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전체 글318

[MDPI-2015] Regression Models Using Fully Discharged Voltage and Internal Resistance for State of Health Estimation of Lithium-Ion Batteries 논문 전문 : https://www.mdpi.com/1996-1073/8/4/2889 [출처] Tseng, K.-H.; Liang, J.-W.; Chang, W.; Huang, S.-C. Regression Models Using Fully Discharged Voltage and Internal Resistance for State of Health Estimation of Lithium-Ion Batteries. Energies 2015, 8, 2889-2907. https://doi.org/10.3390/en8042889 ※ The picture and content of this article are from the original paper. [논문요약] Regression Models Usin.. 2023. 2. 2.
[Applied Energy-2016] Model-based fault diagnosis approach on external short circuit of lithium-ion battery used in electric vehicles 논문 전문 : https://www.sciencedirect.com/science/article/abs/pii/S0306261916314507 [출처] Zeyu Chen, Rui Xiong, Jinpeng Tian, Xiong Shang, Jiahuan Lu, Model-based fault diagnosis approach on external short circuit of lithium-ion battery used in electric vehicles,Applied Energy,Volume 184,2016,Pages 365-374,ISSN 0306-2619,https://doi.org/10.1016/j.apenergy.2016.10.026. ※ The picture and content of thi.. 2023. 1. 30.
[Power Sources-2014] Thermal runaway features of large format prismatic lithium ion battery using extended volume accelerating rate calorimetry 논문 전문 : https://www.sciencedirect.com/science/article/abs/pii/S0378775314000159 [출처] Xuning Feng, Mou Fang, Xiangming He, Minggao Ouyang, Languang Lu, Hao Wang, Mingxuan Zhang, Thermal runaway features of large format prismatic lithium ion battery using extended volume accelerating rate calorimetry,Journal of Power Sources,Volume 255,2014,Pages 294-301,ISSN 0378-7753, https://doi.org/10.1016/j.j.. 2023. 1. 26.
[Power Sources-2015] Internal short circuit detection for battery pack using equivalent parameter and consistency method 논문 전문 : https://www.sciencedirect.com/science/article/abs/pii/S0378775315011210 [출처] Minggao Ouyang, Mingxuan Zhang, Xuning Feng, Languang Lu, Jianqiu Li, Xiangming He, Yuejiu Zheng, Internal short circuit detection for battery pack using equivalent parameter and consistency method,Journal of Power Sources,Volume 294,2015,Pages 272-283,ISSN 0378-7753, https://doi.org/10.1016/j.jpowsour.2015.06.0.. 2023. 1. 23.
[Measurement-2018] Design and analysis of capacity models for lithium-ion battery 논문 전문 : https://www.sciencedirect.com/science/article/abs/pii/S0263224118300897 [출처] Akhil Garg, Xiongbin Peng, My Loan Phung Le, Kapil Pareek, C.M.M. Chin,Design and analysis of capacity models for Lithium-ion battery,Measurement,Volume 120,2018,Pages 114-120,ISSN 0263-2241, https://doi.org/10.1016/j.measurement.2018.02.003. [논문요약] Design and analysis of capacity models for lithium-ion battery .. 2023. 1. 19.
[JES-2019] Review and Performance Comparison of Mechanical-Chemical Degradation Models for Lithium-Ion Batteries 논문 전문 : https://iopscience.iop.org/article/10.1149/2.0281914jes [출처] Jorn M. Reniers et al 2019 J. Electrochem. Soc. 166 A3189DOI 10.1149/2.0281914jes https://doi.org/10.1016/j.jpowsour.2018.05.097. ※ The picture and content of this article are from the original paper. [논문요약] Review and Performance Comparison of Mechanical-Chemical Degradation Models for Lithium-Ion Batteries 배터리를 Digital Twin 하.. 2023. 1. 16.
[JAE-2021] Practical identifiability of electrochemical P2D models for lithium-ion batteries 논문 전문 : https://link.springer.com/article/10.1007/s10800-021-01579-5 [출처] Laue, V., Röder, F. & Krewer, U. Practical identifiability of electrochemical P2D models for lithium-ion batteries. J Appl Electrochem 51, 1253–1265 (2021). https://doi.org/10.1007/s10800-021-01579-5 ※ The picture and content of this article are from the original paper. [논문요약] Practical identifiability of electrochemical P.. 2023. 1. 12.
[MDPI-2021] Machine Learning-Based Data-Driven Fault Detection/Diagnosis of Lithium-Ion Battery: A Critical Review 논문 전문 : https://www.mdpi.com/2079-9292/10/11/1309 [출처] Article: Machine Learning-Based Data-Driven Fault Detection/Diagnosis of Lithium-Ion Battery: A Critical Review Authors: by Akash Samanta,Sumana Chowdhuri and Sheldon S. Williamson Link: https://www.mdpi.com/2079-9292/10/11/1309 ※ The picture and content of this article are from the original paper. [논문요약] Machine Learning-Based Data-Driven F.. 2023. 1. 9.
[Power Sources-2018] Fault diagnosis and quantitative analysis of micro-short circuits for lithium-ion batteries in battery packs 논문 전문 : https://www.sciencedirect.com/science/article/abs/pii/S0378775318305950 [출처] Xiangdong Kong, Yuejiu Zheng, Minggao Ouyang, Languang Lu, Jianqiu Li, Zhendong Zhang, Fault diagnosis and quantitative analysis of micro-short circuits for lithium-ion batteries in battery packs, Journal of Power Sources,Volume 395,2018,Pages 358-368,ISSN 0378-7753, https://doi.org/10.1016/j.jpowsour.2018.05.09.. 2022. 12. 29.

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