Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method
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DOI: 10.1016/j.apenergy.2019.113591
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- Hsu, Chia-Wei & Xiong, Rui & Chen, Nan-Yow & Li, Ju & Tsou, Nien-Ti, 2022. "Deep neural network battery life and voltage prediction by using data of one cycle only," Applied Energy, Elsevier, vol. 306(PB).
- Zhao, Dao & Zhou, Zhijie & Tang, Shuaiwen & Cao, You & Wang, Jie & Zhang, Peng & Zhang, Yijun, 2022. "Online estimation of satellite lithium-ion battery capacity based on approximate belief rule base and hidden Markov model," Energy, Elsevier, vol. 256(C).
- Li, Xiaoyu & Huang, Zhijia & Tian, Jindong & Tian, Yong, 2021. "State-of-charge estimation tolerant of battery aging based on a physics-based model and an adaptive cubature Kalman filter," Energy, Elsevier, vol. 220(C).
- Tu, Hao & Moura, Scott & Wang, Yebin & Fang, Huazhen, 2023. "Integrating physics-based modeling with machine learning for lithium-ion batteries," Applied Energy, Elsevier, vol. 329(C).
- Li, Shuangqi & He, Hongwen & Su, Chang & Zhao, Pengfei, 2020. "Data driven battery modeling and management method with aging phenomenon considered," Applied Energy, Elsevier, vol. 275(C).
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- Zhou, Danhua & Wang, Bin & Zhu, Chao & Zhou, Fang & Wu, Hong, 2023. "A light-weight feature extractor for lithium-ion battery health prognosis," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
- Gong, Dongliang & Gao, Ying & Kou, Yalin & Wang, Yurang, 2022. "State of health estimation for lithium-ion battery based on energy features," Energy, Elsevier, vol. 257(C).
- Dixon, James & Andersen, Peter Bach & Bell, Keith & Træholt, Chresten, 2020. "On the ease of being green: An investigation of the inconvenience of electric vehicle charging," Applied Energy, Elsevier, vol. 258(C).
- Shaojie Ai & Jia Song & Guobiao Cai, 2022. "Sequence-to-Sequence Remaining Useful Life Prediction of the Highly Maneuverable Unmanned Aerial Vehicle: A Multilevel Fusion Transformer Network Solution," Mathematics, MDPI, vol. 10(10), pages 1-23, May.
- Maheshwari, Arpit & Paterakis, Nikolaos G. & Santarelli, Massimo & Gibescu, Madeleine, 2020. "Optimizing the operation of energy storage using a non-linear lithium-ion battery degradation model," Applied Energy, Elsevier, vol. 261(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).
- Chen, Zewang & Shi, Na & Ji, Yufan & Niu, Mu & Wang, Youren, 2021. "Lithium-ion batteries remaining useful life prediction based on BLS-RVM," Energy, Elsevier, vol. 234(C).
- Kim, Sung Wook & Oh, Ki-Yong & Lee, Seungchul, 2022. "Novel informed deep learning-based prognostics framework for on-board health monitoring of lithium-ion batteries," Applied Energy, Elsevier, vol. 315(C).
- Tian, Jiaqiang & Xu, Ruilong & Wang, Yujie & Chen, Zonghai, 2021. "Capacity attenuation mechanism modeling and health assessment of lithium-ion batteries," Energy, Elsevier, vol. 221(C).
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- Hong, Jichao & Wang, Zhenpo & Qu, Changhui & Zhou, Yangjie & Shan, Tongxin & Zhang, Jinghan & Hou, Yankai, 2022. "Investigation on overcharge-caused thermal runaway of lithium-ion batteries in real-world electric vehicles," Applied Energy, Elsevier, vol. 321(C).
- Li, Xiaoyu & Zhang, Zuguang & Wang, Wenhui & Tian, Yong & Li, Dong & Tian, Jindong, 2020. "Multiphysical field measurement and fusion for battery electric-thermal-contour performance analysis," Applied Energy, Elsevier, vol. 262(C).
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Keywords
Lithium-ion batteries; Model migration; Bayesian Monte Carlo; Aging trajectory prediction; State-of-health;All these keywords.
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