Hybrid Neural Network Method of the Lithium-Ion Battery Remaining Useful Life Prediction

Mapping Intimacies ◽

10.1007/978-981-16-7210-1_15 ◽

2021 ◽

pp. 159-167

Author(s):

Dexin Gao ◽

Xin Liu ◽

Qing Yang

Keyword(s):

Neural Network ◽

Lithium Ion Battery ◽

Life Prediction ◽

Lithium Ion ◽

Remaining Useful Life ◽

Hybrid Neural Network ◽

Neural Network Method ◽

Network Method ◽

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A hybrid approach based on decomposition algorithm and neural network for remaining useful life prediction of lithium-ion battery

Reliability Engineering & System Safety ◽

10.1016/j.ress.2021.108082 ◽

2021 ◽

pp. 108082

Author(s):

Ting Tang ◽

Huimei Yuan

Keyword(s):

Neural Network ◽

Lithium Ion Battery ◽

Life Prediction ◽

Hybrid Approach ◽

Lithium Ion ◽

Remaining Useful Life ◽

Decomposition Algorithm ◽

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An artificial neural network method for remaining useful life prediction of equipment subject to condition monitoring

Journal of Intelligent Manufacturing ◽

10.1007/s10845-009-0356-9 ◽

2009 ◽

Vol 23 (2) ◽

pp. 227-237 ◽

Author(s):

Zhigang Tian

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Condition Monitoring ◽

Life Prediction ◽

Remaining Useful Life ◽

Neural Network Method ◽

Network Method ◽

Artificial Neural Network Method ◽

Useful Life ◽

Artificial Neural

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A Comparative Analysis of Lithium Ion Battery Input Profiles for Remaining Useful Life Prediction by Cascade Forward Neural Network

2021 IEEE World AI IoT Congress (AIIoT) ◽

10.1109/aiiot52608.2021.9454234 ◽

2021 ◽

Author(s):

Shaheer Ansari ◽

Afida Ayob ◽

M.S. Hossain Lipu ◽

Mohamad Hanif Md Saad ◽

Aini Hussain

Keyword(s):

Neural Network ◽

Comparative Analysis ◽

Lithium Ion Battery ◽

Life Prediction ◽

Lithium Ion ◽

Remaining Useful Life ◽

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Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network

Applied Energy ◽

10.1016/j.apenergy.2019.113626 ◽

2019 ◽

Vol 253 ◽

pp. 113626 ◽

Author(s):

Guijun Ma ◽

Yong Zhang ◽

Cheng Cheng ◽

Beitong Zhou ◽

Pengchao Hu ◽

...

Keyword(s):

Neural Network ◽

Lithium Ion Batteries ◽

Life Prediction ◽

Lithium Ion ◽

Nearest Neighbors ◽

Remaining Useful Life ◽

Hybrid Neural Network ◽

Useful Life ◽

False Nearest Neighbors

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Remaining Useful Life Prediction of Power Lithium-Ion Battery based on Artificial Neural Network Model

Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017) ◽

10.2991/mecae-17.2017.70 ◽

2017 ◽

Author(s):

Enguang Hou ◽

Xin Qiao ◽

Guangmin Liu

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Lithium Ion Battery ◽

Network Model ◽

Neural Network Model ◽

Artificial Neural Network Model ◽

Life Prediction ◽

Lithium Ion ◽

Remaining Useful Life ◽

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Remaining useful life prediction of lithium-ion battery using a novel particle filter framework with grey neural network

Energy ◽

10.1016/j.energy.2021.122581 ◽

2021 ◽

pp. 122581

Author(s):

Lin Chen ◽

Yunhui Ding ◽

Bohao Liu ◽

Shuxiao Wu ◽

Yaodong Wang ◽

...

Keyword(s):

Neural Network ◽

Particle Filter ◽

Lithium Ion Battery ◽

Life Prediction ◽

Lithium Ion ◽

Remaining Useful Life ◽

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Remaining Useful Life Prediction of Lithium-ion Battery Based on Unscented Kalman Filter and Back propagation Neural Network

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) ◽

10.1109/ddcls.2019.8908952 ◽

2019 ◽

Author(s):

Zhouxiao Xiao ◽

Huajing Fang ◽

Zheng Li ◽

Yang Chang

Keyword(s):

Neural Network ◽

Kalman Filter ◽

Lithium Ion Battery ◽

Life Prediction ◽

Unscented Kalman Filter ◽

Back Propagation ◽

Lithium Ion ◽

Back Propagation Neural Network ◽

Remaining Useful Life ◽

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A Feed-Forward Backpropagation Neural Network Method for Remaining Useful Life Prediction of Francis Turbines

Proceedings of the 3rd World Congress on Mechanical, Chemical, and Material Engineering ◽

10.11159/icmie17.126 ◽

2017 ◽

Author(s):

Alvaro Aguinaga ◽

Xianwu Luo ◽

Víctor Hidalgo ◽

Edgar Cando ◽

Fredy Llulluna

Keyword(s):

Neural Network ◽

Life Prediction ◽

Remaining Useful Life ◽

Backpropagation Neural Network ◽

Feed Forward ◽

Neural Network Method ◽

Network Method ◽

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Remaining useful life prediction for lithium-ion battery by combining an improved particle filter with sliding-window gray model

Energy Reports ◽

10.1016/j.egyr.2020.07.026 ◽

2020 ◽

Vol 6 ◽

pp. 2086-2093

Author(s):

Lin Chen ◽

Jingjing An ◽

Huimin Wang ◽

Mo Zhang ◽

Haihong Pan

Keyword(s):

Particle Filter ◽

Lithium Ion Battery ◽

Life Prediction ◽

Lithium Ion ◽

Sliding Window ◽

Remaining Useful Life ◽

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Novel Statistical Analysis Approach for Remaining Useful Life Prediction of Lithium-Ion Battery

10.1109/icccnt51525.2021.9579982 ◽

2021 ◽

Author(s):

Yash S. Jain ◽

Atharva D. Veer ◽

Gaurav S. Sawant ◽

Yash R. Jain ◽

Sandeep S. Udmale

Keyword(s):

Statistical Analysis ◽

Lithium Ion Battery ◽

Life Prediction ◽

Lithium Ion ◽

Remaining Useful Life ◽

Analysis Approach ◽

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