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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:

Degradation Curve Prediction of Lithium-Ion Batteries Based on Knee Point Detection Algorithm and Convolutional Neural Network
Muhammad Haris, Muhammad Noman Hasan, Shiyin Qin
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-10
Closed Access | Times Cited: 53

Showing 1-25 of 53 citing articles:

Applications of artificial neural network based battery management systems: A literature review
Mehmet Kurucan, Mete Özbaltan, Zekí Yetgín, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 192, pp. 114262-114262
Closed Access | Times Cited: 65
Deep learning enhanced lithium-ion battery nonlinear fading prognosis
Shanling Ji, Jianxiong Zhu, Zhiyang Lyu, et al.
Journal of Energy Chemistry (2023) Vol. 78, pp. 565-573
Closed Access | Times Cited: 43
Predictive health assessment for lithium-ion batteries with probabilistic degradation prediction and accelerating aging detection
Yunhong Che, Yusheng Zheng, Florent Forest, et al.
Reliability Engineering & System Safety (2023) Vol. 241, pp. 109603-109603
Open Access | Times Cited: 40
Unsupervised dynamic prognostics for abnormal degradation of lithium-ion battery
Cong Wang, Yunxia Chen
Applied Energy (2024) Vol. 365, pp. 123280-123280
Closed Access | Times Cited: 32
Exploring Lithium-Ion Battery Degradation: A Concise Review of Critical Factors, Impacts, Data-Driven Degradation Estimation Techniques, and Sustainable Directions for Energy Storage Systems
Tuhibur Rahman, Talal Alharbi
Batteries (2024) Vol. 10, Iss. 7, pp. 220-220
Open Access | Times Cited: 22
State-of-health estimation and knee point identification of lithium-ion battery based on data-driven and mechanism model
Yulong Ni, Kai Song, Lei Pei, et al.
Applied Energy (2025) Vol. 385, pp. 125539-125539
Closed Access | Times Cited: 1
Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Data Preprocessing and Improved ELM
Weili Wu, Shuangshuang Lu
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-14
Closed Access | Times Cited: 29
Voltage relaxation-based state-of-health estimation of lithium-ion batteries using convolutional neural networks and transfer learning
Shaowen Zhang, Haiping Zhu, Jun Wu, et al.
Journal of Energy Storage (2023) Vol. 73, pp. 108579-108579
Closed Access | Times Cited: 29
Nonlinear aging knee-point prediction for lithium-ion batteries faced with different application scenarios
Heze You, Jiangong Zhu, Xueyuan Wang, et al.
eTransportation (2023) Vol. 18, pp. 100270-100270
Closed Access | Times Cited: 26
Review—Flow Batteries from 1879 to 2022 and Beyond
Yuriy V. Tolmachev
Journal of The Electrochemical Society (2023) Vol. 170, Iss. 3, pp. 030505-030505
Open Access | Times Cited: 22
Prediction of nonlinear degradation knee-point and remaining useful life for lithium-ion batteries using relaxation voltage
Wenjun Fan, Jiangong Zhu, Dongdong Qiao, et al.
Energy (2024) Vol. 294, pp. 130900-130900
Closed Access | Times Cited: 13
An Improved Transformer Model for Remaining Useful Life Prediction of Lithium-Ion Batteries under Random Charging and Discharging
Wenwen Zhang, Jianfang Jia, Xiaoqiong Pang, et al.
Electronics (2024) Vol. 13, Iss. 8, pp. 1423-1423
Open Access | Times Cited: 8
A structural pruning method for lithium-ion batteries remaining useful life prediction model with multi-head attention mechanism
Ge Yang, Jiaxin Ma, Guodong Sun
Journal of Energy Storage (2024) Vol. 86, pp. 111396-111396
Closed Access | Times Cited: 7
A CNN-GRU Approach to the Accurate Prediction of Batteries’ Remaining Useful Life from Charging Profiles
Sadiqa Jafari, Yung-Cheol Byun
Computers (2023) Vol. 12, Iss. 11, pp. 219-219
Open Access | Times Cited: 16
ICFormer: A Deep Learning model for informed lithium-ion battery diagnosis and early knee detection
Nahuel Costa, David Anseán, Matthieu Dubarry, et al.
Journal of Power Sources (2023) Vol. 592, pp. 233910-233910
Open Access | Times Cited: 16
Capacity degradation analysis and knee point prediction for Lithium-ion batteries
Teng Wang, Yuhao Zhu, Wenyuan Zhao, et al.
Green Energy and Intelligent Transportation (2024) Vol. 3, Iss. 5, pp. 100171-100171
Open Access | Times Cited: 5
Data-driven degradation trajectory prediction and online knee point identification of battery in electric vehicles
Kailing Li, Naiming Xie, Ou Tang
Engineering Failure Analysis (2024) Vol. 159, pp. 108154-108154
Closed Access | Times Cited: 5
Optimizing size and economic feasibility assessment of photovoltaic and energy storage setup in residential applications
Hossein Nourollahi Hokmabad, Oleksandr Husev, Jarek Kurnitski, et al.
Sustainable Energy Grids and Networks (2024) Vol. 38, pp. 101385-101385
Closed Access | Times Cited: 5
Navigation Path Prediction for Farmland Road Intersections Based on Improved Context Guided Network
Xuyan Li, Zhibo Wu
Sustainability (2025) Vol. 17, Iss. 2, pp. 753-753
Open Access
Early prediction of battery lifetime for lithium-ion batteries based on a hybrid clustered CNN model
Jing Hou, Taian Su, Tian Gao, et al.
Energy (2025), pp. 134992-134992
Closed Access
Lithium-Ion Battery State of Health Estimation by Matrix Profile Empowered Online Knee Onset Identification
Kate Qi Zhou, Yan Qin, Chau Yuen
IEEE Transactions on Transportation Electrification (2023) Vol. 10, Iss. 1, pp. 1935-1946
Closed Access | Times Cited: 12
A Battery Prognostics and Health Management Technique Based on Knee Critical Interval and Linear Complexity Self-Attention Transformer in Electric Vehicles
Yan Ma, Jiaqi Li, Yunfeng Hu, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 8, pp. 10216-10230
Closed Access | Times Cited: 4
Early-cycle prediction of battery aging onset across chemistries
Xi Tan, Nathan Zeng, Yu Deng, et al.
Journal of Energy Chemistry (2025)
Closed Access
Early-stage remaining useful life prediction for lithium-ion batteries based on geometric output construction
Xin Lai, Linglong Qian, Xiaopeng Tang, et al.
Journal of Energy Storage (2025) Vol. 114, pp. 115792-115792
Closed Access
Online identification of knee point in conventional and accelerated aging lithium-ion batteries using linear regression and Bayesian inference methods
Yulong Ni, Xiaoyu Li, He Zhang, et al.
Applied Energy (2025) Vol. 388, pp. 125646-125646
Closed Access
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