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Lithium-Ion Battery State of Health Monitoring Based on Ensemble Learning

  • Published:2019 Issue: Volume:7 Page:8754-8762
  • ISSN:2169-3536
  • Container-title:IEEE Access
  • language:
  • Short-container-title:IEEE Access

Author:

Li YuanyuanORCID,Zhong Shouming,Zhong Qishui,Shi Kaibo

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Dongguan Science and Technology Plan

Opening Fund of Geomathematics Key Laboratory of Sichuan Province

Sichuan Science and Technology Plan Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 70 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Estimation of lithium-ion battery health state using MHATTCN network with multi-health indicators inputs;Scientific Reports;2024-08-08

2. Machine Learning Analysis of Lithium-Ion Battery Behavior and Prediction;2024 International Conference on Circuit, Systems and Communication (ICCSC);2024-06-28

3. Comparative Analysis of State-of-Health Estimation Techniques;Advances in Mechatronics and Mechanical Engineering;2024-06-21

4. State-of-Health Estimation of Li-ion Batteries using Multiple Linear Regression and Optimized Feature Extraction based on Principal Component Analysis;2024 IEEE International Conference on Prognostics and Health Management (ICPHM);2024-06-17

5. Robotised disassembly of electric vehicle batteries: A systematic literature review;Journal of Manufacturing Systems;2024-06
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