Accurate and reliable state of charge estimation of lithium ion batteries using time-delayed recurrent neural networks through the identification of overexcited neurons
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DOI: 10.1016/j.apenergy.2021.117962
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- Cui, Zhenhua & Kang, Le & Li, Liwei & Wang, Licheng & Wang, Kai, 2022. "A hybrid neural network model with improved input for state of charge estimation of lithium-ion battery at low temperatures," Renewable Energy, Elsevier, vol. 198(C), pages 1328-1340.
- Guangheng Qi & Ning Ma & Kai Wang, 2024. "Predicting the Remaining Useful Life of Supercapacitors under Different Operating Conditions," Energies, MDPI, vol. 17(11), pages 1-16, May.
- Zhang, Zhengjie & Cao, Rui & Zheng, Yifan & Zhang, Lisheng & Guang, Haoran & Liu, Xinhua & Gao, Xinlei & Yang, Shichun, 2024. "Online state of health estimation for lithium-ion batteries based on gene expression programming," Energy, Elsevier, vol. 294(C).
- Kurucan, Mehmet & Özbaltan, Mete & Yetgin, Zeki & Alkaya, Alkan, 2024. "Applications of artificial neural network based battery management systems: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
- Saikia, Pranaynil & Bastida, Héctor & Ugalde-Loo, Carlos E., 2024. "An effective predictor of the dynamic operation of latent heat thermal energy storage units based on a non-linear autoregressive network with exogenous inputs," Applied Energy, Elsevier, vol. 360(C).
- Chun Wang & Chaocheng Fang & Aihua Tang & Bo Huang & Zhigang Zhang, 2022. "A Novel Ultracapacitor State-of-Charge Fusion Estimation Method for Electric Vehicles Considering Temperature Uncertainty," Energies, MDPI, vol. 15(12), pages 1-16, June.
- Zhan, Mingjing & Wu, Baigong & Xu, Guoqi & Li, Wenjuan & Liang, Darong & Zhang, Xiao, 2023. "Application of adaptive extended Kalman algorithm based on strong tracking fading factor in Stat-of-Charge estimation of lithium-ion battery," Energy, Elsevier, vol. 284(C).
- Chen, Junxiong & Zhang, Yu & Wu, Ji & Cheng, Weisong & Zhu, Qiao, 2023. "SOC estimation for lithium-ion battery using the LSTM-RNN with extended input and constrained output," Energy, Elsevier, vol. 262(PA).
- Zafar, Muhammad Hamza & Khan, Noman Mujeeb & Houran, Mohamad Abou & Mansoor, Majad & Akhtar, Naureen & Sanfilippo, Filippo, 2024. "A novel hybrid deep learning model for accurate state of charge estimation of Li-Ion batteries for electric vehicles under high and low temperature," Energy, Elsevier, vol. 292(C).
- Siyi Tao & Bo Jiang & Xuezhe Wei & Haifeng Dai, 2023. "A Systematic and Comparative Study of Distinct Recurrent Neural Networks for Lithium-Ion Battery State-of-Charge Estimation in Electric Vehicles," Energies, MDPI, vol. 16(4), pages 1-17, February.
- Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Li, Huan & Xu, Wenhua & Fernandez, Carlos, 2022. "An optimized relevant long short-term memory-squared gain extended Kalman filter for the state of charge estimation of lithium-ion batteries," Energy, Elsevier, vol. 260(C).
- Duan, Linchao & Zhang, Xugang & Jiang, Zhigang & Gong, Qingshan & Wang, Yan & Ao, Xiuyi, 2023. "State of charge estimation of lithium-ion batteries based on second-order adaptive extended Kalman filter with correspondence analysis," Energy, Elsevier, vol. 280(C).
- Zhu, Yunlong & Dong, Zhe & Cheng, Zhonghua & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2023. "Neural network extended state-observer for energy system monitoring," Energy, Elsevier, vol. 263(PA).
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Keywords
Lithium ion battery; State of charge; Time-delayed recurrent neural network; Overexcited neurons; Equivalent circuit models;All these keywords.
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