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A Hybrid Ensemble Deep Learning Approach for Early Prediction of Battery Remaining Useful Life

Qing Xu Min Wu Edwin Khoo Zhenghua Chen Xiaoli Li

自动化学报：英文版2023，Vol.10Issue(1)：P.177-187,11.

自动化学报：英文版2023，Vol.10Issue(1)：P.177-187,11.DOI:10.1109/JAS.2023.123024

A Hybrid Ensemble Deep Learning Approach for Early Prediction of Battery Remaining Useful Life

Qing Xu ¹Min Wu ²Edwin Khoo ¹Zhenghua Chen ²Xiaoli Li²

作者信息

1. the Institute for Infocomm Research,A*STAR,Singapore 138632,Singapore
2. the Institute for Infocomm Research,A*STAR,Singapore 138632,Singapore IEEE
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摘要

关键词

Deep learning/early prediction/lithium-ion battery/remaining useful life(RUL)

分类

信息技术与安全科学

引用本文复制引用

Qing Xu,Min Wu,Edwin Khoo,Zhenghua Chen,Xiaoli Li..A Hybrid Ensemble Deep Learning Approach for Early Prediction of Battery Remaining Useful Life[J].自动化学报：英文版,2023,10(1):P.177-187,11.

基金项目

supported by Agency for Science,Technology and Research(A*STAR)under the Career Development Fund(C210112037)。（A*STAR）

自动化学报：英文版

OACSCDCSTPCDEI

ISSN：2329-9266

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