Lithium-ion batteries life prediction method basedon degenerative characters and improved particle filter

2015 IEEE Conference on Prognostics and Health Management (PHM) ◽

10.1109/icphm.2015.7245051 ◽

2015 ◽

Author(s):

Hongzheng Fang ◽

Huanzhen Fan ◽

Haodong Ma ◽

Hui Shi ◽

Yunfan Dong

Keyword(s):

Particle Filter ◽

Lithium Ion Batteries ◽

Life Prediction ◽

Prediction Method ◽

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Remaining Useful Life Prediction of Lithium-Ion Batteries Using Neural Network and Bat-Based Particle Filter

IEEE Access ◽

10.1109/access.2019.2913163 ◽

2019 ◽

Vol 7 ◽

pp. 54843-54854 ◽

Author(s):

Yi Wu ◽

Wei Li ◽

Youren Wang ◽

Kai Zhang

Keyword(s):

Neural Network ◽

Particle Filter ◽

Lithium Ion Batteries ◽

Life Prediction ◽

Lithium Ion ◽

Remaining Useful Life ◽

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

IEEE Access ◽

10.1109/access.2019.2938060 ◽

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 ◽

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A remaining useful life prediction approach for lithium-ion batteries using Kalman filter and an improved particle filter

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) ◽

10.1109/icphm.2016.7542847 ◽

2016 ◽

Author(s):

Baohua Mo ◽

Jingsong Yu ◽

Diyin Tang ◽

Hao Liu ◽

Jingsong Yu

Keyword(s):

Kalman Filter ◽

Particle Filter ◽

Lithium Ion Batteries ◽

Life Prediction ◽

Lithium Ion ◽

Remaining Useful Life ◽

Useful Life ◽

Prediction Approach

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A novel RUL prediction method for Lithium-ion Batteries via hybrid modeling and BAS based particle filter

10.23919/ccc52363.2021.9550743 ◽

2021 ◽

Author(s):

Ning He ◽

Cheng Qian ◽

Ruoxia Li

Keyword(s):

Particle Filter ◽

Lithium Ion Batteries ◽

Prediction Method ◽

Lithium Ion ◽

Hybrid Modeling

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An Integrated Method for Lithium-ion Batteries Remaining Useful Life Prediction Based on Unscented Particle Filter and Relevance Vector Machine

10.23919/ccc52363.2021.9549315 ◽

2021 ◽

Author(s):

Meng Jiang ◽

Zhenxing Liu ◽

Yong Zhang ◽

Jie He ◽

Yujie Chen

Keyword(s):

Particle Filter ◽

Lithium Ion Batteries ◽

Life Prediction ◽

Lithium Ion ◽

Relevance Vector Machine ◽

Remaining Useful Life ◽

Integrated Method ◽

Unscented Particle Filter ◽

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Cycle life prediction method of lithium ion batteries for new energy electric vehicles

10.1109/icscde54196.2021.00034 ◽

2021 ◽

Author(s):

Runze Gao ◽

Xiao Li ◽

Haitao Yu

Keyword(s):

Lithium Ion Batteries ◽

Electric Vehicles ◽

Life Prediction ◽

Prediction Method ◽

Lithium Ion ◽

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Remaining useful life prediction of aircraft lithium-ion batteries based on F-distribution particle filter and kernel smoothing algorithm

Chinese Journal of Aeronautics ◽

10.1016/j.cja.2020.01.007 ◽

2020 ◽

Vol 33 (5) ◽

pp. 1517-1531

Author(s):

Kai ZHANG ◽

Peng ZHAO ◽

Canfei SUN ◽

Youren WANG ◽

Zewang CHEN

Keyword(s):

Particle Filter ◽

Lithium Ion Batteries ◽

Life Prediction ◽

Kernel Smoothing ◽

Lithium Ion ◽

Remaining Useful Life ◽

Smoothing Algorithm ◽

F Distribution ◽

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A life-prediction method for lithium-ion batteries based on a fusion model and an attention mechanism

Optoelectronics Letters ◽

10.1007/s11801-020-9214-y ◽

2020 ◽

Vol 16 (6) ◽

pp. 410-417

Author(s):

Xian-bao Wang ◽

Fei-teng Wu ◽

Ming-hai Yao

Keyword(s):

Lithium Ion Batteries ◽

Life Prediction ◽

Prediction Method ◽

Lithium Ion ◽

Attention Mechanism ◽

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Remaining Useful Life Prediction of Lithium-Ion Batteries using Semi-Empirical Model and Bat-Based Particle Filter

2020 IEEE International Symposium on Circuits and Systems (ISCAS) ◽

10.1109/iscas45731.2020.9180516 ◽

2020 ◽

Author(s):

Yucheng Lian ◽

Jing V. Wang ◽

Xiangtian Deng ◽

Jianqiang Kang ◽

Guorong Zhu ◽

...

Keyword(s):

Particle Filter ◽

Lithium Ion Batteries ◽

Empirical Model ◽

Life Prediction ◽

Lithium Ion ◽

Remaining Useful Life ◽

Useful Life ◽

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Lithium-ion batteries remaining useful life prediction using Wiener process and unscented particle filter

Journal of Power Electronics ◽

10.1007/s43236-019-00016-3 ◽

2019 ◽

Vol 20 (1) ◽

pp. 270-278 ◽

Author(s):

Ranran Wang ◽

Hailin Feng

Keyword(s):

Particle Filter ◽

Lithium Ion Batteries ◽

Wiener Process ◽

Life Prediction ◽

Lithium Ion ◽

Remaining Useful Life ◽

Unscented Particle Filter ◽

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