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 novel state-of-health estimation for the lithium-ion battery using a convolutional neural network and transformer model
Xinyu Gu et al.
ENERGY (2023)
A review on the state of health estimation methods of lead-acid batteries
Shida Jiang et al.
JOURNAL OF POWER SOURCES (2022)
Future Ageing Trajectory Prediction for Lithium-Ion Battery Considering the Knee Point Effect
Kailong Liu et al.
IEEE TRANSACTIONS ON ENERGY CONVERSION (2022)
Prognostics and health management of Lithium-ion battery using deep learning methods: A review
Ying Zhang et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2022)
An end-to-end neural network framework for state-of-health estimation and remaining useful life prediction of electric vehicle lithium batteries
Penghua Li et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2022)
A model cathode for mechanistic study of organosulfide electrochemistry in Li-organosulfide batteries
Wei Zhang et al.
JOURNAL OF ENERGY CHEMISTRY (2022)
A novel method for state of health estimation of lithium-ion batteries based on improved LSTM and health indicators extraction
Yan Ma et al.
ENERGY (2022)
Battery management strategies: An essential review for battery state of health monitoring techniques
Sunil K. Pradhan et al.
JOURNAL OF ENERGY STORAGE (2022)
Data efficient health prognostic for batteries based on sequential information-driven probabilistic neural network
Yunhong Che et al.
APPLIED ENERGY (2022)
State of health estimation of power batteries based on multi-feature fusion models using stacking algorithm
Gengfeng Liu et al.
ENERGY (2022)
A review of deep learning approach to predicting the state of health and state of charge of lithium-ion batteries
Kai Luo et al.
JOURNAL OF ENERGY CHEMISTRY (2022)
Deep learning enabled state of charge, state of health and remaining useful life estimation for smart battery management system: Methods, implementations, issues and prospects
M. S. Hossain Lipu et al.
JOURNAL OF ENERGY STORAGE (2022)
Battery state-of-health estimation based on a metabolic extreme learning machine combining degradation state model and error compensation
Lin Chen et al.
ENERGY (2021)
Lithium Battery State-of-Health Estimation via Differential Thermal Voltammetry With Gaussian Process Regression
Zhenpo Wang et al.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2021)
Incremental Capacity Analysis Applied on Electric Vehicles for Battery State-of-Health Estimation
Erik Schaltz et al.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS (2021)
A joint grey relational analysis based state of health estimation for lithium ion batteries considering temperature effects
Weiwei Qu et al.
JOURNAL OF ENERGY STORAGE (2021)
Lithium Battery SOH Monitoring and an SOC Estimation Algorithm Based on the SOH Result
Jong-Hyun Lee et al.
ENERGIES (2021)
Remaining Useful Life Assessment for Lithium-Ion Batteries Using CNN-LSTM-DNN Hybrid Method
Brahim Zraibi et al.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2021)
A semiconductor-electrochemistry model for design of high-rate Li ion battery
Wei Zhang et al.
JOURNAL OF ENERGY CHEMISTRY (2020)
State of health estimation for Li-ion battery via partial incremental capacity analysis based on support vector regression
Xiaoyu Li et al.
ENERGY (2020)
A review of the state of health for lithium -ion batteries: Research status and suggestions
Huixin Tian et al.
JOURNAL OF CLEANER PRODUCTION (2020)
One-shot parameter identification of the Thevenin's model for batteries: Methods and validation
Ning Tian et al.
JOURNAL OF ENERGY STORAGE (2020)
The application of hybrid energy storage system with electrified continuously variable transmission in battery electric vehicle
Jiageng Ruan et al.
ENERGY (2019)
Design and implementation of a battery management system with active charge balance based on the SOC and SOH online estimation
Hongbin Ren et al.
ENERGY (2019)
A review on prognostics and health management (PHM) methods of lithium-ion batteries
Huixing Meng et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2019)
Using a stacked residual LSTM model for sentiment intensity prediction
Jin Wang et al.
NEUROCOMPUTING (2018)
Correlation and variable importance in random forests
Baptiste Gregorutti et al.
STATISTICS AND COMPUTING (2017)
Densely Connected Convolutional Networks
Gao Huang et al.
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)
Performance analysis and SOH (state of health) evaluation of lithium polymer batteries through electrochemical impedance spectroscopy
Matteo Galeotti et al.
ENERGY (2015)
A support vector machine-based state-of-health estimation method for lithium-ion batteries under electric vehicle operation
Verena Klass et al.
JOURNAL OF POWER SOURCES (2014)
Using radial basis functions to approximate battery differential capacity and differential voltage
Jon P. Christophersen et al.
JOURNAL OF POWER SOURCES (2010)