[MDPI-2023] Online State-of-Health Estimation for Fast-Charging Lithium-Ion Batteries Based on a Transformer–Long Short-Term Memory Neural Network
논문 전문 : https://www.mdpi.com/2313-0105/9/11/539 [출처] Fan, Y.; Li, Y.; Zhao, J.; Wang, L.; Yan, C.; Wu, X.; Zhang, P.; Wang, J.; Gao, G.; Wei, L. Online State-of-Health Estimation for Fast-Charging Lithium-Ion Batteries Based on a Transformer–Long Short-Term Memory Neural Network. Batteries 2023, 9, 539. https://doi.org/10.3390/batteries9110539 ※ The picture and content of this article are from t..
2023. 11. 25.
[Applied Energy-2016] State of health monitoring of lithium-ion battery modules and packs via incremental capacity peak tracking
논문 전문 : https://www.sciencedirect.com/science/article/abs/pii/S0306261916310741 [출처] Caihao Weng, Xuning Feng, Jing Sun, Huei Peng,State-of-health monitoring of lithiumion battery modules and packs via incremental capacity peak tracking,Applied Energy,Volume 180,2016,Pages 360-368,ISSN 0306-2619, https://doi.org/10.1016/j.apenergy.2016.07.126. ※ The picture and content of this article are from t..
2023. 11. 24.
[Power Sources-2017] A correlation based fault detection method for short circuits in battery packs
논문 전문 : https://www.sciencedirect.com/science/article/abs/pii/S0378775316315300 [출처] Bing Xia, Yunlong Shang, Truong Nguyen, Chris Mi,A correlation based fault detection method for short circuits in battery packs,Journal of Power Sources,Volume 337,2017,Pages 1-10,ISSN 0378-7753, https://doi.org/10.1016/j.jpowsour.2016.11.007. ※ The picture and content of this article are from the original paper..
2023. 11. 16.
