Lithium-ion battery state of health monitoring based on an adaptive variable fractional order multivariate grey model
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DOI: 10.1016/j.energy.2023.129167
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References listed on IDEAS
- Lyu, Guangzheng & Zhang, Heng & Miao, Qiang, 2023. "Parallel State Fusion LSTM-based Early-cycle Stage Lithium-ion Battery RUL Prediction Under Lebesgue Sampling Framework," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
- Chen, Dan & Meng, Jinhao & Huang, Huanyang & Wu, Ji & Liu, Ping & Lu, Jiwu & Liu, Tianqi, 2022. "An Empirical-Data Hybrid Driven Approach for Remaining Useful Life prediction of lithium-ion batteries considering capacity diving," Energy, Elsevier, vol. 245(C).
- Li, Yihuan & Li, Kang & Liu, Xuan & Li, Xiang & Zhang, Li & Rente, Bruno & Sun, Tong & Grattan, Kenneth T.V., 2022. "A hybrid machine learning framework for joint SOC and SOH estimation of lithium-ion batteries assisted with fiber sensor measurements," Applied Energy, Elsevier, vol. 325(C).
- Xiong, Pingping & Li, Kailing & Shu, Hui & Wang, Junjie, 2021. "Forecast of natural gas consumption in the Asia-Pacific region using a fractional-order incomplete gamma grey model," Energy, Elsevier, vol. 237(C).
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- Feng, Tao & Guo, Wei & Wu, Jun & Meng, Zhenghua & Hua, Lin & Zhao, Feng & Zhao, Jialong, 2024. "Energy transition in the new era: The impact of renewable electric power on the life cycle assessment of automotive power batteries," Renewable Energy, Elsevier, vol. 236(C).
- Xiong, Xin & Wang, Yujie & Jiang, Cong & Zhang, Xingchen & Xiang, Haoxiang & Chen, Zonghai, 2024. "End-to-end deep learning powered battery state of health estimation considering multi-neighboring incomplete charging data," Energy, Elsevier, vol. 292(C).
- Fahmy, Hend M. & Alqahtani, Ayedh H. & Hasanien, Hany M., 2024. "Precise modeling of lithium-ion battery in industrial applications using Walrus optimization algorithm," Energy, Elsevier, vol. 294(C).
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Keywords
Lithium-ion batteries; State of health; Grey model; Multiple variables;All these keywords.
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