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Assessing the potential of a hybrid battery system to reduce battery aging in an electric vehicle by studying the cycle life of a graphite∣NCA high energy and a LTO∣metal oxide high power battery cell considering realistic test profiles

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  • Wegmann, Raphael
  • Döge, Volker
  • Sauer, Dirk Uwe

Abstract

The utilization of a hybrid battery system (combination of different battery packs via dc/dc converter) in an electric vehicle application is discussed. It is investigated whether battery aging in an electric vehicle can be reduced by using a hybrid battery system. Cycle aging measurements of lithium-ion battery cells were performed at 23 °C against the background of the latter application. Recommendations for hybrid battery system electric vehicle operation are given. For Panasonic NCR 18650 BD cylindrical high energy cells (graphite anode, Li(NiCoAl) O2 cathode), three cycle aging campaigns were conducted systematically, evaluating the impact of charging as well as discharging loads with different time scales and microcycling per driving distance. A significant impact of recuperation pulse duration on aging per driving distance could be observed, whereas varied discharge load characteristics did not vary the aging characteristics. On the basis of differential open circuit voltage analysis, possible degradation mechanisms are discussed. The main driver of capacity loss and resistance increase in cycle aging campaigns with real world driving cycles appears to be the loss of cyclable lithium. Within the operating conditions investigated here, anode aging is intensified with increasing recuperation pulse duration. Another cycle aging campaign with symmetric current rate of 10C for a prismatic high power battery cell (Li4Ti5O12 anode, metal oxide cathode) yielded excellent cycle performance of this cell.

Suggested Citation

  • Wegmann, Raphael & Döge, Volker & Sauer, Dirk Uwe, 2018. "Assessing the potential of a hybrid battery system to reduce battery aging in an electric vehicle by studying the cycle life of a graphite∣NCA high energy and a LTO∣metal oxide high power battery cell," Applied Energy, Elsevier, vol. 226(C), pages 197-212.
  • Handle: RePEc:eee:appene:v:226:y:2018:i:c:p:197-212
    DOI: 10.1016/j.apenergy.2018.05.104
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    References listed on IDEAS

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    1. Castaings, Ali & Lhomme, Walter & Trigui, Rochdi & Bouscayrol, Alain, 2016. "Comparison of energy management strategies of a battery/supercapacitors system for electric vehicle under real-time constraints," Applied Energy, Elsevier, vol. 163(C), pages 190-200.
    2. Rothgang, Susanne & Baumhöfer, Thorsten & van Hoek, Hauke & Lange, Tobias & De Doncker, Rik W. & Sauer, Dirk Uwe, 2015. "Modular battery design for reliable, flexible and multi-technology energy storage systems," Applied Energy, Elsevier, vol. 137(C), pages 931-937.
    3. Eddahech, Akram & Briat, Olivier & Vinassa, Jean-Michel, 2015. "Performance comparison of four lithium–ion battery technologies under calendar aging," Energy, Elsevier, vol. 84(C), pages 542-550.
    4. Wieczorek, Maciej & Lewandowski, Mirosław, 2017. "A mathematical representation of an energy management strategy for hybrid energy storage system in electric vehicle and real time optimization using a genetic algorithm," Applied Energy, Elsevier, vol. 192(C), pages 222-233.
    5. Trovão, João P. & Silva, Mário A. & Antunes, Carlos Henggeler & Dubois, Maxime R., 2017. "Stability enhancement of the motor drive DC input voltage of an electric vehicle using on-board hybrid energy storage systems," Applied Energy, Elsevier, vol. 205(C), pages 244-259.
    6. Xiong, Rui & Duan, Yanzhou & Cao, Jiayi & Yu, Quanqing, 2018. "Battery and ultracapacitor in-the-loop approach to validate a real-time power management method for an all-climate electric vehicle," Applied Energy, Elsevier, vol. 217(C), pages 153-165.
    7. Zhang, Shuo & Xiong, Rui & Cao, Jiayi, 2016. "Battery durability and longevity based power management for plug-in hybrid electric vehicle with hybrid energy storage system," Applied Energy, Elsevier, vol. 179(C), pages 316-328.
    8. Hannan, M.A. & Hoque, M.M. & Mohamed, A. & Ayob, A., 2017. "Review of energy storage systems for electric vehicle applications: Issues and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 771-789.
    9. Zhang, Shuo & Xiong, Rui & Sun, Fengchun, 2017. "Model predictive control for power management in a plug-in hybrid electric vehicle with a hybrid energy storage system," Applied Energy, Elsevier, vol. 185(P2), pages 1654-1662.
    10. Wang, Bin & Xu, Jun & Cao, Binggang & Ning, Bo, 2017. "Adaptive mode switch strategy based on simulated annealing optimization of a multi-mode hybrid energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 194(C), pages 596-608.
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    1. Dongcheul Lee & Boram Koo & Chee Burm Shin & So-Yeon Lee & Jinju Song & Il-Chan Jang & Jung-Je Woo, 2019. "Modeling the Effect of the Loss of Cyclable Lithium on the Performance Degradation of a Lithium-Ion Battery," Energies, MDPI, vol. 12(22), pages 1-14, November.
    2. Li, Shuangqi & He, Hongwen & Su, Chang & Zhao, Pengfei, 2020. "Data driven battery modeling and management method with aging phenomenon considered," Applied Energy, Elsevier, vol. 275(C).
    3. Li, Dezhi & Li, Shuo & Zhang, Shubo & Sun, Jianrui & Wang, Licheng & Wang, Kai, 2022. "Aging state prediction for supercapacitors based on heuristic kalman filter optimization extreme learning machine," Energy, Elsevier, vol. 250(C).

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