Convolutional neural network based capacity estimation using random segments of the charging curves for lithium-ion batteries
出版年份 2021 全文链接
标题
Convolutional neural network based capacity estimation using random segments of the charging curves for lithium-ion batteries
作者
关键词
Lithium-ion battery, Capacity estimation, One-dimensional convolutional neural network, Random segment
出版物
ENERGY
Volume -, Issue -, Pages 120333
出版商
Elsevier BV
发表日期
2021-03-14
DOI
10.1016/j.energy.2021.120333
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。- Deep learning networks for capacity estimation for monitoring SOH of Li‐ion batteries for electric vehicles
- (2020) Kirandeep Kaur et al. INTERNATIONAL JOURNAL OF ENERGY RESEARCH
- Co-estimation of capacity and state-of-charge for lithium-ion batteries in electric vehicles
- (2019) Xiaoyu Li et al. ENERGY
- Online State-of-Health Estimation for Li-Ion Battery Using Partial Charging Segment Based on Support Vector Machine
- (2019) Xuning Feng et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- A novel capacity estimation method based on charging curve sections for lithium-ion batteries in electric vehicles
- (2019) Yuejiu Zheng et al. ENERGY
- A deep learning method for online capacity estimation of lithium-ion batteries
- (2019) Sheng Shen et al. Journal of Energy Storage
- Novel battery state-of-health online estimation method using multiple health indicators and an extreme learning machine
- (2018) Haihong Pan 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
- Gaussian Process Regression for In-situ Capacity Estimation of Lithium-ion Batteries
- (2018) Robert R. Richardson et al. IEEE Transactions on Industrial Informatics
- Performance and cost of materials for lithium-based rechargeable automotive batteries
- (2018) Richard Schmuch et al. Nature Energy
- State-of-health estimation for Li-ion batteries by combing the incremental capacity analysis method with grey relational analysis
- (2018) Xiaoyu Li et al. JOURNAL OF POWER SOURCES
- 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 Novel Estimation Method for the State of Health of Lithium-Ion Battery Using Prior Knowledge-Based Neural Network and Markov Chain
- (2018) Houde Dai et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Capacity estimation algorithm with a second-order differential voltage curve for Li-ion batteries with NMC cathodes
- (2017) Taedong Goh et al. ENERGY
- On-board state of health estimation of LiFePO4 battery pack through differential voltage analysis
- (2016) Limei Wang et al. APPLIED ENERGY
- State-of-health estimation of LiFePO 4 /graphite batteries based on a model using differential capacity
- (2016) Soichiro Torai et al. JOURNAL OF POWER SOURCES
- Online Capacity Estimation of Lithium-Ion Batteries Based on Novel Feature Extraction and Adaptive Multi-Kernel Relevance Vector Machine
- (2015) Yang Zhang et al. Energies
- Rapidly falling costs of battery packs for electric vehicles
- (2015) Björn Nykvist et al. Nature Climate Change
- Understanding Lithium Inventory Loss and Sudden Performance Fade in Cylindrical Cells during Cycling with Deep-Discharge Steps
- (2014) E. Sarasketa-Zabala et al. Journal of Physical Chemistry C
- A support vector machine-based state-of-health estimation method for lithium-ion batteries under electric vehicle operation
- (2014) Verena Klass et al. JOURNAL OF POWER SOURCES
- Synthesize battery degradation modes via a diagnostic and prognostic model
- (2012) Matthieu Dubarry et al. JOURNAL OF POWER SOURCES
- Prognostics of lithium-ion batteries based on Dempster–Shafer theory and the Bayesian Monte Carlo method
- (2011) Wei He et al. JOURNAL OF POWER SOURCES
- Electrical Energy Storage for the Grid: A Battery of Choices
- (2011) B. Dunn et al. SCIENCE
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