IDEAS home Printed from https://ideas.repec.org/r/gam/jeners/v16y2023i8p3393-d1121721.html
   My bibliography  Save this item

State of Health Estimation of Lithium-Ion Battery Based on Electrochemical Impedance Spectroscopy

Citations

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


Cited by:

  1. Liu, Yanli & Wang, Junyi & Liu, Liqi, 2024. "Physics-informed reinforcement learning for probabilistic wind power forecasting under extreme events," Applied Energy, Elsevier, vol. 376(PA).
  2. Li, Zongxiang & Li, Liwei & Chen, Jing & Wang, Dongqing, 2024. "A multi-head attention mechanism aided hybrid network for identifying batteries’ state of charge," Energy, Elsevier, vol. 286(C).
  3. Chen, Junxiong & Hu, Yuanjiang & Zhu, Qiao & Rashid, Haroon & Li, Hongkun, 2023. "A novel battery health indicator and PSO-LSSVR for LiFePO4 battery SOH estimation during constant current charging," Energy, Elsevier, vol. 282(C).
  4. Yao, Jiachi & Han, Te, 2023. "Data-driven lithium-ion batteries capacity estimation based on deep transfer learning using partial segment of charging/discharging data," Energy, Elsevier, vol. 271(C).
  5. Mizutani, Daijiro & Nakazato, Yuto & Ikushima, Rie & Satsukawa, Koki & Kawasaki, Yosuke & Kuwahara, Masao, 2024. "Optimal intervention policy of emergency storage batteries for expressway transportation systems considering deterioration risk during lead time of replacement," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
  6. Giovane Ronei Sylvestrin & Joylan Nunes Maciel & Marcio Luís Munhoz Amorim & João Paulo Carmo & José A. Afonso & Sérgio F. Lopes & Oswaldo Hideo Ando Junior, 2025. "State of the Art in Electric Batteries’ State-of-Health (SoH) Estimation with Machine Learning: A Review," Energies, MDPI, vol. 18(3), pages 1-77, February.
  7. Zhang, Wencan & He, Hancheng & Li, Taotao & Yuan, Jiangfeng & Xie, Yi & Long, Zhuoru, 2024. "Lithium-ion battery state of health prognostication employing multi-model fusion approach based on image coding of charging voltage and temperature data," Energy, Elsevier, vol. 296(C).
  8. Paweł Ruchała & Olga Orynycz & Wit Stryczniewicz & Karol Tucki, 2023. "Possibility of Energy Recovery from Airflow around an SUV-Class Car Based on Wind Tunnel Testing," Energies, MDPI, vol. 16(19), pages 1-16, October.
  9. Shuhui Cui & Saleem Riaz & Kai Wang, 2023. "Study on Lifetime Decline Prediction of Lithium-Ion Capacitors," Energies, MDPI, vol. 16(22), pages 1-17, November.
  10. Qi, Wei & Qin, Wenhu & Yun, Zhonghua, 2024. "Closed-loop state of charge estimation of Li-ion batteries based on deep learning and robust adaptive Kalman filter," Energy, Elsevier, vol. 307(C).
  11. Wu, Jian & Meng, Jinhao & Lin, Mingqiang & Wang, Wei & Wu, Ji & Stroe, Daniel-Ioan, 2024. "Lithium-ion battery state of health estimation using a hybrid model with electrochemical impedance spectroscopy," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
  12. Zhao, Hongqian & Chen, Zheng & Shu, Xing & Xiao, Renxin & Shen, Jiangwei & Liu, Yu & Liu, Yonggang, 2024. "Online surface temperature prediction and abnormal diagnosis of lithium-ion batteries based on hybrid neural network and fault threshold optimization," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
  13. Xu, Xiaodong & Tang, Shengjin & Han, Xuebing & Lu, Languang & Wu, Yu & Yu, Chuanqiang & Sun, Xiaoyan & Xie, Jian & Feng, Xuning & Ouyang, Minggao, 2023. "Fast capacity prediction of lithium-ion batteries using aging mechanism-informed bidirectional long short-term memory network," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
  14. Meng, Jinhao & You, Yuqiang & Lin, Mingqiang & Wu, Ji & Song, Zhengxiang, 2024. "Multi-scenarios transferable learning framework with few-shot for early lithium-ion battery lifespan trajectory prediction," Energy, Elsevier, vol. 286(C).
  15. Li, Fang & Min, Yongjun & Zhang, Ying & Zhang, Yong & Zuo, Hongfu & Bai, Fang, 2024. "State-of-health estimation method for fast-charging lithium-ion batteries based on stacking ensemble sparse Gaussian process regression," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
  16. Ma, Yan & Li, Jiaqi & Gao, Jinwu & Chen, Hong, 2024. "State of health prediction of lithium-ion batteries under early partial data based on IWOA-BiLSTM with single feature," Energy, Elsevier, vol. 295(C).
  17. Yongquan Sun & Xinkun Qin & Lin Li & Youmei Zhang & Jiahai Zhang & Jia Qi, 2024. "The Impact of Temperature on the Performance and Reliability of Li/SOCl 2 Batteries," Energies, MDPI, vol. 17(13), pages 1-14, June.
  18. Gang Zhou & Jianxun Shi & Bingjing Chen & Zhongyi Qi & Licheng Wang, 2023. "Risk Assessment of Power Supply Security Considering Optimal Load Shedding in Extreme Precipitation Scenarios," Energies, MDPI, vol. 16(18), pages 1-17, September.
  19. 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).
  20. Yu He & Norasage Pattanadech & Kasiean Sukemoke & Minling Pan & Lin Chen, 2025. "The State of Health Estimation of Retired Lithium-Ion Batteries Using a Multi-Input Metabolic Gated Recurrent Unit," Energies, MDPI, vol. 18(5), pages 1-21, February.
  21. 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).
  22. Peng, Simin & Zhu, Junchao & Wu, Tiezhou & Tang, Aihua & Kan, Jiarong & Pecht, Michael, 2024. "SOH early prediction of lithium-ion batteries based on voltage interval selection and features fusion," Energy, Elsevier, vol. 308(C).
  23. Jiakun An & Wei Guo & Tingyan Lv & Ziheng Zhao & Chunguang He & Hongshan Zhao, 2023. "Joint Prediction of the State of Charge and the State of Health of Lithium-Ion Batteries Based on the PSO-XGBoost Algorithm," Energies, MDPI, vol. 16(10), pages 1-14, May.
  24. Sulaiman, Mohd Herwan & Mustaffa, Zuriani & Mohamed, Amir Izzani & Samsudin, Ahmad Salihin & Mohd Rashid, Muhammad Ikram, 2024. "Battery state of charge estimation for electric vehicle using Kolmogorov-Arnold networks," Energy, Elsevier, vol. 311(C).
  25. Li, Xiaoyu & Lyu, Mohan & Li, Kuo & Gao, Xiao & Liu, Caixia & Zhang, Zhaosheng, 2023. "Lithium-ion battery state of health estimation based on multi-source health indicators extraction and sparse Bayesian learning," Energy, Elsevier, vol. 282(C).
  26. Che, Yunhong & Zheng, Yusheng & Forest, Florent Evariste & Sui, Xin & Hu, Xiaosong & Teodorescu, Remus, 2024. "Predictive health assessment for lithium-ion batteries with probabilistic degradation prediction and accelerating aging detection," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
  27. Wang, Siwei & Xiao, Xinping & Ding, Qi, 2024. "A novel fractional system grey prediction model with dynamic delay effect for evaluating the state of health of lithium battery," Energy, Elsevier, vol. 290(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.