• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
  • COPE
  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
  • Scopus
  • crossref
  • orcid

References

1 
Y. Zhao, 2021, A review on battery market trends, second-life reuse, and recycling, Sustainable Chemistry, Vol. 2, No. 1, pp. 167-205DOI
2 
W. Mrozik, 2021, Environmental impacts, pollution sources and pathways of spent lithium-ion batteries, Energy & Environmental Science, Vol. 14, No. 12, pp. 6099-6121DOI
3 
A. Kampker, 2021, Battery pack remanufacturing process up to cell level with sorting and repurposing of battery cells, Journal of Remanufacturing, Vol. 11, No. 1, pp. 1-23DOI
4 
J. B. Jeong, 2023, A Study on Internal Resistance Evaluation for the Reuse of Medium- and Large-Sized Batteries, Journal of the Korean Institute of Electrical Engineers, Vol. 72, No. 6, pp. 717-723DOI
5 
M. M. Kabir, D. E. Demirocak, 2017, Degradation mechanisms in Li-ion batteries: A state-of-the-art review, International Journal of Energy Research, Vol. 41, No. 14, pp. 1963-1986DOI
6 
T. Wang, 2025, Review of aging mechanism and diagnostic methods for lithium-ion batteries, Energies, Vol. 18, No. 14DOI
7 
M. S. Park, J. S. Kim, B. W. Kim, 2024, A Study on SOH Estimation of Lithium-Ion Batteries Using Incremental Capacity Analysis and Deep Learning, Journal of the Korean Institute of Electrical Engineers, Vol. 73, No. 2, pp. 349-357DOI
8 
M. Dubarry, D. Ansean, 2022, Best practices for incremental capacity analysis, Frontiers in Energy Research, Vol. 10DOI
9 
M. Lewerenz, 2017, Differential voltage analysis as a tool for analyzing inhomogeneous aging: A case study for LiFePO4|Graphite cylindrical cells, Journal of Power Sources, Vol. 368, pp. 57-67DOI
10 
A. Maradesa, 2024, Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method, Joule, Vol. 8, No. 7, pp. 1958-1981DOI
11 
W. Hu, 2023, Application of electrochemical impedance spectroscopy to degradation and aging research of lithium-ion batteries, The Journal of Physical Chemistry C, Vol. 127, No. 9, pp. 4465-4495DOI
12 
A. Krupp, 2021, Incremental capacity analysis as a state of health estimation method for lithium-ion battery modules with series-connected cells, Batteries, Vol. 7, No. 1DOI
13 
J. He, 2020, Comparative study of curve determination methods for incremental capacity analysis and state of health estimation of lithium-ion battery, Journal of Energy Storage, Vol. 29DOI
14 
C. You, 2020, Application of the Kramers–Kronig relations to multi-sine electrochemical impedance measurements, Journal of The Electrochemical Society, Vol. 167, No. 2DOI
15 
L. Wildfeuer, P. Gieler, A. Karger, 2021, Combining the distribution of relaxation times from EIS and time-domain data for parameterizing equivalent circuit models of lithium-ion batteries, Batteries, Vol. 7, No. 3DOI
16 
Z. Habib, M. Sarfraz, M. Sakai, 2005, Rational cubic spline interpolation with shape control, Computers & Graphics, Vol. 29, No. 4, pp. 594-605DOI
17 
J. Tsiligaridis, 2023, Tree-based ensemble models and algorithms for classification, pp. 103-106DOI
18 
S. Cho, J. Hur, 2025, A Study on an XGBoost-Based Wind Power Generation Forecasting Model Using Spatial Interpolation of Meteorological Data, Journal of the Korean Institute of Electrical Engineers, Vol. 74, No. 5, pp. 870-877DOI
19 
X. Y. Liew, N. Hameed, J. Clos, 2021, An investigation of XGBoost-based algorithm for breast cancer classification, Machine Learning with Applications, Vol. 6DOI
20 
A. M. Salih, 2025, A perspective on explainable artificial intelligence methods: SHAP and LIME, Advanced Intelligent Systems, Vol. 7, No. 1DOI