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Sensor-less control of the methanol concentration of direct methanol fuel cells at varying ambient temperatures

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  • An, Myung-Gi
  • Mehmood, Asad
  • Ha, Heung Yong

Abstract

A new version of an algorithm is used to control the methanol concentration in the feed of DMFC systems without using methanol sensors under varying ambient temperatures. The methanol concentration is controlled indirectly by controlling the temperature of the DMFC stack, which correlates well with the methanol concentration. Depending on the ambient temperature relative to a preset reference temperature, two different strategies are used to control the stack temperature: either reducing the cooling rate of the methanol solution passing through an anode-side heat exchanger; or, lowering the pumping rate of the pure methanol to the depleted feed solution. The feasibility of the algorithm is evaluated using a DMFC system that consists of a 200W stack and the balance of plant (BOP). The DMFC system includes a sensor-less methanol controller that is operated using a LabView system as the central processing unit. The algorithm is experimentally confirmed to precisely control the methanol concentration and the stack temperature at target values under an environment of varying ambient temperatures.

Suggested Citation

  • An, Myung-Gi & Mehmood, Asad & Ha, Heung Yong, 2014. "Sensor-less control of the methanol concentration of direct methanol fuel cells at varying ambient temperatures," Applied Energy, Elsevier, vol. 129(C), pages 104-111.
    • Handle: RePEc:eee:appene:v:129:y:2014:i:c:p:104-111
    DOI: 10.1016/j.apenergy.2014.04.100
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    References listed on IDEAS

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    1. Achmad, F. & Kamarudin, S.K. & Daud, W.R.W. & Majlan, E.H., 2011. "Passive direct methanol fuel cells for portable electronic devices," Applied Energy, Elsevier, vol. 88(5), pages 1681-1689, May.
    2. An, Myung-Gi & Mehmood, Asad & Ha, Heung Yong, 2014. "A sensor-less methanol concentration control system based on feedback from the stack temperature," Applied Energy, Elsevier, vol. 131(C), pages 257-266.
    3. Kim, Joon-Hee & Yang, Min-Jee & Park, Jun-Young, 2014. "Improvement on performance and efficiency of direct methanol fuel cells using hydrocarbon-based membrane electrode assembly," Applied Energy, Elsevier, vol. 115(C), pages 95-102.
    4. Zainoodin, A.M. & Kamarudin, S.K. & Masdar, M.S. & Daud, W.R.W. & Mohamad, A.B. & Sahari, J., 2014. "High power direct methanol fuel cell with a porous carbon nanofiber anode layer," Applied Energy, Elsevier, vol. 113(C), pages 946-954.
    5. Mehmood, Asad & Ha, Heung Yong, 2014. "Performance restoration of direct methanol fuel cells in long-term operation using a hydrogen evolution method," Applied Energy, Elsevier, vol. 114(C), pages 164-171.
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    Citations

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    Cited by:

    1. Liu, Guicheng & Li, Xinyang & Wang, Hui & Liu, Xiuying & Chen, Ming & Woo, Jae Young & Kim, Ji Young & Wang, Xindong & Lee, Joong Kee, 2017. "Design of 3-electrode system for in situ monitoring direct methanol fuel cells during long-time running test at high temperature," Applied Energy, Elsevier, vol. 197(C), pages 163-168.
    2. An, Myung-Gi & Mehmood, Asad & Hwang, Jinyeon & Ha, Heung Yong, 2016. "A novel method of methanol concentration control through feedback of the amplitudes of output voltage fluctuations for direct methanol fuel cells," Energy, Elsevier, vol. 100(C), pages 217-226.
    3. Chi, Xuncheng & Chen, Fengxiang & Mo, Tiande & Li, Yu & Wei, Wei, 2024. "Improve methanol efficiency for direct methanol fuel cell system via investigation and control of optimal operating methanol concentration," Energy, Elsevier, vol. 290(C).
    4. Yang, Qinwen & Xiao, Gang & Li, Lexi & Che, Mengjie & Hu, Xu-Qu & Meng, Min, 2021. "Collaborative design of multi-type parameters for design and operational stage matching in fuel cells," Renewable Energy, Elsevier, vol. 175(C), pages 1101-1110.
    5. Calabriso, Andrea & Borello, Domenico & Romano, Giovanni Paolo & Cedola, Luca & Del Zotto, Luca & Santori, Simone Giovanni, 2017. "Bubbly flow mapping in the anode channel of a direct methanol fuel cell via PIV investigation," Applied Energy, Elsevier, vol. 185(P2), pages 1245-1255.
    6. Akbari, Elnaz & Buntat, Zolkafle & Nikoukar, Ali & Kheirandish, Azadeh & Khaledian, Mohsen & Afroozeh, Abdolkarim, 2016. "Sensor application in Direct Methanol Fuel Cells (DMFCs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1125-1139.
    7. Chen, Qing-Yun & Fu, Rong & Fang, Xiao-Wen & Cai, Wen-Fang & Wang, Yun-Hai & Cheng, Shao-An, 2015. "Cr-methanol fuel cell for efficient Cr(VI) removal and high power production," Applied Energy, Elsevier, vol. 138(C), pages 31-35.
    8. Chen, Fengxiang & Chi, Xuncheng & Wei, Wei & Mo, Tiande & Li, Yu, 2023. "Model-based observer for direct methanol fuel cell concentration estimation by using second-order sliding-mode algorithm," Energy, Elsevier, vol. 263(PD).

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