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Lifetime optimized charging strategy of Li-ion cells based on daily driving cycle of electric two-wheelers

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  • Rechkemmer, Sabrina Kathrin
  • Zang, Xiaoyun
  • Zhang, Weimin
  • Sawodny, Oliver

Abstract

Especially for electric two-wheelers (E2Ws), battery lifetime is a key challenge compared to electric vehicles (EVs) due to the lower battery capacity and thus higher cell-specific currents. This study therefore introduces an optimization framework for day-to-day routes in the metropolis of Shanghai with heavily frequented E2W traffic. The optimization aims at prolonging battery lifetime while not restricting the driver in their driving and usage behavior. This framework is based on accelerated aging tests of LMO cells as well as approximated battery aging and E2W powertrain models. Latter are applied to a typical driving profile of Shanghai. Central aim of the proposed framework is to identify relevant cycles and to optimize charging profiles under consideration of SOC constraints in order to extend battery lifetime. Both factors, targeted SOC and charging profiles, are known to have a significant impact on aging. Results are presented for different lengths of the driving cycle, initial SOCs, and temperatures and a heuristic charging rule is derived. One optimization scenario is validated by applying the optimal charging profile to typical cells used for E2W and by exploiting the targeted SOC as additional degree of freedom. The results are compared to a conventional strategy. Lifetime predictions expect a lifetime prolongation of half a year.

Suggested Citation

  • Rechkemmer, Sabrina Kathrin & Zang, Xiaoyun & Zhang, Weimin & Sawodny, Oliver, 2019. "Lifetime optimized charging strategy of Li-ion cells based on daily driving cycle of electric two-wheelers," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    • Handle: RePEc:eee:appene:v:251:y:2019:i:c:65
    DOI: 10.1016/j.apenergy.2019.113415
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    References listed on IDEAS

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    1. Zhang, Caiping & Jiang, Jiuchun & Gao, Yang & Zhang, Weige & Liu, Qiujiang & Hu, Xiaosong, 2017. "Charging optimization in lithium-ion batteries based on temperature rise and charge time," Applied Energy, Elsevier, vol. 194(C), pages 569-577.
    2. 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.
    3. Weiss, Martin & Patel, Martin K. & Junginger, Martin & Perujo, Adolfo & Bonnel, Pierre & van Grootveld, Geert, 2012. "On the electrification of road transport - Learning rates and price forecasts for hybrid-electric and battery-electric vehicles," Energy Policy, Elsevier, vol. 48(C), pages 374-393.
    4. repec:cdl:itsdav:qt0d05f8v9 is not listed on IDEAS
    5. Weinert, Jonathan & Ogden, Joan & Sperling, Dan & Burke, Andrew, 2008. "The future of electric two-wheelers and electric vehicles in China," Energy Policy, Elsevier, vol. 36(7), pages 2544-2555, July.
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    Cited by:

    1. Cui, Yuepeng & Xu, Hao & Zou, Fumin & Chen, Zhihui & Gong, Kuangmin, 2021. "Optimization based method to develop representative driving cycle for real-world fuel consumption estimation," Energy, Elsevier, vol. 235(C).
    2. Yang, Yang & Yuan, Wei & Zhang, Xiaoqing & Ke, Yuzhi & Qiu, Zhiqiang & Luo, Jian & Tang, Yong & Wang, Chun & Yuan, Yuhang & Huang, Yao, 2020. "A review on structuralized current collectors for high-performance lithium-ion battery anodes," Applied Energy, Elsevier, vol. 276(C).
    3. Ahmed, Abdelsalam A. & Ramadan, Haitham S., 2020. "Prototype implementation of advanced electric vehicles drivetrain system: Verification and validation," Applied Energy, Elsevier, vol. 266(C).

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