State‐of‐Health Prediction for Lithium‐Ion Batteries Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise‐Gate Recurrent Unit Fusion Model-Reference-Cited by-同舟云学术

State‐of‐Health Prediction for Lithium‐Ion Batteries Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise‐Gate Recurrent Unit Fusion Model

Published:2022-02-25 Issue:4 Volume:10 Page:2100767
ISSN:2194-4288
Container-title:Energy Technology
language:en
Short-container-title:Energy Tech

Author:

Xia Fei¹,Wang Kangan¹^ORCID,Chen Jiajun²

Affiliation:

1. College of Automation Engineering Shanghai University of Electric Power Shanghai 200090 China

2. Department of Battery Development Pegasus Power Energy Co., Ltd. Hangzhou 310019 China

Publisher

Wiley

Subject

General Energy

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ente.202100767

Reference56 articles.

1. History, Evolution, and Future Status of Energy Storage

2. Recent Progress in Advanced Materials for Lithium Ion Batteries

3. Hydrothermal synthesis of lithium iron phosphate

4. Critical review of state of health estimation methods of Li-ion batteries for real applications

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