研究论文
Remaining useful life prediction for lithium-ion batteries based on a hybrid model combining the long short-term memory and Elman neural networks
Xiaoyu Li, Lei Zhang, Zhenpo Wang, Peng Dong
Beijing Institute of Technology
来源Journal of Energy Storage
年份2018
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工程Battery Modeling and Management
Advancements in Battery Materials · Machine Fault Diagnosis Techniques
参考文献 36
Robust prognostics for state of health estimation of lithium-ion batteries based on an improved PSO–SVR model
被引 176Taichun Qin, Shengkui Zeng, Jianbin Guo · Microelectronics Reliability · 2015
A novel multistage Support Vector Machine based approach for Li ion battery remaining useful life estimation
被引 629Meru A. Patil, Piyush Tagade, Krishnan S. Hariharan · Applied Energy · 2015
Method for estimating capacity and predicting remaining useful life of lithium-ion battery
被引 162Chao Kun Hu, Gaurav Jain, Prabhakar A. Tamirisa · Applied Energy · 2014
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引用本文 443
A review on the long short-term memory model
被引 2,066Greg Van Houdt, Carlos Mosquera, Gonzalo Nápoles · Artificial Intelligence Review · 2020
Deep Learning for Time Series Forecasting: A Survey
被引 847José Francisco Torres, Dalil Hadjout, Abderrazak Sebaa · Big Data · 2020
State of health estimation for Li-Ion battery using incremental capacity analysis and Gaussian process regression
被引 485Xiaoyu Li, Changgui Yuan, Xiaohui Li · Energy · 2019
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