An adaptive semi-supervised self-learning method for online state of health estimation of lithium-ion batteries
Author:
Funder
National Natural Science Foundation of China
Publisher
Elsevier BV
Reference44 articles.
1. Battery leakage fault diagnosis based on multi-modality multi-classifier fusion decision algorithm;Zhang;J Energy Storage,2023
2. A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery;Sui;Appl Energy,2021
3. A review on methods for state of health forecasting of lithium-ion batteries applicable in real-world operational conditions;von Bülow;J Energy Storage,2023
4. Review on technological advancement of lithium-ion battery states estimation methods for electric vehicle applications;Shrivastava;J Energy Storage,2023
5. Towards a smarter battery management system: a critical review on battery state of health monitoring methods;Xiong;J Power Sources,2018
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