Battery Health Estimation Based on Multi-domain Transfer Learning-Reference-Cited by-同舟云学术

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Battery Health Estimation Based on Multi-domain Transfer Learning

Published:2023 Issue: Volume: Page:1-13
ISSN:0885-8993
Container-title:IEEE Transactions on Power Electronics
language:
Short-container-title:IEEE Trans. Power Electron.

Author:

Sheng Hanmin¹,Ray Biplob²,Kayamboo Shaben²,Xu Xintao¹,Wang Shafei³

Affiliation:

1. School of Automation Engineering, University of Science and Technology, Chengdu, China

2. Centre for Machine Learning Networks and Educational Technologies (CMLNET), College of ICT, School of Engineering and Technology, CQUniversity, Australia

3. Laboratory of Electromagnetic Space Cognition and Intelligent Control, Beijing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/63/4359240/10373113.pdf?arnumber=10373113

Cited by 2 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. Source-Free Dynamic Weighted Federated Transfer Learning for State-of-Health Estimation of Lithium-Ion Batteries With Data Privacy;IEEE Transactions on Power Electronics;2024-11

2. Enhancing data-driven-based state of health estimation for diverse battery applications through effective feature construction;Energy;2024-11

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