Related references
Note: Only part of the references are listed.State of health estimation for lithium battery random charging process based on CNN-GRU method
Yuxuan Zheng et al.
ENERGY REPORTS (2023)
A statistical assessment of the state-of-health of LiFePO4 cells harvested from a hybrid-electric vehicle battery pack
Katrina Ramirez-Meyers et al.
JOURNAL OF ENERGY STORAGE (2023)
A hybrid CNN-GRU based probabilistic model for load forecasting from individual household to commercial building
Ming-Chuan Chiu et al.
ENERGY REPORTS (2023)
An encoder-decoder model based on deep learning for state of health estimation of lithium-ion battery
Qingrui Gong et al.
JOURNAL OF ENERGY STORAGE (2022)
Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation
Jiangong Zhu et al.
NATURE COMMUNICATIONS (2022)
Lithium-ion battery charging optimization based on electrical, thermal and aging mechanism models
Jiaqiang Tian et al.
ENERGY REPORTS (2022)
Online state of health estimation for lithium-ion batteries based on a dual self-attention multivariate time series prediction network
Huanyu Wang et al.
ENERGY REPORTS (2022)
Adaptive State-of-Charge Estimation for Lithium-Ion Batteries by Considering Capacity Degradation
Peipei Xu et al.
ELECTRONICS (2021)
Predicting battery end of life from solar off-grid system field data using machine learning
Antti Aitio et al.
JOULE (2021)
Early prediction of battery lifetime via a machine learning based framework
Zicheng Fei et al.
ENERGY (2021)
The challenge and opportunity of battery lifetime prediction from field data
Valentin Sulzer et al.
JOULE (2021)
Incremental Capacity Analysis as a State of Health Estimation Method for Lithium-Ion Battery Modules with Series-Connected Cells
Amelie Krupp et al.
BATTERIES-BASEL (2021)
State of Charge Estimation of Lithium-Ion Batteries Based on Temporal Convolutional Network and Transfer Learning
Yuefeng Liu et al.
IEEE ACCESS (2021)
SOH Estimation of Lithium-Ion Battery Pack Based on Integrated State Information from Cells
Xiaohong Wang et al.
APPLIED SCIENCES-BASEL (2020)
Fast Charge-Driven Li Plating on Anode and Structural Degradation of Cathode
Seoung-Bum Son et al.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2020)
Data-driven prediction of battery cycle life before capacity degradation
Kristen A. Severson et al.
NATURE ENERGY (2019)
Design and calibration of a semi-empirical model for capturing dominant aging mechanisms of a PbA battery
Kaveh Khodadadi Sadabadi et al.
JOURNAL OF ENERGY STORAGE (2019)
A semi-empirical, electrochemistry-based model for Li-ion battery performance prediction over lifetime
Maria Varini et al.
JOURNAL OF ENERGY STORAGE (2019)
Developing a real-time data-driven battery health diagnosis method, using time and frequency domain condition indicators
S. Khaleghi et al.
APPLIED ENERGY (2019)
Bayesian hierarchical model-based prognostics for lithium-ion batteries
Madhav Mishra et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2018)
Remaining Useful Life Prediction for Lithium-Ion Battery: A Deep Learning Approach
Lei Ren et al.
IEEE ACCESS (2018)
Modeling Solid-Electrolyte Interphase (SEI) Fracture: Coupled Mechanical/Chemical Degradation of the Lithium Ion Battery
Rutooj D. Deshpande et al.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2017)
State-of-health monitoring of lithium-ion battery modules and packs via incremental capacity peak tracking
Caihao Weng et al.
APPLIED ENERGY (2016)
Promise and reality of post-lithium-ion batteries with high energy densities
Jang Wook Choi et al.
NATURE REVIEWS MATERIALS (2016)
Understanding aging mechanisms in lithium-ion battery packs: From cell capacity loss to pack capacity evolution
Yuejiu Zheng et al.
JOURNAL OF POWER SOURCES (2015)