Impedance-based capacity estimation for lithium-ion batteries using generative adversarial network
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Impedance-based capacity estimation for lithium-ion batteries using generative adversarial network
Authors
Keywords
Lithium-ion battery, State of health, Electrochemical impedance spectroscopy, Information maximizing generative adversarial network
Journal
APPLIED ENERGY
Volume 308, Issue -, Pages 118317
Publisher
Elsevier BV
Online
2021-12-21
DOI
10.1016/j.apenergy.2021.118317
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Electrochemical impedance spectroscopy study of lithium-ion capacitors: Modeling and capacity fading mechanism
- (2021) Xiaohu Zhang et al. JOURNAL OF POWER SOURCES
- A simplification of the time-domain equivalent circuit model for lithium-ion batteries based on low-frequency electrochemical impedance spectra
- (2021) Yuejiu Zheng et al. JOURNAL OF POWER SOURCES
- Forecasting state-of-health of lithium-ion batteries using variational long short-term memory with transfer learning
- (2021) Seongyoon Kim et al. Journal of Energy Storage
- Digital twin for battery systems: Cloud battery management system with online state-of-charge and state-of-health estimation
- (2020) Weihan Li et al. Journal of Energy Storage
- State of charge estimation of lithium-ion batteries using hybrid autoencoder and Long Short Term Memory neural networks
- (2020) Mohammad Fasahat et al. JOURNAL OF POWER SOURCES
- Implementation of generative adversarial network-CLS combined with bidirectional long short-term memory for lithium-ion battery state prediction
- (2020) Haoliang Zhang et al. Journal of Energy Storage
- Application of electrochemical impedance spectroscopy to commercial Li-ion cells: A review
- (2020) Nina Meddings et al. JOURNAL OF POWER SOURCES
- State-of-health estimators coupled to a random forest approach for lithium-ion battery aging factor ranking
- (2020) Kodjo S.R. Mawonou et al. JOURNAL OF POWER SOURCES
- Big data driven lithium-ion battery modeling method based on SDAE-ELM algorithm and data pre-processing technology
- (2019) Shuangqi Li et al. APPLIED ENERGY
- In situ monitoring of lithium-ion battery degradation using an electrochemical model
- (2019) Chao Lyu et al. APPLIED ENERGY
- Concept of reliability and safety assessment of lithium-ion batteries in electric vehicles: Basics, progress, and challenges
- (2019) Foad H. Gandoman et al. APPLIED ENERGY
- An enhanced multi-state estimation hierarchy for advanced lithium-ion battery management
- (2019) Xiaosong Hu et al. APPLIED ENERGY
- Online state-of-health estimation for lithium-ion batteries using constant-voltage charging current analysis
- (2018) Jufeng Yang et al. APPLIED ENERGY
- Comparative study of reduced order equivalent circuit models for on-board state-of-available-power prediction of lithium-ion batteries in electric vehicles
- (2018) Alexander Farmann et al. APPLIED ENERGY
- Remaining Useful Life Prediction for Lithium-ion Battery: A Deep Learning Approach
- (2018) Lei Ren et al. IEEE Access
- Towards a smarter battery management system: A critical review on battery state of health monitoring methods
- (2018) Rui Xiong et al. JOURNAL OF POWER SOURCES
- A data-driven remaining capacity estimation approach for lithium-ion batteries based on charging health feature extraction
- (2018) Peiyao Guo et al. JOURNAL OF POWER SOURCES
- A comparative study of global optimization methods for parameter identification of different equivalent circuit models for Li-ion batteries
- (2018) Xin Lai et al. ELECTROCHIMICA ACTA
- A Comparison between Electrochemical Impedance Spectroscopy and Incremental Capacity-Differential Voltage as Li-ion Diagnostic Techniques to Identify and Quantify the Effects of Degradation Modes within Battery Management Systems
- (2017) Carlos Pastor-Fernández et al. JOURNAL OF POWER SOURCES
- Gaussian process regression for forecasting battery state of health
- (2017) Robert R. Richardson et al. JOURNAL OF POWER SOURCES
- A comprehensive review of lithium-ion batteries used in hybrid and electric vehicles at cold temperatures
- (2016) J. Jaguemont et al. APPLIED ENERGY
- Analysis of Lithium-Ion Battery Models Based on Electrochemical Impedance Spectroscopy
- (2016) Uwe Westerhoff et al. Energy Technology
- 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
- Resolving Losses at the Negative Electrode in All-Vanadium Redox Flow Batteries Using Electrochemical Impedance Spectroscopy
- (2014) Che-Nan Sun et al. JOURNAL OF THE ELECTROCHEMICAL SOCIETY
- Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles
- (2013) Habiballah Rahimi-Eichi et al. IEEE Industrial Electronics Magazine
- Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods
- (2012) Adnan Nuhic et al. JOURNAL OF POWER SOURCES
- Characterization of high-power lithium-ion batteries by electrochemical impedance spectroscopy. I. Experimental investigation
- (2011) D. Andre et al. JOURNAL OF POWER SOURCES
- A review on prognostics and health monitoring of Li-ion battery
- (2011) Jingliang Zhang et al. JOURNAL OF POWER SOURCES
- Electrical Energy Storage for the Grid: A Battery of Choices
- (2011) B. Dunn et al. SCIENCE
- Building better batteries
- (2008) M. Armand et al. NATURE
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started