Review on li-ion battery model used in electrical vehicle

Open Access

Issue		BIO Web Conf. Volume 97, 2024 Fifth International Scientific Conference of Alkafeel University (ISCKU 2024)


Article Number		00092
Number of page(s)		8
DOI		https://doi.org/10.1051/bioconf/20249700092
Published online		05 April 2024

G. Barletta, P. DiPrima, and D. Papurello, “Thévenin’s Battery Model Parameter Estimation Based on Simulink,” Energies, vol. 15, no. 17. 2022. DOI: 10.3390/en15176207. [CrossRef] [Google Scholar]
N. Campagna et al., “Battery models for battery powered applications: A comparative study,” Energies, vol. 13, no. 15, 2020, DOI: 10.3390/en13164085. [CrossRef] [Google Scholar]
J.D. Valladolid, D. Patiño, J.P. Ortiz, I. Minchala, and G. Gruosso, “Proposal for modeling electric vehicle battery using experimental data and considering temperature effects,” in 2019 IEEE Milan PowerTech, PowerTech 2019, 2019. DOI: 10.1109/PTC.2019.8810611. [Google Scholar]
M.D. Kharisma, M. Ridwan, A.F. Ilmiawan, F. Ario Nurman, and S. Rizal, “Modeling and Simulation of Lithium-Ion Battery Pack Using Modified Battery Cell Model,” ICEVT 2019 - Proceeding: 6th International Conference on Electric Vehicular Technology 2019. pp. 25–30, 2019. DOI: 10.1109/ICEVT48285.2019.8994009. [Google Scholar]
S. Bhagat et al., “Simulation of Li-ion Battery using MATLAB-Simulink for Charging and Discharging,” E3S Web of Conferences, vol. 353. 2022. DOI: 10.1051/e3sconf/202235303001. [Google Scholar]
B.G. Kim, D.D. Patel, and Z.M. Salameh, “Circuit Model of 100 Ah Lithium Polymer Battery Cell,” Journal of Power and Energy Engineering, vol. 01, no. 06. pp. 1–8, 2013. DOI: 10.4236/jpee.2013.16001. [CrossRef] [Google Scholar]
Y. Cao, R.C. Kroeze, and P.T. Krein, “Multi-timescale parametric electrical battery model for use in dynamic electric vehicle simulations,” IEEE Trans. Transp. Electrif., vol. 2, no. 4, pp. 432–442, 2016, DOI: 10.1109/TTE.2016.2569069. [CrossRef] [Google Scholar]
R. Nemes, S. Ciornei, M. Ruba, H. Hedesiu, and C. Martis, “Modeling and simulation of first-order Li-Ion battery cell with experimental validation,” Proceedings of 2019 8th International Conference on Modern Power Systems, MPS 2019., 2019. DOI: 10.1109/MPS.2019.8759769. [Google Scholar]
Y.K. Tan, J.C. Mao, and K.J. Tseng, “Modelling of battery temperature effect on electrical characteristics of Li-ion battery in hybrid electric vehicle,” in Proceedings of the International Conference on Power Electronics and Drive Systems, 2011, pp. 637–642. DOI: 10.1109/PEDS.2011.6147318. [Google Scholar]
R.M. Spotnitz, “Battery modeling,” Electrochemical Society Interface, vol. 14, no. 4. pp. 39–42, 2005. DOI: 10.1149/2.f05054if. [CrossRef] [Google Scholar]
M. Chen and G.A. Rincon-Mora, “Accurate electrical battery model capable of predicting runtime and I-V performance,” IEEE Trans. Energy Convers., vol. 21, no. 2, pp. 504–511, Jun. 2006, DOI: 10.1109/TEC.2006.874229. [CrossRef] [Google Scholar]
A. IEEE Industrial Electronics Society. Conference (39th : 2013 : Vienna, Technische Universität Wien, Austrian Institute of Technology, IEEE Industrial Electronics Society, and Institute of Electrical and Electronics Engineers, “IECON 2013-39th Annual Conference of the IEEE Industrial Electronics Society : proceedings : Austria Center Vienna, Vienna, Austria, 10-14 November, 2013.” pp. 1729–1734, 2013. [Google Scholar]
O. Tremblay, L.A. Dessaint, and A.I. Dekkiche, “A generic battery model for the dynamic simulation of hybrid electric vehicles,” VPPC 2007 - Proceedings of the 2007 IEEE Vehicle Power and Propulsion Conference., pp. 284–289, 2007. DOI: 10.1109/VPPC.2007.4544139. [CrossRef] [Google Scholar]
E.M. Ahmed, E.A. Mohamed, A. Elmelegi, M. Aly, and O. Elbaksawi, “Optimum Modified Fractional Order Controller for Future Electric Vehicles and Renewable Energy-Based Interconnected Power Systems,” IEEE Access, vol. 9, pp. 29993–30010, 2021, DOI: 10.1109/ACCESS.2021.3058521. [CrossRef] [Google Scholar]
[K.C. Syracuse and W.D.K. Clark, “Statistical approach to domain performance modeling for oxyhalide primary lithium batteries,” in Proceedings of the Annual Battery Conference on Applications and Advances, 1997, pp. 163–166. DOI: 10.1109/bcaa.1997.574098. [Google Scholar]
M. Pedram and Qing Wu, “Design considerations for battery-powered electronics,” 2003, pp. 861–866. DOI: 10.1109/dac.1999.782166. [Google Scholar]
C.F. Chiasserini and R.R. Rao, “Energy efficient battery management,” IEEE Journal on Selected Areas in Communications, vol. 19, no. 7. pp. 1235–1245, 2001. DOI: 10.1109/49.932692. [CrossRef] [Google Scholar]
D. Panigrahi, C. Chiasserini, S. Dey, R. Rao, A. Raghunathan, and K. Lahiri, “Battery life estimation of mobile embedded systems,” Proceedings of the IEEE International Conference on VLSI Design., pp. 57–63, 2001. DOI: 10.1109/icvd.2001.902640. [Google Scholar]
J.H. Lee and I.S. Lee, “Lithium battery SOH monitoring and an SOC estimation algorithm based on the SOH result,” Energies, vol. 14, no. 15. 2021. DOI: 10.3390/en14154506. [Google Scholar]
J. Li, J. Klee Barillas, C. Guenther, and M.A. Danzer, “A comparative study of state of charge estimation algorithms for LiFePO4 batteries used in electric vehicles,” Journal of Power Sources, vol. 230. pp. 244–250, 2013. DOI: 10.1016/j.jpowsour.2012.12.057. [CrossRef] [Google Scholar]
D. Aschwanden, “Battery State of Charge Modeling”. [Google Scholar]
A. Hasan, M. Skriver, and T.A. Johansen, “Exogenous Kalman Filter for State-of-Charge Estimation in Lithium-Ion Batteries,” 2018 IEEE Conference on Control Technology and Applications, CCTA 2018. pp. 1403–1408, 2018. DOI: 10.1109/CCTA.2018.8511577. [Google Scholar]
I. Radaš, N. Pilat, D. Gnjatović, V. Šunde, and Ž. Ban, “Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current Pulse,” Energies, vol. 15, no. 18. 2022. DOI: 10.3390/en15186495. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.