Open Access
| Issue |
E3S Web Conf.
Volume 680, 2025
The 4th International Conference on Energy and Green Computing (ICEGC’2025)
|
|
|---|---|---|
| Article Number | 00016 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/e3sconf/202568000016 | |
| Published online | 19 December 2025 | |
- M. Liu, H. Hao, Z. Lin, X. He, Y. Qian, X. Sun, J. Geng, Z. Li, “Flying cars economically favor battery electric over fuel cell and internal combustion engine,” PNAS Nexus, vol. 2023, Mar. 2023. [Google Scholar]
- S.-W. Kim, D.-H. Kwon, I.-H. Cho, “Temperature Management Strategy for Urban Air Mobility Batteries to Improve Energy Efficiency in Low-Temperature Conditions,” Sustainability, vol. 16, no. 18, 2024. [Google Scholar]
- S. An, G. Cai, X. Peng, M. Dai, G. Yang, “The Design of Improved Series Hybrid Power System Based on Compound-Wing VTOL,” Drones, vol. 8, no. 11, pp. 634, Nov. 2024. [Google Scholar]
- D. Souidi, J. Chrouta, A. J. Telmoudi, “A Hybrid Deep Learning Approach for SOC Estimation in Electric Vehicle Batteries,” International Journal of Dynamics and Control, vol. 13, 2025. [Google Scholar]
- H. Labiri, S. Farhat, F. E. Nadir, Z. Chekoubi, H. Elihssini, “SoC Estimation in Electric Cars using Ampere-Hour and Fuzzy Logic Approaches,” 2025 5th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), Fez, Morocco, 2025, pp. 1–4, doi: 10.1109/IRASET64571.2025.11008166. [Google Scholar]
- D. Zhang, C. Zhong, P. Xu, Y. Tian, “Deep Learning in the State of Charge Estimation for Li-Ion Batteries of Electric Vehicles: A Review,” Machines, vol. 10, no. 10, 2022. [Google Scholar]
- V. S. V. Krishna, N. Pappa, S. P. Joy Vasantha Rani, “Deep-Learning Framework for State of Charge (SoC) Estimation of Electric Vehicle Batteries Using a Pynq Board,” Journal of Applied Research and Technology, vol. 22, no. 6, 2024. [Google Scholar]
- J. Yao, J. Kowal, “Towards a Smarter Battery Management System: A Critical Review on Deep Learning-Based State of Charge Estimation of Lithium-Ion Batteries,” Energy and AI, vol. 21, 2025. [Google Scholar]
- S. Mukherjee, K. Chowdhury, “State of charge estimation techniques for battery management system used in electric vehicles: a review,” Energy Systems, Springer, Oct. 2023. [Google Scholar]
- S. Shirguppikar, P. Gavali, V. Ganachari, et al., “Characterization of Li-ion Battery and State of Charge Estimation Methods for Diverse Battery Chemistries: A Review,” Discover Applied Sciences, vol. 7, article 1443, 2025. [Google Scholar]
- Das, K., Kumar, R. “A Comprehensive Review of Categorization and Perspectives on State-of-Charge Estimation Using Deep Learning Methods for Electric Transportation,” Wireless Pers Commun 133, 1599–1618 (2023). https://doi.org/10.1007/s11277-023-10830-5 [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.