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All issues Volume 182 (2020) E3S Web Conf., 182 (2020) 03007 References
Open Access
Issue
E3S Web Conf.
Volume 182, 2020
2020 10th International Conference on Power, Energy and Electrical Engineering (CPEEE 2020)
Article Number 03007
Number of page(s) 7
Section Energy and Energy Storage Technology
DOI https://doi.org/10.1051/e3sconf/202018203007
Published online 31 July 2020
  1. Xiaopeng Tang, Yujie Wang, Changfu Zou, Ke Yao, Yongxiao Xia, Furong Gao. A novel framework for Lithium-ion battery modeling considering uncertainties of temperature and aging. Energy Convers., 2019; 180:162-170. [Google Scholar]
  2. Anthony Barré, Benjamin Deguilhem, Sébastien Grolleau, Mathias Gérard, Frédéric Suard, Delphine Riu. A review on lithium-ion battery ageing mechanisms and estimations for automotive applications. Journal of Power Sources, 2013; 241:680-689. [Google Scholar]
  3. Christoph R. Birkl, Matthew R. Roberts, Euan McTurk, Peter G. Bruce, David A. Howey. Degradation diagnostics for lithium ion cells. Journal of Power Sources, 2017; 341:373-386. [Google Scholar]
  4. Feng Leng, Cher Ming Tan, Michael Pecht. Effect of temperature on the aging rate of Li ion battery operating above room temperature. Sci. Rep.,5, 12967; doi: 10.1038/srep12967 (2015). [Google Scholar]
  5. Naixing Yang, Xiongwen Zhang, BinBin Shang, Guojun Li. Unbalanced discharging and aging due to temperature differences among the cells in a lithium-ion battery pack with parallel combination. Journal of Power Sources, 2016; 306:733-741. [Google Scholar]
  6. Christoph R. Birkl, Matthew R. Roberts, Euan McTurk, Peter G. Bruce, David A. Howey. Degradation diagnostics for lithium ion cells. Journal of Power Sources, 2017; 341:373-386. [Google Scholar]
  7. Issam Baghdadi, Olivier Briat, Jean-Yves Delétage, Philippe Gyan, Jean-Michel Vinassa. Lithium battery aging model based on Dakin’s degradation approach. Journal of Power Sources, 2016; 325:273-285. [Google Scholar]
  8. Yang Gao, Jiuchun Jiang, Caiping Zhang, Weige Zhang, Yan Jiang. Aging mechanisms under different state-of-charge ranges and the multi-indicators system of state-of-health for lithium-ion battery with Li(NiMnCo)O2 cathode. Journal of Power Sources, 2018; 400:641-651. [Google Scholar]
  9. Matthiue Dubarry, Cyril Truchot, Boryann Liaw. Mechanistic diagnosis and prognosis on Li-ion battery degradation. Presented at: 2013 IBA. [Google Scholar]
  10. Linjing Zhang, Jiuchun Jiang, Weige Zhang. Capacity Decay Mechanism of the LCO + NMC532/Graphite Cells Combined with PostMortem Technique. Energies. 10(8), 1147; doi: 10.3390/en10081147 (2017). [Google Scholar]
  11. Tiphaine Plattard, Nathalie Barnel, Loïc Assaud, Sylvain Franger, Jean-Marc Duffault. Combining a Fatigue Model and an Incremental Capacity Analysis on a Commercial NMC/Graphite Cell under Constant Current Cycling with and without Calendar Aging. Batteries., 5(1), 36; doi: 10.3390/batteries5010036 (2019). [Google Scholar]
  12. Adnan Nuhic, Tarik Terzimehic, Thomas Soczka-Guth, Michael Buchholz, Klaus Dietmayer. Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods. Journal of Power Sources, 2013; 239:680-688. [Google Scholar]
  13. Xiaosong Hu, Shengbo Eben Li, Yalian Yang. Advanced Machine Learning Approach for Lithium-Ion Battery State Estimation in Electric Vehicles. IEEE Transactions on Transportation Electrification, 2016; 2:140-149. [Google Scholar]

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