Remaining useful life prediction of lithium-ion batteries based on stacked autoencoder and gaussian mixture regression

2021 ◽  
pp. 103558
Author(s):  
Meng Wei ◽  
Min Ye ◽  
Qiao Wang ◽  
Xinxin-Xu ◽  
Jean Pierre Twajamahoro
Keyword(s):  
Lithium Ion Batteries ◽  
Life Prediction ◽  
Lithium Ion ◽  
Gaussian Mixture ◽  
Remaining Useful Life ◽  
Mixture Regression ◽  
Stacked Autoencoder ◽  
Useful Life

scholarly journals A critical review of improved deep learning methods for the remaining useful life prediction of lithium-ion batteries

2021 ◽  
Vol 7 ◽  
pp. 5562-5574 ◽  
Author(s):  
Shunli Wang ◽  
Siyu Jin ◽  
Dekui Bai ◽  
Yongcun Fan ◽  
Haotian Shi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Lithium Ion Batteries ◽  
Critical Review ◽  
Life Prediction ◽  
Lithium Ion ◽  
Remaining Useful Life ◽  
Learning Methods ◽  
Useful Life

Remaining useful life prediction for lithium-ion batteries based on an integrated health indicator

2018 ◽  
Vol 88-90 ◽  
pp. 1189-1194 ◽  
Author(s):  
Yongquan Sun ◽  
Xueling Hao ◽  
Michael Pecht ◽  
Yapeng Zhou
Keyword(s):  
Lithium Ion Batteries ◽  
Life Prediction ◽  
Lithium Ion ◽  
Remaining Useful Life ◽  
Health Indicator ◽  
Integrated Health ◽  
Useful Life

scholarly journals Residual Remaining Useful Life Prediction Method for Lithium-Ion Batteries in Satellite With Incomplete Healthy Historical Data

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 127788-127799 ◽  
Author(s):  
Jian Peng ◽  
Zhongbao Zhou ◽  
Jiongqi Wang ◽  
Di Wu ◽  
Yinman Guo
Keyword(s):  
Lithium Ion Batteries ◽  
Life Prediction ◽  
Historical Data ◽  
Prediction Method ◽  
Lithium Ion ◽  
Remaining Useful Life ◽  
Useful Life
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