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Dynamic modeling of a microbial fuel cell considering anodic electron flow and electrical charge storage

Author

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  • Park, Jae-Do
  • Roane, Timberley M.
  • Ren, Zhiyong Jason
  • Alaraj, Muhannad

Abstract

To describe the anodic electron flow and electric charge storage behavior of an MFC system from an electrical perspective, a dynamic model based on a novel electrical equivalent circuit is developed. Conventional equivalent circuits typically have series impedances to model the system from the standpoint of terminal quantities: output voltage and current. However, the conventional approaches do not properly explain internal anodic electron flow and double-layer charge storage characteristics of MFCs. The proposed model uses an equivalent capacitance in parallel and series resistances to accurately model and characterize the anodic electron flow, electrical charge storage, and the dynamic characteristics of both output voltage and current. Two straightforward test methods are proposed to determine the equivalent circuit parameters. Experimental results showed the validity of proposed MFC model.

Suggested Citation

  • Park, Jae-Do & Roane, Timberley M. & Ren, Zhiyong Jason & Alaraj, Muhannad, 2017. "Dynamic modeling of a microbial fuel cell considering anodic electron flow and electrical charge storage," Applied Energy, Elsevier, vol. 193(C), pages 507-514.
    • Handle: RePEc:eee:appene:v:193:y:2017:i:c:p:507-514
    DOI: 10.1016/j.apenergy.2017.02.055
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    References listed on IDEAS

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    1. Chen, Zeyu & Xiong, Rui & Tian, Jinpeng & Shang, Xiong & Lu, Jiahuan, 2016. "Model-based fault diagnosis approach on external short circuit of lithium-ion battery used in electric vehicles," Applied Energy, Elsevier, vol. 184(C), pages 365-374.
    2. Pandey, Prashant & Shinde, Vikas N. & Deopurkar, Rajendra L. & Kale, Sharad P. & Patil, Sunil A. & Pant, Deepak, 2016. "Recent advances in the use of different substrates in microbial fuel cells toward wastewater treatment and simultaneous energy recovery," Applied Energy, Elsevier, vol. 168(C), pages 706-723.
    3. Tanaka, T. & Ito, S. & Muramatsu, M. & Yamada, T. & Kamiko, H. & Kakimoto, N. & Inui, Y., 2015. "Accurate and versatile simulation of transient voltage profile of lithium-ion secondary battery employing internal equivalent electric circuit," Applied Energy, Elsevier, vol. 143(C), pages 200-210.
    4. Mingant, R. & Bernard, J. & Sauvant-Moynot, V., 2016. "Novel state-of-health diagnostic method for Li-ion battery in service," Applied Energy, Elsevier, vol. 183(C), pages 390-398.
    5. Ng, Kong Soon & Moo, Chin-Sien & Chen, Yi-Ping & Hsieh, Yao-Ching, 2009. "Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries," Applied Energy, Elsevier, vol. 86(9), pages 1506-1511, September.
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    Cited by:

    1. Wang, Chin-Tsan & Huang, Yan-Sian & Sangeetha, Thangavel & Yan, Wei-Mon, 2018. "Assessment of recirculation batch mode operation in bufferless Bio-cathode microbial Fuel Cells (MFCs)," Applied Energy, Elsevier, vol. 209(C), pages 120-126.
    2. Santoro, Carlo & Abad, Fernando Benito & Serov, Alexey & Kodali, Mounika & Howe, Kerry J. & Soavi, Francesca & Atanassov, Plamen, 2017. "Supercapacitive microbial desalination cells: New class of power generating devices for reduction of salinity content," Applied Energy, Elsevier, vol. 208(C), pages 25-36.

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