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Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method

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  1. Fabian Rücker & Ilka Schoeneberger & Till Wilmschen & Ahmed Chahbaz & Philipp Dechent & Felix Hildenbrand & Elias Barbers & Matthias Kuipers & Jan Figgener & Dirk Uwe Sauer, 2022. "A Comprehensive Electric Vehicle Model for Vehicle-to-Grid Strategy Development," Energies, MDPI, vol. 15(12), pages 1-31, June.
  2. Benalcazar, Pablo & Kalka, Maciej & Kamiński, Jacek, 2024. "From consumer to prosumer: A model-based analysis of costs and benefits of grid-connected residential PV-battery systems," Energy Policy, Elsevier, vol. 191(C).
  3. Qian, Zhuoyi & Chen, Zhen & Pan, Ershun, 2026. "A transfer condition-focused model for battery capacity forecast," Reliability Engineering and System Safety, Elsevier, vol. 267(PB).
  4. 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).
  5. Ouyang, Tiancheng & Gong, Yubin & Ye, Jinlu & Deng, Qiaoyang & Su, Yingying, 2025. "State co-estimation for lithium-ion batteries based on multi-innovations online identification," Renewable and Sustainable Energy Reviews, Elsevier, vol. 210(C).
  6. 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).
  7. 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).
  8. 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).
  9. 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).
  10. Deng, Feiyue & Hao, Rujiang & Yang, Shaopu & Luo, Boxun & Sha, Jin, 2026. "Collaborative domain adaptation-based bidirectional temporal convolution network for cross-condition and cross-equipment remaining useful life prediction of rolling bearings," Reliability Engineering and System Safety, Elsevier, vol. 270(C).
  11. da Silva, Samuel Filgueira & Eckert, Jony Javorski & Corrêa, Fernanda Cristina & Silva, Fabrício Leonardo & Silva, Ludmila C.A. & Dedini, Franco Giuseppe, 2022. "Dual HESS electric vehicle powertrain design and fuzzy control based on multi-objective optimization to increase driving range and battery life cycle," Applied Energy, Elsevier, vol. 324(C).
  12. 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).
  13. Zhuang, Jihan & Bach, Amadeus & van Vlijmen, Bruis H.C. & Reichelstein, Stefan J. & Chueh, William & Onori, Simona & Benson, Sally M., 2025. "Technoeconomic decision support for second-life batteries," Applied Energy, Elsevier, vol. 390(C).
  14. 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).
  15. 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).
  16. 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.
  17. 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).
  18. 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).
  19. Atif Abdalla, Ammar & El Moursi, Mohamed Shawky & El-Fouly, Tarek H.M. & Al Hosani, Khalifa Hassan, 2026. "A state-of-the-art review of adaptive, predictive, synergistic, and degradation-aware power variability smoothing techniques in photovoltaic power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 230(C).
  20. 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).
  21. Deng, Weikun & Le, Hung & Nguyen, Khanh T.P. & Gogu, Christian & Medjaher, Kamal & Morio, Jérôme & Wu, Dazhong, 2025. "A Generic physics-informed machine learning framework for battery remaining useful life prediction using small early-stage lifecycle data," Applied Energy, Elsevier, vol. 384(C).
  22. 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).
  23. 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).
  24. Che, Yunhong & Zheng, Yusheng & Wu, Yue & Sui, Xin & Bharadwaj, Pallavi & Stroe, Daniel-Ioan & Yang, Yalian & Hu, Xiaosong & Teodorescu, Remus, 2022. "Data efficient health prognostic for batteries based on sequential information-driven probabilistic neural network," Applied Energy, Elsevier, vol. 323(C).
  25. 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).
  26. 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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