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Degradation model and cycle life prediction for lithium-ion battery used in hybrid energy storage system

Citations

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  1. Wenyu Qu & Guici Chen & Tingting Zhang, 2022. "An Adaptive Noise Reduction Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries," Energies, MDPI, vol. 15(19), pages 1-18, October.
  2. Jiang, Lidang & Li, Zhuoxiang & Hu, Changyan & Chen, Junxiong & Huang, Qingsong & He, Ge, 2024. "A robust adapted Flexible Parallel Neural Network architecture for early prediction of lithium battery lifespan," Energy, Elsevier, vol. 308(C).
  3. Xiaodong Xu & Chuanqiang Yu & Shengjin Tang & Xiaoyan Sun & Xiaosheng Si & Lifeng Wu, 2019. "Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Wiener Processes with Considering the Relaxation Effect," Energies, MDPI, vol. 12(9), pages 1-17, May.
  4. Zhang, Meng & Hu, Tao & Wu, Lifeng & Kang, Guoqing & Guan, Yong, 2021. "A method for capacity estimation of lithium-ion batteries based on adaptive time-shifting broad learning system," Energy, Elsevier, vol. 231(C).
  5. Ma, Qiuhui & Zheng, Ying & Yang, Weidong & Zhang, Yong & Zhang, Hong, 2021. "Remaining useful life prediction of lithium battery based on capacity regeneration point detection," Energy, Elsevier, vol. 234(C).
  6. Yanlin Guo, 2022. "Correlation Analysis between Stock Price and Accounting Profit Based on a Vector Autoregressive Model," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
  7. Liu, Qin & Zhang, Wencan & Zhang, Zhongbo & Qin, Qichao, 2022. "A drive system global control strategy for electric vehicle based on optimized acceleration curve," Energy, Elsevier, vol. 248(C).
  8. Wang, Shuoqi & Guo, Dongxu & Han, Xuebing & Lu, Languang & Sun, Kai & Li, Weihan & Sauer, Dirk Uwe & Ouyang, Minggao, 2020. "Impact of battery degradation models on energy management of a grid-connected DC microgrid," Energy, Elsevier, vol. 207(C).
  9. J. N. Chandra Sekhar & Bullarao Domathoti & Ernesto D. R. Santibanez Gonzalez, 2023. "Prediction of Battery Remaining Useful Life Using Machine Learning Algorithms," Sustainability, MDPI, vol. 15(21), pages 1-28, October.
  10. Hu, Jie & Liu, Di & Du, Changqing & Yan, Fuwu & Lv, Chen, 2020. "Intelligent energy management strategy of hybrid energy storage system for electric vehicle based on driving pattern recognition," Energy, Elsevier, vol. 198(C).
  11. Cheng, Xiaoyuan & Yao, Ruiqiu & Postnikov, Andrey & Hu, Yukun & Varga, Liz, 2024. "Decentralized intelligent multi-party competitive aggregation framework for electricity prosumers," Applied Energy, Elsevier, vol. 373(C).
  12. Zheng, Bowen & Deng, Zhichao & Luo, Zhenhao & Mao, Shuoyuan & Ouyang, Minggao & Han, Xuebing & Wang, Hewu & Li, Yalun & Sun, Yukun & Wang, Depeng & Yuan, Yuebo & He, Liangxi & Yang, Zhi & Zhu, Yanlin, 2025. "A comprehensive review of lithium-ion battery modelling research and prospects: in-depth analysis of current research and future directions," Applied Energy, Elsevier, vol. 401(PB).
  13. Zhu, Tao & Lot, Roberto & Wills, Richard G.A. & Yan, Xingda, 2020. "Sizing a battery-supercapacitor energy storage system with battery degradation consideration for high-performance electric vehicles," Energy, Elsevier, vol. 208(C).
  14. Mehrshad Pakjoo & Luigi Piegari & Giuliano Rancilio & Silvia Colnago & Joseph Epoupa Mengou & Federico Bresciani & Giacomo Gorni & Stefano Mandelli & Marco Merlo, 2023. "A Review on Testing of Electrochemical Cells for Aging Models in BESS," Energies, MDPI, vol. 16(19), pages 1-26, September.
  15. Zhang, Qisong & Yang, Lin & Guo, Wenchao & Qiang, Jiaxi & Peng, Cheng & Li, Qinyi & Deng, Zhongwei, 2022. "A deep learning method for lithium-ion battery remaining useful life prediction based on sparse segment data via cloud computing system," Energy, Elsevier, vol. 241(C).
  16. Xie, Qilong & Liu, Rongchuan & Huang, Jihao & Su, Jianhui, 2023. "Residual life prediction of lithium-ion batteries based on data preprocessing and a priori knowledge-assisted CNN-LSTM," Energy, Elsevier, vol. 281(C).
  17. Ameer, Hamza & Wang, Yujie & Chen, Zonghai, 2025. "A density-based spatial clustering and linear programming method for electric vehicle charging station location and price optimization," Energy, Elsevier, vol. 317(C).
  18. Shen, Dongxu & Wu, Lifeng & Kang, Guoqing & Guan, Yong & Peng, Zhen, 2021. "A novel online method for predicting the remaining useful life of lithium-ion batteries considering random variable discharge current," Energy, Elsevier, vol. 218(C).
  19. Sun, Shukai & Che, Liang & Zhao, Ruifeng & Chen, Yizhe & Li, Ming, 2025. "Multi-task learning and voltage reconstruction-based battery degradation prediction under variable operating conditions of energy storage applications," Energy, Elsevier, vol. 317(C).
  20. Cheng, Gong & Wang, Xinzhi & He, Yurong, 2021. "Remaining useful life and state of health prediction for lithium batteries based on empirical mode decomposition and a long and short memory neural network," Energy, Elsevier, vol. 232(C).
  21. Chen, Guisheng & Zhou, Hengyu & Xu, Yangsong & Zhu, Wenxia & Chen, Liang & Wang, Yusong, 2025. "A novel SOC-OCV separation and extraction technology suitable for online joint estimation of SOC and SOH in lithium-ion batteries," Energy, Elsevier, vol. 326(C).
  22. Han, Xiaojuan & Wang, Zuran & Wei, Zixuan, 2021. "A novel approach for health management online-monitoring of lithium-ion batteries based on model-data fusion," Applied Energy, Elsevier, vol. 302(C).
  23. Chen, Guisheng & Zhou, Hengyu & Yang, Jie & Xu, Yangsong & Xiao, Renxin & Wang, Yusong, 2026. "Optimization of open-circuit voltage curve acquisition and state estimation for aging lithium-ion batteries," Energy, Elsevier, vol. 342(C).
  24. Jianfang Jia & Jianyu Liang & Yuanhao Shi & Jie Wen & Xiaoqiong Pang & Jianchao Zeng, 2020. "SOH and RUL Prediction of Lithium-Ion Batteries Based on Gaussian Process Regression with Indirect Health Indicators," Energies, MDPI, vol. 13(2), pages 1-20, January.
  25. Li, Dexin & Zuo, Wei & Li, Qingqing & Zhang, Guangde & Zhou, Kun & E, Jiaqiang, 2023. "Effects of pulsating flow on the performance of multi-channel cold plate for thermal management of lithium-ion battery pack," Energy, Elsevier, vol. 273(C).
  26. Arévalo, Paúl & Cano, Antonio & Jurado, Francisco, 2022. "Mitigation of carbon footprint with 100% renewable energy system by 2050: The case of Galapagos islands," Energy, Elsevier, vol. 245(C).
  27. Wang, Shuai & Ma, Hongyan & Zhang, Yingda & Li, Shengyan & He, Wei, 2023. "Remaining useful life prediction method of lithium-ion batteries is based on variational modal decomposition and deep learning integrated approach," Energy, Elsevier, vol. 282(C).
  28. Chen, Lei & Wang, Shunli & Jiang, Hong & Fernandez, Carlos, 2024. "A multi-time-scale framework for state of energy and maximum available energy of lithium-ion battery under a wide operating temperature range," Applied Energy, Elsevier, vol. 355(C).
  29. Zhu, Tao & Wills, Richard G.A. & Lot, Roberto & Kong, Xiaodan & Yan, Xingda, 2021. "Optimal sizing and sensitivity analysis of a battery-supercapacitor energy storage system for electric vehicles," Energy, Elsevier, vol. 221(C).
  30. Jiang, Yinghua & Kang, Lixia & Liu, Yongzhong, 2019. "A unified model to optimize configuration of battery energy storage systems with multiple types of batteries," Energy, Elsevier, vol. 176(C), pages 552-560.
  31. Chen, Jianguo & Wang, Yu & Guo, Dongxu & Shen, Yifan & Sun, Tao & Han, Xuebing & Zheng, Yuejiu & Ouyang, Minggao, 2025. "Deep learning model for remaining useful life prediction with reduced labeling data dependency," Applied Energy, Elsevier, vol. 402(PA).
  32. Fan Zhang & Lele Yin & Jianqiang Kang, 2021. "Enhancing Stability and Robustness of State-of-Charge Estimation for Lithium-Ion Batteries by Using Improved Adaptive Kalman Filter Algorithms," Energies, MDPI, vol. 14(19), pages 1-18, October.
  33. 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).
  34. Tian, Jiaqiang & Wang, Yujie & Liu, Chang & Chen, Zonghai, 2020. "Consistency evaluation and cluster analysis for lithium-ion battery pack in electric vehicles," Energy, Elsevier, vol. 194(C).
  35. Ting Zhu & Wenbo Wang & Yu Cao & Xia Liu & Zhongyuan Lai & Hui Lan, 2025. "An Innovative Framework for Forecasting the State of Health of Lithium-Ion Batteries Based on an Improved Signal Decomposition Method," Sustainability, MDPI, vol. 17(11), pages 1-25, May.
  36. 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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