Open Access
| Issue |
E3S Web Conf.
Volume 234, 2021
The International Conference on Innovation, Modern Applied Science & Environmental Studies (ICIES2020)
|
|
|---|---|---|
| Article Number | 00097 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/e3sconf/202123400097 | |
| Published online | 02 February 2021 | |
- P. Shrivastava, T.K. Soon, M. Y. I. B Idris, et S. Mekhilef, « Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries », Renewable and Sustainable Energy Reviews, Vol. 113, p. 109233, oct. 2019, doi: 10.1016/j.rser.2019.06.040 [CrossRef] [Google Scholar]
- Y. Tian, R. Lai, X. Li, L. Xiang, et J. Tian, « A combined method for state-of-charge estimation for lithium-ion batteries using a long short-term memory network and an adaptive cubature Kalman filter », Applied Energy, Vol. 265, p. 114789, mai 2020, doi: 10.1016/j.apenergy.2020.114789 [Google Scholar]
- X. Li, Z. Wang, et L. Zhang, « Co-estimation of capacity and state-of-charge for lithium-ion batteries in electric vehicles », Energy, Vol. 174, p. 33 44, mai 2019, doi: 10.1016/j.energy.2019.02.147 [CrossRef] [Google Scholar]
- J. Peng, J. Luo, H. He, et B. Lu, « An improved state of charge estimation method based on cubature Kalman filter for lithium-ion batteries », Applied Energy, Vol. 253, p. 113520, nov. 2019, doi: 10.1016/j.apenergy.2019.113520 [Google Scholar]
- J. Linghu, L. Kang, M. Liu, X. Luo, Y. Feng, et C. Lu, « Estimation for state-of-charge of lithium-ion battery based on an adaptive high-degree cubature Kalman filter », Energy, Vol. 189, p. 116204, déc. 2019, doi: 10.1016/j.energy.2019.116204 [CrossRef] [Google Scholar]
- R. Zhang et al., « A Study on the Open Circuit Voltage and State of Charge Characterization of High Capacity Lithium-Ion Battery Under Different Temperature », Energies, Vol. 11, no 9, p. 2408, sept. 2018, doi: 10.3390/en11092408 [Google Scholar]
- « Battery Management Systems, Volume II: Equivalent-Circuit Methods - Artech books ». https://ieeexplore.ieee.org/document/9100098 (consulté le nov. 25, 2020) [Google Scholar]
- J. Lv, B. Jiang, X. Wang, Y. Liu, et Y. Fu, « Estimation of the State of Charge of Lithium Batteries Based on Adaptive Unscented Kalman Filter Algorithm », Electronics, Vol. 9, no 9, p. 1425, sept. 2020, doi: 10.3390/electronics9091425 [Google Scholar]
- H. Yang, X. Sun, Y. An, X. Zhang, T. Wei, et Y. Ma, « Online parameters identification and state of charge estimation for lithium-ion capacitor based on improved Cubature Kalman filter », Journal of Energy Storage, Vol. 24, p. 100810, août 2019, doi: 10.1016/j.est.2019.100810 [Google Scholar]
- M. Ali et al., « An Online Data-Driven Model Identification and Adaptive State of Charge Estimation Approach for Lithium-ion-Batteries Using the Lagrange Multiplier Method », Energies, Vol. 11, no 11, p. 2940, oct. 2018, doi: 10.3390/en11112940 [Google Scholar]
- D. Sun et al., « State of charge estimation for lithium-ion battery based on an Intelligent Adaptive Extended Kalman Filter with improved noise estimator », Energy, Vol. 214, p. 119025, janv. 2021, doi: 10.1016/j.energy.2020.119025 [CrossRef] [Google Scholar]
- R. Ahmed, M. El Sayed, I. Arasaratnam, Jimi Tjong, et S. Habibi, « Reduced-Order Electrochemical Model Parameters Identification and SOC Estimation for Healthy and Aged Li-Ion Batteries Part I: Parameterization Model Development for Healthy Batteries », IEEE J. Emerg. Sel. Topics Power Electron., Vol. 2, no 3, p. 659 677, sept. 2014, doi: 10.1109/JESTPE.2014.2331059 [CrossRef] [Google Scholar]
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