A Novel Data-Driven Fast Capacity Estimation of Spent Electric Vehicle Lithium-ion Batteries
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- Xiong, Rui & Sun, Fengchun & Chen, Zheng & He, Hongwen, 2014. "A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion olymer battery in electric vehicles," Applied Energy, Elsevier, vol. 113(C), pages 463-476.
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- Yang Zhang & Bo Guo, 2015. "Online Capacity Estimation of Lithium-Ion Batteries Based on Novel Feature Extraction and Adaptive Multi-Kernel Relevance Vector Machine," Energies, MDPI, vol. 8(11), pages 1-19, November.
- Jinsong Yu & Baohua Mo & Diyin Tang & Jie Yang & Jiuqing Wan & Jingjing Liu, 2017. "Indirect State-of-Health Estimation for Lithium-Ion Batteries under Randomized Use," Energies, MDPI, vol. 10(12), pages 1-19, December.
- Yong Tian & Qianyuan Dong & Jindong Tian & Xiaoyu Li, 2023. "Capacity Estimation of Lithium-Ion Batteries Based on Multiple Small Voltage Sections and BP Neural Networks," Energies, MDPI, vol. 16(2), pages 1-18, January.
- Weiping Diao & Jiuchun Jiang & Hui Liang & Caiping Zhang & Yan Jiang & Leyi Wang & Biqiang Mu, 2016. "Flexible Grouping for Enhanced Energy Utilization Efficiency in Battery Energy Storage Systems," Energies, MDPI, vol. 9(7), pages 1-15, June.
- Sebastian Bräuer & Florian Plenter & Benjamin Klör & Markus Monhof & Daniel Beverungen & Jörg Becker, 2020. "Transactions for trading used electric vehicle batteries: theoretical underpinning and information systems design principles," Business Research, Springer;German Academic Association for Business Research, vol. 13(1), pages 311-342, April.
- Liu, Yisheng & Fan, Guodong & Zhou, Boru & Chen, Shun & Sun, Ziqiang & Wang, Yansong & Zhang, Xi, 2023. "Rapid and flexible battery capacity estimation using random short-time charging segments based on residual convolutional networks," Applied Energy, Elsevier, vol. 351(C).
- Xuning Feng & Caihao Weng & Xiangming He & Li Wang & Dongsheng Ren & Languang Lu & Xuebing Han & Minggao Ouyang, 2018. "Incremental Capacity Analysis on Commercial Lithium-Ion Batteries using Support Vector Regression: A Parametric Study," Energies, MDPI, vol. 11(9), pages 1-21, September.
- He, Hongwen & Xiong, Rui & Peng, Jiankun, 2016. "Real-time estimation of battery state-of-charge with unscented Kalman filter and RTOS μCOS-II platform," Applied Energy, Elsevier, vol. 162(C), pages 1410-1418.
- Hong Zhang & Li Zhao & Yong Chen, 2015. "A Lossy Counting-Based State of Charge Estimation Method and Its Application to Electric Vehicles," Energies, MDPI, vol. 8(12), pages 1-18, December.
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Keywords
lithium-ion batteries; second-life; fast capacity estimation; artificial neural networks; robustness;All these keywords.
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