A deep learning method for lithium-ion battery remaining useful life prediction based on sparse segment data via cloud computing system
出版年份 2021 全文链接
标题
A deep learning method for lithium-ion battery remaining useful life prediction based on sparse segment data via cloud computing system
作者
关键词
Lithium-ion battery, Cloud computing system, Remaining useful life prediction, Residual convolutional neural network, Sparse segment data
出版物
ENERGY
Volume 241, Issue -, Pages 122716
出版商
Elsevier BV
发表日期
2021-12-02
DOI
10.1016/j.energy.2021.122716
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- A machine-learning prediction method of lithium-ion battery life based on charge process for different applications
- (2021) Yixin Yang APPLIED ENERGY
- Effect analysis on SOC values of the power lithium manganate battery during discharging process and its intelligent estimation
- (2021) Hongyan Zuo et al. ENERGY
- Application domain extension of incremental capacity-based battery SoH indicators
- (2021) Brian Ospina Agudelo et al. ENERGY
- Lithium-ion batteries remaining useful life prediction based on BLS-RVM
- (2021) Zewang Chen et al. ENERGY
- Cycle life test optimization for different Li-ion power battery formulations using a hybrid remaining-useful-life prediction method
- (2020) Jian Ma et al. APPLIED ENERGY
- State of health estimation for Li-ion battery via partial incremental capacity analysis based on support vector regression
- (2020) Xiaoyu Li et al. ENERGY
- Battery life estimation based on cloud data for electric vehicles
- (2020) Kai Li et al. JOURNAL OF POWER SOURCES
- Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles
- (2020) Rui Xiong et al. APPLIED ENERGY
- Control-oriented thermal-electrochemical modeling and validation of large size prismatic lithium battery for commercial applications
- (2020) Dongdong Li et al. ENERGY
- A novel data-driven method for predicting the circulating capacity of lithium-ion battery under random variable current
- (2020) Tingting Xu et al. ENERGY
- General Discharge Voltage Information Enabled Health Evaluation for Lithium-Ion Batteries
- (2020) Zhongwei Deng et al. IEEE-ASME TRANSACTIONS ON MECHATRONICS
- Data-driven prediction of battery cycle life before capacity degradation
- (2019) Kristen A. Severson et al. Nature Energy
- A review on various temperature-indication methods for Li-ion batteries
- (2019) L.H.J. Raijmakers et al. APPLIED ENERGY
- Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries
- (2019) Prashant Shrivastava et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Supervisory long-term prediction of state of available power for lithium-ion batteries in electric vehicles
- (2019) Lin Yang et al. APPLIED ENERGY
- State of health estimation for Li-Ion battery using incremental capacity analysis and Gaussian process regression
- (2019) Xiaoyu Li et al. ENERGY
- Incremental capacity analysis and differential voltage analysis based state of charge and capacity estimation for lithium-ion batteries
- (2018) Linfeng Zheng et al. ENERGY
- Online identification of lithium-ion battery state-of-health based on fast wavelet transform and cross D-Markov machine
- (2018) Yishan Cai et al. ENERGY
- Gaussian Process Regression for In-situ Capacity Estimation of Lithium-ion Batteries
- (2018) Robert R. Richardson et al. IEEE Transactions on Industrial Informatics
- Online Estimation of the Electrochemical Impedance Spectrum and Remaining Useful Life of Lithium-Ion Batteries
- (2018) Arijit Guha et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
- Long short-term memory recurrent neural network for remaining useful life prediction of lithium-ion batteries
- (2018) Yongzhi Zhang et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- A novel prediction method based on the support vector regression for the remaining useful life of lithium-ion batteries
- (2018) Qi Zhao et al. MICROELECTRONICS RELIABILITY
- Performance and cost of materials for lithium-based rechargeable automotive batteries
- (2018) Richard Schmuch et al. Nature Energy
- Random forest regression for online capacity estimation of lithium-ion batteries
- (2018) Yi Li et al. APPLIED ENERGY
- Degradation model and cycle life prediction for lithium-ion battery used in hybrid energy storage system
- (2018) Chang Liu et al. ENERGY
- Gaussian process regression for forecasting battery state of health
- (2017) Robert R. Richardson et al. JOURNAL OF POWER SOURCES
- The state of understanding of the lithium-ion-battery graphite solid electrolyte interphase (SEI) and its relationship to formation cycling
- (2016) Seong Jin An et al. CARBON
- Fast charging technique for high power LiFePO 4 batteries: A mechanistic analysis of aging
- (2016) D. Anseán et al. JOURNAL OF POWER SOURCES
- Deep learning
- (2015) Yann LeCun et al. NATURE
- An integrated unscented kalman filter and relevance vector regression approach for lithium-ion battery remaining useful life and short-term capacity prediction
- (2015) Xiujuan Zheng et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles
- (2014) Wladislaw Waag et al. JOURNAL OF POWER SOURCES
- Development of a lifetime prediction model for lithium-ion batteries based on extended accelerated aging test data
- (2012) Madeleine Ecker et al. JOURNAL OF POWER SOURCES
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search