closed Access | Times Cited: 72
State of health estimation for lithium-ion batteries based on hybrid attention and deep learning
Hongqian Zhao, Zheng Chen, Xing Shu, et al.
Reliability Engineering & System Safety (2022) Vol. 232, pp. 109066-109066
Closed Access | Times Cited: 68
Convolutional autoencoder-based SOH estimation of lithium-ion batteries using electrochemical impedance spectroscopy
Josue Obregon, Yu-Ri Han, Chang Won Ho, et al.
Journal of Energy Storage (2023) Vol. 60, pp. 106680-106680
Closed Access | Times Cited: 65
Battery SOH estimation and RUL prediction framework based on variable forgetting factor online sequential extreme learning machine and particle filter
Wenxian Duan, Shixin Song, Feng Xiao, et al.
Journal of Energy Storage (2023) Vol. 65, pp. 107322-107322
Closed Access | Times Cited: 60
A novel back propagation neural network-dual extended Kalman filter method for state-of-charge and state-of-health co-estimation of lithium-ion batteries based on limited memory least square algorithm
Chao Wang, Shunli Wang, Jinzhi Zhou, et al.
Journal of Energy Storage (2023) Vol. 59, pp. 106563-106563
Closed Access | Times Cited: 58
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
Machine learning for battery research
Zheng Wei, Qiu He, Yan Zhao
Journal of Power Sources (2022) Vol. 549, pp. 232125-232125
Closed Access | Times Cited: 62
Li-ion battery degradation modes diagnosis via Convolutional Neural Networks
Nahuel Costa, Luciano Sánchez, David Anseán, et al.
Journal of Energy Storage (2022) Vol. 55, pp. 105558-105558
Open Access | Times Cited: 45
State-of-health estimation for lithium-ion batteries with hierarchical feature construction and auto-configurable Gaussian process regression
Haiyan Jin, Ningmin Cui, Lei Cai, et al.
Energy (2022) Vol. 262, pp. 125503-125503
Closed Access | Times Cited: 41
Data-driven-aided strategies in battery lifecycle management: Prediction, monitoring, and optimization
Liqianyun Xu, Feng Wu, Renjie Chen, et al.
Energy storage materials (2023) Vol. 59, pp. 102785-102785
Closed Access | Times Cited: 39
Deep feature extraction in lifetime prognostics of lithium-ion batteries: Advances, challenges and perspectives
Chuan Li, Huahua Zhang, Ping Ding, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 184, pp. 113576-113576
Closed Access | Times Cited: 39
State of health estimation of lithium-ion batteries based on equivalent circuit model and data-driven method
Liping Chen, Xinyuan Bao, António M. Lopes, et al.
Journal of Energy Storage (2023) Vol. 73, pp. 109195-109195
Closed Access | Times Cited: 33
Model-free reconstruction of capacity degradation trajectory of lithium-ion batteries using early cycle data
Seongyoon Kim, Hangsoon Jung, Min‐Ho Lee, et al.
eTransportation (2023) Vol. 17, pp. 100243-100243
Open Access | Times Cited: 25
Hybrid Modeling of Lithium-Ion Battery: Physics-Informed Neural Network for Battery State Estimation
Soumya Singh, Yvonne Eboumbou Ebongue, Shahed Rezaei, et al.
Batteries (2023) Vol. 9, Iss. 6, pp. 301-301
Open Access | Times Cited: 23
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
Co-Estimation of State-of-Charge and State-of-Health for Lithium-Ion Batteries Considering Temperature and Ageing
Xin Lai, Ming Yuan, Xiaopeng Tang, et al.
Energies (2022) Vol. 15, Iss. 19, pp. 7416-7416
Open Access | Times Cited: 36
Battery health evaluation using a short random segment of constant current charging
Zhongwei Deng, Xiao Hu, Yi Xie, et al.
iScience (2022) Vol. 25, Iss. 5, pp. 104260-104260
Open Access | Times Cited: 32
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
Clustering and dynamic recognition based auto-reservoir neural network: A wait-and-see approach for short-term park power load forecasting
Jing‐yao Liu, Jiajia Chen, Guijin Yan, et al.
iScience (2023) Vol. 26, Iss. 8, pp. 107456-107456
Open Access | Times Cited: 18
A Flexible deep convolutional neural network coupled with progressive training framework for online capacity estimation of lithium-ion batteries
Qiao Xue, Junqiu Li, Yansheng Xiao, et al.
Journal of Cleaner Production (2023) Vol. 397, pp. 136575-136575
Closed Access | Times Cited: 17
Page 1 - Next Page

Scroll to top