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Battery SOH12

[EVS-26] Towards onboard Li-ion battery state-of-health diagnosis by a virtual sensor 논문 전문 : https://www.researchgate.net/publication/288166468_Towards_Onboard_Li-ion_Battery_State-of-health_Diagnosis_by_a_Virtual_Sensor/fulltext/5afe2195458515e9a5763964/Towards-Onboard-Li-ion-Battery-State-of-health-Diagnosis-by-a-Virtual-Sensor.pdf [출처] World Electric Vehicle Journal Vol. 5 - ISSN 2032-6653 ※ The picture and content of this article are from the original paper. [논문 요약] Towards .. 2024. 4. 5.
[Scientific Report-2020] An Incremental Voltage Difference Based Technique for Online State of Health Estimation of Li-ion Batteries 논문 전문 : https://www.nature.com/articles/s41598-020-66424-9 [출처] Naha, A., Han, S., Agarwal, S. et al. An Incremental Voltage Difference Based Technique for Online State of Health Estimation of Li-ion Batteries. Sci Rep 10, 9526 (2020). https://doi.org/10.1038/s41598-020-66424-9 ※ The picture and content of this article are from the original paper. This article is more of an intuitive understandi.. 2023. 12. 26.
[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.
[MDPI-2021] Attention-Based Long Short Term Memory Recurrent Neural Network for Capacity Degradation of Lithium-Ion Batteries 논문 전문 : https://www.mdpi.com/2313-0105/7/4/66 [출처] Mamo, T.; Wang, F.-K. Attention-Based Long Short-Term Memory Recurrent Neural Network for Capacity Degradation of Lithium-Ion Batteries. Batteries 2021, 7, 66. https://doi.org/10.3390/batteries7040066 ※ The picture and content of this article are from the original paper. [논문 요약] Attention-Based Long Short Term Memory Recurrent Neural Network for.. 2023. 3. 20.
[MEV-2015] Comparative study between Internal ohmic resistance and capacity for battery state of health estimation 논문 전문 : https://ieeexplore.ieee.org/document/9121487 [출처] Ramadan, M. & Pramana, Bhisma & Widayat, Sigit & Amifia, Lora & Cahyadi, Adha & Wahyunggoro, Oyas. (2015). Comparative Study Between Internal Ohmic Resistance and Capacity for Battery State of Health Estimation. Journal of Mechatronics, Electrical Power, and Vehicular Technology. 6. 113. 10.14203/j.mev.2015.v6.113-122. ※ The picture and c.. 2023. 3. 2.

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