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Application-specific electrical characterization of high power batteries with lithium titanate anodes for electric vehicles

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  • Farmann, Alexander
  • Waag, Wladislaw
  • Sauer, Dirk Uwe

Abstract

This study shows results of extensive experimental measurements performed on high power lithium titanate based batteries. Characterization tests are performed over a wide temperature range (−20 °C – +40 °C) by employing electrochemical impedance spectroscopy and modified hybrid pulse power characterization tests. Furthermore, the behavior of battery impedance parameters over the battery lifetime with regard to temperature, State-of-Charge and their influence on available battery power in an example of electric vehicles is discussed. Based on extracted parameters, a reduced order equivalent circuit model considering the nonlinearity of the charge transfer resistance is parametrized. The obtained results indicate that ohmic resistance increases with decreasing State-of-Charge while the shape of the curve remains almost constant over the battery lifetime. The total impedance determined at 1 mHz shows almost no dependence on State-of-Charge and remains constant over the whole State-of-Charge range. The necessity of considering the impact of the current dependence of the direct current resistance at least at low temperatures (i.e., below 0 °C) is confirmed. Moreover, by investigating the Butler-Volmer equation the behavior of exchange current density and symmetry factor is analyzed for various temperatures and State-of-Charges over the battery lifetime.

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  • Farmann, Alexander & Waag, Wladislaw & Sauer, Dirk Uwe, 2016. "Application-specific electrical characterization of high power batteries with lithium titanate anodes for electric vehicles," Energy, Elsevier, vol. 112(C), pages 294-306.
    • Handle: RePEc:eee:energy:v:112:y:2016:i:c:p:294-306
    DOI: 10.1016/j.energy.2016.06.088
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    1. Firouz, Y. & Relan, R. & Timmermans, J.M. & Omar, N. & Van den Bossche, P. & Van Mierlo, J., 2016. "Advanced lithium ion battery modeling and nonlinear analysis based on robust method in frequency domain: Nonlinear characterization and non-parametric modeling," Energy, Elsevier, vol. 106(C), pages 602-617.
    2. Xuebing Han & Minggao Ouyang & Languang Lu & Jianqiu Li, 2014. "Cycle Life of Commercial Lithium-Ion Batteries with Lithium Titanium Oxide Anodes in Electric Vehicles," Energies, MDPI, vol. 7(8), pages 1-15, July.
    3. Yanhui, Zhang & Wenji, Song & Guoqing, Xu, 2014. "Relaxation effect analysis on the initial state of charge for LiNi0.5Co0.2Mn0.3O2/graphite battery," Energy, Elsevier, vol. 74(C), pages 368-373.
    4. Chen, Zeyu & Xiong, Rui & Cao, Jiayi, 2016. "Particle swarm optimization-based optimal power management of plug-in hybrid electric vehicles considering uncertain driving conditions," Energy, Elsevier, vol. 96(C), pages 197-208.
    5. Tanim, Tanvir R. & Rahn, Christopher D. & Wang, Chao-Yang, 2015. "State of charge estimation of a lithium ion cell based on a temperature dependent and electrolyte enhanced single particle model," Energy, Elsevier, vol. 80(C), pages 731-739.
    6. Suri, Girish & Onori, Simona, 2016. "A control-oriented cycle-life model for hybrid electric vehicle lithium-ion batteries," Energy, Elsevier, vol. 96(C), pages 644-653.
    7. Xia, Bizhong & Chen, Chaoren & Tian, Yong & Wang, Mingwang & Sun, Wei & Xu, Zhihui, 2015. "State of charge estimation of lithium-ion batteries based on an improved parameter identification method," Energy, Elsevier, vol. 90(P2), pages 1426-1434.
    8. Dong, Guangzhong & Zhang, Xu & Zhang, Chenbin & Chen, Zonghai, 2015. "A method for state of energy estimation of lithium-ion batteries based on neural network model," Energy, Elsevier, vol. 90(P1), pages 879-888.
    9. Waag, Wladislaw & Käbitz, Stefan & Sauer, Dirk Uwe, 2013. "Experimental investigation of the lithium-ion battery impedance characteristic at various conditions and aging states and its influence on the application," Applied Energy, Elsevier, vol. 102(C), pages 885-897.
    10. Galeotti, Matteo & Cinà, Lucio & Giammanco, Corrado & Cordiner, Stefano & Di Carlo, Aldo, 2015. "Performance analysis and SOH (state of health) evaluation of lithium polymer batteries through electrochemical impedance spectroscopy," Energy, Elsevier, vol. 89(C), pages 678-686.
    11. Saw, L.H. & Ye, Y. & Tay, A.A.O., 2014. "Electro-thermal analysis and integration issues of lithium ion battery for electric vehicles," Applied Energy, Elsevier, vol. 131(C), pages 97-107.
    12. Cheng, Yujie & Lu, Chen & Li, Tieying & Tao, Laifa, 2015. "Residual lifetime prediction for lithium-ion battery based on functional principal component analysis and Bayesian approach," Energy, Elsevier, vol. 90(P2), pages 1983-1993.
    13. Yang, Zunxian & Meng, Qing & Guo, Zaiping & Yu, Xuebin & Guo, Tailiang & Zeng, Rong, 2013. "Highly reversible lithium storage in uniform Li4Ti5O12/carbon hybrid nanowebs as anode material for lithium-ion batteries," Energy, Elsevier, vol. 55(C), pages 925-932.
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    3. Ji’ang Zhang & Ping Wang & Yushu Liu & Ze Cheng, 2021. "Variable-Order Equivalent Circuit Modeling and State of Charge Estimation of Lithium-Ion Battery Based on Electrochemical Impedance Spectroscopy," Energies, MDPI, vol. 14(3), pages 1-20, February.
    4. Wang, Mingyue & Huang, Ying & Wang, Ke & Zhu, Yade & Zhang, Na & Zhang, Hongming & Li, Suping & Feng, Zhenhe, 2018. "PVD synthesis of binder-free silicon and carbon coated 3D α-Fe2O3 nanorods hybrid films as high-capacity and long-life anode for flexible lithium-ion batteries," Energy, Elsevier, vol. 164(C), pages 1021-1029.
    5. Farmann, Alexander & Sauer, Dirk Uwe, 2018. "Comparative study of reduced order equivalent circuit models for on-board state-of-available-power prediction of lithium-ion batteries in electric vehicles," Applied Energy, Elsevier, vol. 225(C), pages 1102-1122.
    6. Wang, Kangkang & Gao, Fei & Zhu, Yanli & Liu, Hao & Qi, Chuang & Yang, Kai & Jiao, Qingjie, 2018. "Internal resistance and heat generation of soft package Li4Ti5O12 battery during charge and discharge," Energy, Elsevier, vol. 149(C), pages 364-374.
    7. Zhang, Yuan Ci & Briat, Olivier & Boulon, Loïc & Deletage, Jean-Yves & Martin, Cyril & Coccetti, Fabio & Vinassa, Jean-Michel, 2019. "Non-isothermal Ragone plots of Li-ion cells from datasheet and galvanostatic discharge tests," Applied Energy, Elsevier, vol. 247(C), pages 703-715.
    8. Theodoros Kalogiannis & Md Sazzad Hosen & Mohsen Akbarzadeh Sokkeh & Shovon Goutam & Joris Jaguemont & Lu Jin & Geng Qiao & Maitane Berecibar & Joeri Van Mierlo, 2019. "Comparative Study on Parameter Identification Methods for Dual-Polarization Lithium-Ion Equivalent Circuit Model," Energies, MDPI, vol. 12(21), pages 1-35, October.
    9. Rogers, Daniel J. & Aslett, Louis J.M. & Troffaes, Matthias C.M., 2021. "Modelling of modular battery systems under cell capacity variation and degradation," Applied Energy, Elsevier, vol. 283(C).
    10. Cheng Siong Chin & Zuchang Gao & Joel Hay King Chiew & Caizhi Zhang, 2018. "Nonlinear Temperature-Dependent State Model of Cylindrical LiFePO 4 Battery for Open-Circuit Voltage, Terminal Voltage and State-of-Charge Estimation with Extended Kalman Filter," Energies, MDPI, vol. 11(9), pages 1-28, September.

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