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            47.  Ruiz V.  Standards  for  the  Performance  and  Durability   for lithium-ion batteries. J Power Sources. 2002;109(1):160-166.
               Assessment of Electric Vehicle Batteries-Possible Performance      doi: 10.1016/S0378-7753(02)00048-4
               Criteria for an Ecodesign Regulation. Eng Mater Sci. 2018;68.
                                                               55.  De Hoog J, Jaguemont J, Abdel-Monem M, Van Den Bossche P,
            48.  Abolhassani Monfared N, Gharib N, Moqtaderi H,  et al.   Van Mierlo J, Omar N. Combining an electrothermal and
               Prediction of state-of-charge effects on lead-acid battery   impedance aging model to investigate thermal degradation
               characteristics using neural network parameter modifier.   caused by fast charging. Energies. 2018;11(4):804.
               J Power Sources. 2006;158(2 Specail issue):932-935.
                                                                  doi: 10.3390/en11040804
               doi: 10.1016/j.jpowsour.2005.11.023
                                                               56.  Marotta A, Tutuianu M. Europe-Centric Light Duty Test Cycle
            49.  Nikolian A, Jaguemont J, de Hoog J, et al. Complete cell-  and Differences with Respect to the WLTP Cycle. Vol. 7-10.
               level  lithium-ion electrical  ECM model for  different   Luxembourg: Institute for Energy and Transport; 2012.
               chemistries (NMC, LFP, LTO) and temperatures (−5 °C to
               45 °C)-Optimized modelling techniques. Int J Electr Power      doi: 10.2790/53651
               Energy Syst. 2018;98:133-146.                   57.  de Hoog J, Timmermans JM, Ioan-Stroe D, et al. Combined
               doi: 10.1016/j.ijepes.2017.11.031                  cycling and calendar capacity fade modeling of a Nickel-
                                                                  Manganese-Cobalt  Oxide  Cell  with  real-life  profile
            50.  He H, Xiong R, Fan J. Evaluation of lithium-ion battery   validation. Appl Energy. 2017;200:47-61.
               equivalent circuit models for state of charge estimation by
               an experimental approach. Energies. 2011;4(4):582-598.     doi: 10.1016/j.apenergy.2017.05.018
               doi: 10.3390/en4040582                          58.  Tu H, Moura S, Wang Y, Fang H. Integrating physics-based
                                                                  modeling with machine learning for lithium-ion batteries.
            51.  Jaguemont J, Darwiche A, Barde F. Optimal fast-charging   Appl Energy. 2023;329:1-25.
               strategy for cylindrical li-ion cells at different temperatures.
               World Electr Veh J. 2024;15(8):330.                doi: 10.1016/j.apenergy.2022.120289
                                                               59.  Pour MY. Electro-Thermal Modeling of Lithium-Ion Batteries.
               doi: 10.3390/wevj15080330
                                                                  2015.  Available  from:  https://www.sfu.ca/~mbahrami/pdf/
            52.  Jaguemont  J,  Darwiche  A,  Bardé  F.  Optimal  fast-charging   Theses/Thesis - M. Yazdan Pour - Electro-thermal Modeling
               strategy for cylindrical li-ion cells. Highlights Veh. 2024;2:24-34.  of Lithium-ion Battery.pdf [Last accessed on 2025 Feb 27].
            53.  White G, Hales A. Novel methods for measuring the thermal   60.  Zhang L, Peng H, Ning Z, Mu Z, Sun C. Comparative
               diffusivity  and  the  thermal  conductivity  of  a  lithium-ion   research on RC equivalent circuit models for lithium-ion
               battery. Appl Therm Eng. 2022;212:118573.          batteries of electric vehicles. Appl Sci. 2017;7(10):1002.
            54.  Wu MS, Liu KH, Wang YY, Wan CC. Heat dissipation design      doi: 10.3390/app7101002



































            Volume 2 Issue 1 (2025)                         15                               doi: 10.36922/eer.7228
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