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Application of Li-Ion Cell Aging Models on Automotive Electrical Propulsion Cells

  • Davide TarsitanoEmail author
  • Federico Perelli
  • Francesco Braghin
  • Ferdinando Luigi Mapelli
  • Zhi Zhang
Conference paper
Part of the Lecture Notes in Mobility book series (LNMOB)

Abstract

In this paper the capacity fade of a Li-Ion battery for electric and hybrid vehicles is studied. The battery lifetime is a crucial characteristic for the usage of this technology on Full Electrical Vehicle (EV) or Hybrid Electrical Vehicle (HEV). Thanks to low costs and easy electronic devices design for small Li-Ion battery tests, many studies have established life prediction models.

The aim of this paper is to verify whether these models can be used to predict capacity fade for a high capacity Li-Ion battery for full electric and hybrid vehicles, or not.

During this study a test bench has been developed to control charge and discharge cell current. At last a comparison between different models will be provided.

Keywords

Li-Ion battery automation propulsion cell aging model battery life prediction 

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References

  1. 1.
    Mapelli, F.L., Tarsitano, D.: Energy control for plug-in hev with ultracapacitors lithium-ion batteries storage system for fia alternative energy cup race. In: 2010 IEEE Vehicle Power and Propulsion Conference (VPPC), pp. 1–6 (2010)Google Scholar
  2. 2.
    Mapelli, F.L., Tarsitano, D., Annese, D., Sala, M., Bosia, G.: A study of urban electric bus with a fast charging energy storage system based on lithium battery and superca-pacitors. In: 8th International Conference and Exhibition on Ecological Vehicles and Renewable Energies (EVER), pp. 1–9 (2013)Google Scholar
  3. 3.
    Vetter, J., Novák, P., Wagner, M., Veit, C., Möller, K., Besenhard, J., Winter, M., Wohlfahrt-Mehrens, M., Vogler, C., Hammouche, A.: Aging mechanisms in lithium-ion batteries. Journal of Power Sources 147(1-2), 269–281 (2005)CrossRefGoogle Scholar
  4. 4.
    Uno, M., Tanaka, K.: Accelerated aging testing and cycle life prediction of superca-pacitors for alternative battery applications. In: 2011 IEEE 33rd International Telecommunications Energy Conference (INTELEC), pp. 1–6 (2011)Google Scholar
  5. 5.
    Wang, J., Liu, P., Hicks-Garner, J., Sherman, E., Soukiazian, S., Verbrugge, M., Tataria, H., Musser, J., Finamore, P.: Cycle-life model for graphite-LiFePO4 cells. Journal of Power Sources 196(8), 3942–3948 (2011)CrossRefGoogle Scholar
  6. 6.
    Pradai, E., Di Domenico, D., Creff, Y., Bernard, J., Sauvant-Moynot, V., Huet, F.: Physics-based modeling of LiFeP04-graphite Li-ion batteries for Power and Capacity fade predictions: Application to calendar aging of PHEV and EV. In: Vehicle Power and Propulsion Conference (VPPC), pp. 301–308 (2012)Google Scholar
  7. 7.
    Sauer, D., Wenzl, H.: Comparison of different approaches for lifetime prediction of electrochemical systems — Using lead-acid batteries as example. Journal of Power Sources 176(2), 534–546 (2008)CrossRefGoogle Scholar
  8. 8.
    Marano, V., Onori, S., Guezennec, Y., Rizzoni, G., Madella, N.: Lithium-ion batteries life estimation for plug-in hybrid electric vehicles. In: IEEE Vehicle Power and Propulsion Conference, pp. 536–543 (2009)Google Scholar
  9. 9.
    Majima, M., Ujiie, S., Yagasaki, E., Koyama, K., Inazawa, S.: Development of long life lithium ion battery for power storage. Journal of Power Sources 101, 53–59 (2001)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Davide Tarsitano
    • 1
    Email author
  • Federico Perelli
    • 1
  • Francesco Braghin
    • 1
  • Ferdinando Luigi Mapelli
    • 1
  • Zhi Zhang
    • 1
  1. 1.Department of MechanicsPolitecnico di MilanoMilanItaly

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