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Dynamic electro-thermal modeling of all-vanadium redox flow battery with forced cooling strategies

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  • Wei, Zhongbao
  • Zhao, Jiyun
  • Xiong, Binyu

Abstract

The present study focuses on the dynamic electro-thermal modeling for the all-vanadium redox flow battery (VRB) with forced cooling strategies. The Foster network is adopted to dynamically model the heat dissipation of VRB with heat exchangers. The parameters of Foster network are extracted by fitting the step response of it to the results of linearized CFD model. Then a complete electro-thermal model is proposed by coupling the heat generation model, Foster network and electrical model. Results show that the established model has nearly the same accuracy with the nonlinear CFD model in electrolyte temperature prediction but drastically improves the computational efficiency. The modeled terminal voltage is also benchmarked with the experimental data under different current densities. The electrolyte temperature is found to be significantly influenced by the flow rate of coolant. As compared, although the electrolyte flow rate has unremarkable impact on electrolyte temperature, its effect on system pressure drop and battery efficiency is significant. Increasing the electrolyte flow rate improves the coulombic efficiency, voltage efficiency and energy efficiency simultaneously but at the expense of higher pump power demanded. An optimal flow rate exists for each operating condition to maximize the system efficiency.

Suggested Citation

  • Wei, Zhongbao & Zhao, Jiyun & Xiong, Binyu, 2014. "Dynamic electro-thermal modeling of all-vanadium redox flow battery with forced cooling strategies," Applied Energy, Elsevier, vol. 135(C), pages 1-10.
    • Handle: RePEc:eee:appene:v:135:y:2014:i:c:p:1-10
    DOI: 10.1016/j.apenergy.2014.08.062
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    7. Wei, Zhongbao & Meng, Shujuan & Xiong, Binyu & Ji, Dongxu & Tseng, King Jet, 2016. "Enhanced online model identification and state of charge estimation for lithium-ion battery with a FBCRLS based observer," Applied Energy, Elsevier, vol. 181(C), pages 332-341.
    8. Chou, Yi-Sin & Hsu, Ning-Yih & Jeng, King-Tsai & Chen, Kuan-Hsiang & Yen, Shi-Chern, 2016. "A novel ultrasonic velocity sensing approach to monitoring state of charge of vanadium redox flow battery," Applied Energy, Elsevier, vol. 182(C), pages 253-259.
    9. Trovò, Andrea & Marini, Giacomo & Sutto, Alessandro & Alotto, Piergiorgio & Giomo, Monica & Moro, Federico & Guarnieri, Massimo, 2019. "Standby thermal model of a vanadium redox flow battery stack with crossover and shunt-current effects," Applied Energy, Elsevier, vol. 240(C), pages 893-906.
    10. Wu, Maochun & Liu, Mingyao & Long, Guifa & Wan, Kai & Liang, Zhenxing & Zhao, Tim S., 2014. "A novel high-energy-density positive electrolyte with multiple redox couples for redox flow batteries," Applied Energy, Elsevier, vol. 136(C), pages 576-581.
    11. Wang, Tao & Fu, Jiahui & Zheng, Menglian & Yu, Zitao, 2018. "Dynamic control strategy for the electrolyte flow rate of vanadium redox flow batteries," Applied Energy, Elsevier, vol. 227(C), pages 613-623.
    12. Zhou, X.L. & Zhao, T.S. & An, L. & Zeng, Y.K. & Yan, X.H., 2015. "A vanadium redox flow battery model incorporating the effect of ion concentrations on ion mobility," Applied Energy, Elsevier, vol. 158(C), pages 157-166.
    13. Shu-Ling Huang & Chi-Ping Li & Chia-Chin Chang & Chen-Chen Tseng & Ming-Wei Wang & Mei-Ling Chen, 2020. "Real-Time Monitoring of the Thermal Effect for the Redox Flow Battery by an Infrared Thermal Imaging Technology," Energies, MDPI, vol. 13(24), pages 1-19, December.
    14. Wei, Zhongbao & Lim, Tuti Mariana & Skyllas-Kazacos, Maria & Wai, Nyunt & Tseng, King Jet, 2016. "Online state of charge and model parameter co-estimation based on a novel multi-timescale estimator for vanadium redox flow battery," Applied Energy, Elsevier, vol. 172(C), pages 169-179.
    15. Wei, Zhongbao & Zhao, Jiyun & Ji, Dongxu & Tseng, King Jet, 2017. "A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model," Applied Energy, Elsevier, vol. 204(C), pages 1264-1274.
    16. Guarnieri, Massimo & Trovò, Andrea & Picano, Francesco, 2020. "Enhancing the efficiency of kW-class vanadium redox flow batteries by flow factor modulation: An experimental method," Applied Energy, Elsevier, vol. 262(C).
    17. Alejandro Clemente & Ramon Costa-Castelló, 2020. "Redox Flow Batteries: A Literature Review Oriented to Automatic Control," Energies, MDPI, vol. 13(17), pages 1-31, September.
    18. Bo Li & Wenhao Wang & Shaoyi Bei & Zhengqiang Quan, 2022. "Analysis of Heat Dissipation Performance of Battery Liquid Cooling Plate Based on Bionic Structure," Sustainability, MDPI, vol. 14(9), pages 1-16, May.
    19. Ivan Kuzmin & Alexey Loskutov & Evgeny Osetrov & Andrey Kurkin, 2022. "Source for Autonomous Power Supply System Based on Flow Battery," Energies, MDPI, vol. 15(9), pages 1-15, April.

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