IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v325y2022ics0306261922010662.html

A hybrid machine learning framework for joint SOC and SOH estimation of lithium-ion batteries assisted with fiber sensor measurements

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Sulaiman, Mohd Herwan & Mustaffa, Zuriani & Zakaria, Nor Farizan & Saari, Mohd Mawardi, 2023. "Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle," Energy, Elsevier, vol. 279(C).
  2. Huang, Haichi & Bian, Chong & Wu, Mengdan & An, Dong & Yang, Shunkun, 2024. "A novel integrated SOC–SOH estimation framework for whole-life-cycle lithium-ion batteries," Energy, Elsevier, vol. 288(C).
  3. Ko, Chi-Jyun & Chen, Kuo-Ching & Chen, Chih-Hung, 2025. "Advantageous characteristics of constant voltage charging: A good option to estimate battery states for lithium-ion batteries," Energy, Elsevier, vol. 322(C).
  4. Chen, Mengyang & Chen, Xueyang & Fang, Weiwei & Hou, Yuyang & Liu, Lili & Ye, Jilei & Wu, Yuping, 2025. "High-accuracy state of health estimation for lithium-ion batteries via current fluctuation analysis and multi-feature fusion," Energy, Elsevier, vol. 339(C).
  5. Liu, Ruixue & Jiang, Benben, 2025. "A multi-time-resolution attention-based interaction network for co-estimation of multiple battery states," Applied Energy, Elsevier, vol. 381(C).
  6. Li, Yang & Gao, Guoqiang & Chen, Kui & He, Shuhang & Liu, Kai & Xin, Dongli & Luo, Yang & Long, Zhou & Wu, Guangning, 2025. "State-of-health prediction of lithium-ion batteries using feature fusion and a hybrid neural network model," Energy, Elsevier, vol. 319(C).
  7. Zhang, Hao & Gao, Jingyi & Kang, Le & Zhang, Yi & Wang, Licheng & Wang, Kai, 2023. "State of health estimation of lithium-ion batteries based on modified flower pollination algorithm-temporal convolutional network," Energy, Elsevier, vol. 283(C).
  8. Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Yang, Xiao & Fernandez, Carlos, 2023. "A hybrid probabilistic correction model for the state of charge estimation of lithium-ion batteries considering dynamic currents and temperatures," Energy, Elsevier, vol. 273(C).
  9. Xu, Zhicun & Xie, Naiming & Diao, Huakang, 2023. "Lithium-ion battery state of health monitoring based on an adaptive variable fractional order multivariate grey model," Energy, Elsevier, vol. 283(C).
  10. Yang, Yongsong & Xu, Yuchen & Nie, Yuwei & Li, Jianming & Liu, Shizhuo & Zhao, Lijun & Yu, Quanqing & Zhang, Chengming, 2024. "Deep transfer learning enables battery state of charge and state of health estimation," Energy, Elsevier, vol. 294(C).
  11. Fu, Shiyi & Fan, Hongtao & Jin, Zhaorui & Ji, Fan & Tao, Yulin & Dong, Yachao & Chen, Xunyuan & Shao, Minghao & Yuan, Shuyu & Wang, Yu & Sun, Yaojie, 2026. "Recent progress in state of health estimation for lithium-ion batteries: From laboratory to practical application," Renewable and Sustainable Energy Reviews, Elsevier, vol. 226(PB).
  12. Ye, Songtao & An, Dou & Wang, Chun & Zhang, Tao & Xi, Huan, 2025. "Towards fast multi-scale state estimation for retired battery reusing via Pareto-efficient," Energy, Elsevier, vol. 319(C).
  13. Tian, Aina & Yu, Haijun & Hu, Zhaoyu & Wang, Yuqin & Wu, Tiezhou & Jiang, Jiuchun, 2025. "A novel remaining useful life prediction method based on CNN-Attention combined with SMA-GPR," Energy, Elsevier, vol. 321(C).
  14. Bian, Chong & Duan, Zhiyu & Li, Daoyi & Yang, Shunkun & Feng, Junlan, 2026. "Joint state-of-charge and state-of-health estimation of lithium-ion batteries across varying operational stages on differing timescales with large language model: a multi-task prompting method," Reliability Engineering and System Safety, Elsevier, vol. 267(PB).
  15. Jianyu Zhang & Kang Li, 2024. "State-of-Health Estimation for Lithium-Ion Batteries in Hybrid Electric Vehicles—A Review," Energies, MDPI, vol. 17(22), pages 1-16, November.
  16. Ko, Chi-Jyun & Chen, Kuo-Ching, 2024. "Using tens of seconds of relaxation voltage to estimate open circuit voltage and state of health of lithium ion batteries," Applied Energy, Elsevier, vol. 357(C).
  17. Liu, Donglei & Wang, Shunli & Fan, Yongcun & Fernandez, Carlos & Blaabjerg, Frede, 2024. "An optimized multi-segment long short-term memory network strategy for power lithium-ion battery state of charge estimation adaptive wide temperatures," Energy, Elsevier, vol. 304(C).
  18. Li, Hao & Chen, Chao, 2025. "Lithium-ion battery SOH prediction based on multi-dimensional features and multi-model feature selector," Energy, Elsevier, vol. 331(C).
  19. Zhang, Xugang & Gao, Xiyuan & Duan, Linchao & Gong, Qingshan & Wang, Yan & Ao, Xiuyi, 2025. "A novel method for state of health estimation of lithium-ion batteries based on fractional-order differential voltage-capacity curve," Applied Energy, Elsevier, vol. 377(PA).
  20. Ruan, Haokai & Wei, Zhongbao & Shang, Wentao & Wang, Xuechao & He, Hongwen, 2023. "Artificial Intelligence-based health diagnostic of Lithium-ion battery leveraging transient stage of constant current and constant voltage charging," Applied Energy, Elsevier, vol. 336(C).
  21. Fu, Shiyi & Tao, Shengyu & Fan, Hongtao & He, Kun & Liu, Xutao & Tao, Yulin & Zuo, Junxiong & Zhang, Xuan & Wang, Yu & Sun, Yaojie, 2024. "Data-driven capacity estimation for lithium-ion batteries with feature matching based transfer learning method," Applied Energy, Elsevier, vol. 353(PA).
  22. 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).
  23. Molla Shahadat Hossain Lipu & Tahia F. Karim & Shaheer Ansari & Md. Sazal Miah & Md. Siddikur Rahman & Sheikh T. Meraj & Rajvikram Madurai Elavarasan & Raghavendra Rajan Vijayaraghavan, 2022. "Intelligent SOX Estimation for Automotive Battery Management Systems: State-of-the-Art Deep Learning Approaches, Open Issues, and Future Research Opportunities," Energies, MDPI, vol. 16(1), pages 1-31, December.
  24. Clerici, Davide, 2025. "POLISOC: A hybrid state of charge estimation algorithm for lithium-ion batteries based on electrical and mechanical measurements," Applied Energy, Elsevier, vol. 401(PC).
  25. Hou, Shujuan & Fan, Yue & Dou, Bowen & Li, Hai & Zhang, Qin & Chen, Hao-sen, 2025. "Strain feature-assisted state of health estimation for lithium-ion batteries," Energy, Elsevier, vol. 326(C).
  26. Sheng, Wenjuan & Wang, Junkai & Peng, G.D., 2025. "Enhanced strain assistance for SOC estimation of lithium-ion batteries using FBG sensors," Applied Energy, Elsevier, vol. 383(C).
  27. Wang, Yaxuan & Guo, Shilong & Cui, Yue & Deng, Liang & Zhao, Lei & Li, Junfu & Wang, Zhenbo, 2025. "A comprehensive review of machine learning-based state of health estimation for lithium-ion batteries: data, features, algorithms, and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 224(C).
  28. Liu, Yaru & Wang, Lei & Ng, Bing Feng, 2024. "A hybrid model-data-driven framework for inverse load identification of interval structures based on physics-informed neural network and improved Kalman filter algorithm," Applied Energy, Elsevier, vol. 359(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.