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Development of an empirical aging model for Li-ion batteries and application to assess the impact of Vehicle-to-Grid strategies on battery lifetime

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  • Petit, Martin
  • Prada, Eric
  • Sauvant-Moynot, Valérie

Abstract

In this paper an empirical capacity fade model for Li-ion batteries has been developed, calibrated and validated for a NCA/C and a LFP/C Li-ion cell. Based on extensive experimental work, this original, generic model is well suited for system simulation approaches, and is able to describe both cycle and calendar effects on aging. The stress factors taken into account for each aging mode are the state of charge and the temperature for calendar aging, and the temperature and the current for cycle aging. A simple approach has been adopted in order to instantaneously apply either cycle aging or calendar aging according to operating conditions and thus accurately model aging effects due to dynamic operating conditions. This model has then been coupled to an electrothermal model and integrated in a system simulation software application in order to assess the effect of charging rates, charging strategies and V2G on battery lifetime. When compared, the two battery chemistries exhibited different behaviors when submitted to V2G scenarios. Light V2G scenarios caused relatively low aging for the LFP/C based battery but tended to slightly increase the aging of the NCA/C based battery according to simulations.

Suggested Citation

  • Petit, Martin & Prada, Eric & Sauvant-Moynot, Valérie, 2016. "Development of an empirical aging model for Li-ion batteries and application to assess the impact of Vehicle-to-Grid strategies on battery lifetime," Applied Energy, Elsevier, vol. 172(C), pages 398-407.
    • Handle: RePEc:eee:appene:v:172:y:2016:i:c:p:398-407
    DOI: 10.1016/j.apenergy.2016.03.119
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    References listed on IDEAS

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    1. Marongiu, Andrea & Roscher, Marco & Sauer, Dirk Uwe, 2015. "Influence of the vehicle-to-grid strategy on the aging behavior of lithium battery electric vehicles," Applied Energy, Elsevier, vol. 137(C), pages 899-912.
    2. Sarasketa-Zabala, E. & Martinez-Laserna, E. & Berecibar, M. & Gandiaga, I. & Rodriguez-Martinez, L.M. & Villarreal, I., 2016. "Realistic lifetime prediction approach for Li-ion batteries," Applied Energy, Elsevier, vol. 162(C), pages 839-852.
    3. Bishop, Justin D.K. & Axon, Colin J. & Bonilla, David & Tran, Martino & Banister, David & McCulloch, Malcolm D., 2013. "Evaluating the impact of V2G services on the degradation of batteries in PHEV and EV," Applied Energy, Elsevier, vol. 111(C), pages 206-218.
    4. Björn Nykvist & Måns Nilsson, 2015. "Rapidly falling costs of battery packs for electric vehicles," Nature Climate Change, Nature, vol. 5(4), pages 329-332, April.
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