Open Access
| Issue |
E3S Web Conf.
Volume 108, 2019
Energy and Fuels 2018
|
|
|---|---|---|
| Article Number | 01017 | |
| Number of page(s) | 10 | |
| Section | Energy | |
| DOI | https://doi.org/10.1051/e3sconf/201910801017 | |
| Published online | 05 July 2019 | |
- L. Kasprzyk, K. Bednarek, The selection of hybrid energy storage for electrical vehicle. Przegląd Elektrotechniczny 91, no 12, 129–132, (2015) [Google Scholar]
- M. Y. Ayad, M. Becherif, A. Aboubou, M. Wack, Electrical Vehicle Hybridized by Supercapacitors, IEEE International Energy Conference, pp. 79-84, (2010) [Google Scholar]
- N. Omar, M. A. Monem, Y. Firouz, J. Salminen, J. Smekens, O. Hegazy, H. Gaulous, G. Mulder, P. Van den Bossche, T. Coosemans, J. Van Mierlo, Lithium-iron phosphate based battery – Assessment of the aging parameters and development of cycle life model, Applied Energy 113, 1575–1585, (2014) [Google Scholar]
- J. Wang, P. Liu, J. Hicks-Garner, E. Sherman, S. Soukiazian, M. Verbrugge, H. Tataria, J. Musser, P. Finamore, Cycle-life model for graphite-LiFePO4 cells, Journal of Power Sources 196, 3942-3948, (2011) [Google Scholar]
- A. J. Bard, L. R. Faulkner, Electrochemical methods: Fundamentals and Applications, Second Edition. John Wiley & Sons, (2001) [Google Scholar]
- H. J. Bergveld, Battery Management Systems Design by Modelling. University Press Facilities, Eindhoven, pp. 55–67 (2001) [Google Scholar]
- K. A. Smith, Ch. Rahn, Ch. Wang, Control oriented 1D electrochemical model of lithium-ion battery, Energy Conversion and Management 48, 2565–2578 (2007) [Google Scholar]
- E. Prada, D. Di Domenico, Y. Creff, J. Bernard, V. Sauvant-Moynot, A coupled 0D electrochemical ageing & electro-thermal Li-ion modeling approach for HEV/PHEV. IEEE Vehicle Power and Propulsion Conference, (2011) [Google Scholar]
- A. Rahmoun, H. Biechl, Modelling of Li-ion batteries using equivalent circuit diagrams. Przegląd Elektrotechniczny 88, no 7b, 152–156 (2012) [Google Scholar]
- U. Westerhoff, K. Kurbach, F. Lienesch, M. Kurrat, Analysis of Lithium-Ion Battery Models Based on Electrochemical Impedance Spectroscopy. Energy Technology 4, 1620–1630, (2016) [CrossRef] [Google Scholar]
- M. Ceraolo, New dynamical models of lead-acid batteries. IEEE Transactions On Power Systems 15, No.4, (November 2000) [Google Scholar]
- D. Burzynski, L. Kasprzyk, Modelling and simulation of lead-acid battery pack powering electric vehicle. E3S Web of Conferences 14, doi: 10.1051/e3sconf/20171401041 (2017) [CrossRef] [EDP Sciences] [Google Scholar]
- L. Kasprzyk, Modelling and analysis of dynamic states of the lead-acid batteries in electric vehicles. Eksploatacja i Niezawodnosc Maintenance and Reliability 19, no 2, 229–236, http://dx.doi.org/10.17531/ein.2017.2.10 (2017) [CrossRef] [Google Scholar]
- L. Kasprzyk, K. Bednarek, D. Burzyński, Symulacja pracy akumulatorów kwasowoołowiowych. Przegląd Elektrotechniczny 12, pp. 61–64, (2016) [Google Scholar]
- C. Hendricks, N. Williard, S. Mathew, M. Pecht, A failure modes, mechanisms, and effects analysis (FMMEA) of lithium-ion batteries, Journal of Power Sources 297, 113120, (2015) [Google Scholar]
- J. Vetter, P. Novak, M. R. Wagner, C. Veit, K.-C. Möller, J. O. Besenhard, M. Winter, M. Wohlfahrt-Mehrens, C. Vogler, A. Hammouche, Ageing mechanisms in lithium-ion batteries, Journal of Power Sources 147, 269–281, (2005) [Google Scholar]
- Ch. R. Birkl, Matthew R. Roberts, E. McTurk, P. G. Bruce, D. A. Howey, Degradation diagnostics for lithium-ion cell, Journal of Power Sources 341, 373–386, (2017) [Google Scholar]
- S. J. An, J. Li, C. Daniel, D. Mohanty, S. Nagpure, D. L. Wood III, The state of understanding of the lithium-ion-battery graphite solid electrolyte interphase (SEI) and its relationship to formation cycling, Carbon 105, 52–76, (2016) [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.