Transformer Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
Author:
Affiliation:
1. School of Intelligent Transportation, Zhejiang Institute of Mechanical and Electrical Engineering, Hangzhou, China
2. Shuye Technology Company Ltd., Hangzhou, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09714323.pdf?arnumber=9714323
Reference66 articles.
1. A review on the key issues for lithium-ion battery management in electric vehicles
2. Dynamic Long Short-Term Memory Neural-Network- Based Indirect Remaining-Useful-Life Prognosis for Satellite Lithium-Ion Battery
3. Modeling Recurrence for Transformer
4. Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit
5. LSTM-Based Battery Remaining Useful Life Prediction With Multi-Channel Charging Profiles
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