Aging mechanisms, prognostics and management for lithium-ion batteries: Recent advances
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DOI: 10.1016/j.rser.2024.114915
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- Jalkanen, K. & Karppinen, J. & Skogström, L. & Laurila, T. & Nisula, M. & Vuorilehto, K., 2015. "Cycle aging of commercial NMC/graphite pouch cells at different temperatures," Applied Energy, Elsevier, vol. 154(C), pages 160-172.
- Ma, Yan & Shan, Ce & Gao, Jinwu & Chen, Hong, 2022. "A novel method for state of health estimation of lithium-ion batteries based on improved LSTM and health indicators extraction," Energy, Elsevier, vol. 251(C).
- 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.
- Jiang, Benben & Berliner, Marc D. & Lai, Kun & Asinger, Patrick A. & Zhao, Hongbo & Herring, Patrick K. & Bazant, Martin Z. & Braatz, Richard D., 2022. "Fast charging design for Lithium-ion batteries via Bayesian optimization," Applied Energy, Elsevier, vol. 307(C).
- Zheng, Xiujuan & Fang, Huajing, 2015. "An integrated unscented kalman filter and relevance vector regression approach for lithium-ion battery remaining useful life and short-term capacity prediction," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 74-82.
- Miaomiao Zeng & Peng Zhang & Yang Yang & Changjun Xie & Ying Shi, 2019. "SOC and SOH Joint Estimation of the Power Batteries Based on Fuzzy Unscented Kalman Filtering Algorithm," Energies, MDPI, vol. 12(16), pages 1-15, August.
- 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).
- Qin, Yudi & Xu, Zhoucheng & Xiao, Shengran & Gao, Ming & Bai, Jian & Liebig, Dorothea & Lu, Languang & Han, Xuebing & Li, Yalun & Du, Jiuyu & Ouyang, Minggao, 2023. "Temperature consistency–oriented rapid heating strategy combining pulsed operation and external thermal management for lithium-ion batteries," Applied Energy, Elsevier, vol. 335(C).
- Kong, Jin-zhen & Yang, Fangfang & Zhang, Xi & Pan, Ershun & Peng, Zhike & Wang, Dong, 2021. "Voltage-temperature health feature extraction to improve prognostics and health management of lithium-ion batteries," Energy, Elsevier, vol. 223(C).
- Ming Zhang & Dongfang Yang & Jiaxuan Du & Hanlei Sun & Liwei Li & Licheng Wang & Kai Wang, 2023. "A Review of SOH Prediction of Li-Ion Batteries Based on Data-Driven Algorithms," Energies, MDPI, vol. 16(7), pages 1-28, March.
- Patil, Meru A. & Tagade, Piyush & Hariharan, Krishnan S. & Kolake, Subramanya M. & Song, Taewon & Yeo, Taejung & Doo, Seokgwang, 2015. "A novel multistage Support Vector Machine based approach for Li ion battery remaining useful life estimation," Applied Energy, Elsevier, vol. 159(C), pages 285-297.
- Deng, Zhongwei & Hu, Xiaosong & Lin, Xianke & Che, Yunhong & Xu, Le & Guo, Wenchao, 2020. "Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression," Energy, Elsevier, vol. 205(C).
- Shengjin Tang & Chuanqiang Yu & Xue Wang & Xiaosong Guo & Xiaosheng Si, 2014. "Remaining Useful Life Prediction of Lithium-Ion Batteries Based on the Wiener Process with Measurement Error," Energies, MDPI, vol. 7(2), pages 1-28, January.
- Wang, Yujie & Zhou, Caijie & Chen, Zonghai, 2022. "Optimization of battery charging strategy based on nonlinear model predictive control," Energy, Elsevier, vol. 241(C).
- Pastor-Fernández, Carlos & Yu, Tung Fai & Widanage, W. Dhammika & Marco, James, 2019. "Critical review of non-invasive diagnosis techniques for quantification of degradation modes in lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 138-159.
- Lingling Li & Pengchong Wang & Kuei-Hsiang Chao & Yatong Zhou & Yang Xie, 2016. "Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Gaussian Processes Mixture," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-13, September.
- J. M. Amanor-Boadu & A. Guiseppi-Elie & E. Sánchez-Sinencio, 2018. "The Impact of Pulse Charging Parameters on the Life Cycle of Lithium-Ion Polymer Batteries," Energies, MDPI, vol. 11(8), pages 1-15, August.
- Sarasketa-Zabala, E. & Martinez-Laserna, E. & Berecibar, M. & Gandiaga, I. & Rodriguez-Martinez, L.M. & Villarreal, I., 2016. "Realistic lifetime prediction approach for Li-ion batteries," Applied Energy, Elsevier, vol. 162(C), pages 839-852.
- Xu, Zhicheng & Wang, Jun & Lund, Peter D. & Zhang, Yaoming, 2022. "Co-estimating the state of charge and health of lithium batteries through combining a minimalist electrochemical model and an equivalent circuit model," Energy, Elsevier, vol. 240(C).
- He, Rong & He, Yongling & Xie, Wenlong & Guo, Bin & Yang, Shichun, 2023. "Comparative analysis for commercial li-ion batteries degradation using the distribution of relaxation time method based on electrochemical impedance spectroscopy," Energy, Elsevier, vol. 263(PD).
- Zhang, Ying & Li, Yan-Fu, 2022. "Prognostics and health management of Lithium-ion battery using deep learning methods: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
- Tao, Laifa & Ma, Jian & Cheng, Yujie & Noktehdan, Azadeh & Chong, Jin & Lu, Chen, 2017. "A review of stochastic battery models and health management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 716-732.
- Wu, Ji & Zhang, Chenbin & Chen, Zonghai, 2016. "An online method for lithium-ion battery remaining useful life estimation using importance sampling and neural networks," Applied Energy, Elsevier, vol. 173(C), pages 134-140.
- Hanlei Sun & Jianrui Sun & Kun Zhao & Licheng Wang & Kai Wang & Mohammad Yaghoub Abdollahzadeh Jamalabadi, 2022. "Data-Driven ICA-Bi-LSTM-Combined Lithium Battery SOH Estimation," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-8, March.
- Jiang, Jiuchun & Ruan, Haijun & Sun, Bingxiang & Wang, Leyi & Gao, Wenzhong & Zhang, Weige, 2018. "A low-temperature internal heating strategy without lifetime reduction for large-size automotive lithium-ion battery pack," Applied Energy, Elsevier, vol. 230(C), pages 257-266.
- Zheng, Linfeng & Zhu, Jianguo & Lu, Dylan Dah-Chuan & Wang, Guoxiu & He, Tingting, 2018. "Incremental capacity analysis and differential voltage analysis based state of charge and capacity estimation for lithium-ion batteries," Energy, Elsevier, vol. 150(C), pages 759-769.
- Wang, Yujie & Zhang, Chenbin & Chen, Zonghai & Xie, Jing & Zhang, Xu, 2015. "A novel active equalization method for lithium-ion batteries in electric vehicles," Applied Energy, Elsevier, vol. 145(C), pages 36-42.
- Xu, Xiaodong & Tang, Shengjin & Yu, Chuanqiang & Xie, Jian & Han, Xuebing & Ouyang, Minggao, 2021. "Remaining Useful Life Prediction of Lithium-ion Batteries Based on Wiener Process Under Time-Varying Temperature Condition," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
- Hu, Chao & Youn, Byeng D. & Chung, Jaesik, 2012. "A multiscale framework with extended Kalman filter for lithium-ion battery SOC and capacity estimation," Applied Energy, Elsevier, vol. 92(C), pages 694-704.
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Keywords
Lithium-ion batteries; Battery aging mechanisms; Battery health prognostics; Battery health management; Battery management system;All these keywords.
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