Long-term Evaluation of the State-of-Health of Traction Lithium-ion Batteries in Operational Buses

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Published May 30, 2022
Miguel Simão
Rune Prytz Sławomir Nowaczyk

Abstract

In this paper, we present and evaluate a novel methodology to estimate the usable capacity and state-of-health (SOH) of lithium-ion batteries in battery-electric buses (BEV). This methodology is designed to be applicable to any BEV in normal operation, independently of battery chemistry, and without requiring complex electrochemical models or large data sets. We have tested the proposed methodology on two vehicle fleets with a total of 105 vehicles, for which we have been acquiring data for up to three years. Additionally, we have analysed the operation of the fleets in terms of daily distance driven and the charging strategies chosen by the operators.
The monitored vehicles are part of fleets currently in normal operation in Europe. The data collection is done with a third-party data logger that is connected to the vehicles’ Communication Area Network (CAN) buses, and no additional changes were made to the vehicle’s hardware or software. The results show that the proposed methodology shows significantly lower variance in SOH estimation than the alternative methodologies. It also shows similar accuracy in the long-term and smaller short-term deviations from the typical capacity fade model.

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Keywords

electric vehicles, battery prognostics, state-of-health, fleet management

References
Andre, D., Meiler, M., Steiner, K., Wimmer, C., Soczka-Guth, T., & Sauer, D. (2011). Characterization of high-power lithium-ion batteries by electrochemical impedance spectroscopy. i. experimental investigation. Journal of Power Sources, 196(12), 5334-5341. doi: https://doi.org/10.1016/j.jpowsour.2010.12.102
Berecibar, M., Gandiaga, I., Villarreal, I., Omar, N., Mierlo, J. V., & Bossche, P. V. D. (2016, 4). Critical review of state of health estimation methods of li-ion batteries for real applications. Renewable and Sustainable Energy Reviews, 56, 572-587. doi: 10.1016/J.RSER.2015.11.042
Gismero, A., Schaltz, E., & Stroe, D.-I. (2020). Recursive state of charge and state of health estimation method for lithium-ion batteries based on coulomb counting and open circuit voltage. Energies, 13(7). doi: 10.3390/en13071811
Li, W., Sengupta, N., Dechent, P., Howey, D., Annaswamy, A., & Sauer, D. U. (2021, 1). Online capacity estimation of lithium-ion batteries with deep long short-term memory networks. Journal of Power Sources, 482, 228863. doi: 10.1016/J.JPOWSOUR.2020.228863
Li, Y., Liu, K., Foley, A. M., Zülke, A., Berecibar, M., Nanini-Maury, E., . . . Hoster, H. E. (2019). Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review. Renewable and Sustainable Energy Reviews, 113, 109254. doi: https://doi.org/10.1016/j.rser.2019.109254
Lipu, M. H., Hannan, M., Hussain, A., Hoque, M., Ker, P. J., Saad, M., & Ayob, A. (2018). A review of state of health and remaining useful life estimation methods for lithium-ion battery in electric vehicles: Challenges and recommendations. Journal of Cleaner Production, 205, 115-133. doi: https://doi.org/10.1016/j.jclepro.2018.09.065
Ng, K. S., Moo, C.-S., Chen, Y.-P., & Hsieh, Y.-C. (2009). Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries. Applied Energy, 86(9), 1506–1511. doi: https://doi.org/10.1016/j.apenergy.2008.11.021
Pastor-Fernández, C., Uddin, K., Chouchelamane, G. H., Widanage, W. D., & Marco, J. (2017). A comparison between electrochemical impedance spectroscopy and incremental capacity-differential voltage as li-ion diagnostic techniques to identify and quantify the effects of degradation modes within battery management systems. Journal of Power Sources, 360, 301-318. doi: https://doi.org/10.1016/j.jpowsour.2017.03.042
Vichard, L., Ravey, A., Venet, P., Harel, F., Pelissier, S., & Hissel, D. (2021, 6). A method to estimate battery soh indicators based on vehicle operating data only. Energy, 225, 120235. doi: 10.1016/J.ENERGY.2021.120235
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Technical Briefs