An Electrode Aging Information-Embedded Rapid Sorting Approach for Second-Life Applications of Lithium-Ion Batteries Retired from Electric Vehicles
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-3940-0_24
Reference19 articles.
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2. Guo, R., Shen, W.: An information analysis based online parameter identification method for lithium-ion batteries in electric vehicles. IEEE Trans. Ind. Electron. 71(7), 7095–7105 (2023)
3. Tian, J., Xiong, R., Shen, W., Sun, F.: Electrode ageing estimation and open circuit voltage reconstruction for lithium ion batteries. Energy Storage Mater. 37, 283–295 (2021). https://doi.org/10.1016/j.ensm.2021.02.018
4. Guo, R., Xu, Y., Hu, C., Shen, W.: Self-adaptive neural network-based fractional-order nonlinear observer design for state of charge estimation of lithium-ion batteries. IEEE/ASME Trans. Mechatron. 1–12 (2023). https://doi.org/10.1109/TMECH.2023.3321719
5. Zhang, Y., et al.: Performance assessment of retired EV battery modules for echelon use. Energy 193, 116555 (2020). https://doi.org/10.1016/j.energy.2019.116555
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