Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

Predict the lifetime of lithium-ion batteries using early cycles: A review

Minxing Yang, Xiaofei Sun, Rui Liu, Lingzhi Wang, Fei Zhao and Xuesong Mei
Applied Energy 376 124171 (2024)
https://doi.org/10.1016/j.apenergy.2024.124171

Predicting the RUL of Li-Ion Batteries in UAVs Using Machine Learning Techniques

Dragos Andrioaia, Vasile Gaitan, George Culea and Ioan Banu
Computers 13 (3) 64 (2024)
https://doi.org/10.3390/computers13030064

An Improved Generic Hybrid Prognostic Method for RUL Prediction Based on PF-LSTM Learning

Ke Xue, Jun Yang, Ming Yang and Dagui Wang
IEEE Transactions on Instrumentation and Measurement 72 1 (2023)
https://doi.org/10.1109/TIM.2023.3251391

Hybrid Neural Network Method for Predicting the SOH and RUL of Lithium-Ion Batteries

Brahim Zraibi, Mohamed Mansouri, Salah Eddine Loukili and Said Ben Alla
Advances in Science, Technology and Engineering Systems Journal 7 (5) 193 (2022)
https://doi.org/10.25046/aj070520

Comparing deep learning methods to predict the remaining useful life of lithium-ion batteries

Brahim Zraibi, Mohamed Mansouri and Salah Eddine Loukili
Materials Today: Proceedings 62 6298 (2022)
https://doi.org/10.1016/j.matpr.2022.04.082

State of charge, remaining useful life and knee point estimation based on artificial intelligence and Machine learning in lithium-ion EV batteries: A comprehensive review

Aryan Shah, Khushi Shah, Charmi Shah and Manan Shah
Renewable Energy Focus 42 146 (2022)
https://doi.org/10.1016/j.ref.2022.06.001