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Numerical studies of effect of integrated through-plane array flow field on novel PEFC performance using BWO algorithm under uncertainties

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  • Li, Hui
  • Eghbalian, Nasrin

Abstract

One of the essential mechanisms for polymer electrolyte FCs (PEFCs) is the flow-field plates. Two types of flow fields are serpentine channels and incorporating parallel, which is the most common models. The main objective of this paper is to model and analyse the thermodynamic performance of a novel FC. In this paper, a novel kind of PEFC is proposed, which is a new flowing field known as the through-plane array (TPA). Furthermore, a novel application of the Black Widow Optimization Algorithm (BWO) is implemented to gain unidentified parameters of the novel PEFC model. Developing a precise PEFC model is the final goal of the current work that prepares real modelling and simulation results of desired FCs. The various curves of the PEFC such as I–V, I–P, I–P–V, and I-T-Voltage are obtained via the BWO algorithm. This problem is a nonlinear model, in which the sum of the squared errors of FC. BWO algorithm is applied for objective function minimization. The predicted PEFC model is verified using measured results, which are obtained under different conditions of pressure and temperature uncertainty. Finally, a comparison between the TPA model and the other two models based on the BWO is accomplished and the superiority of the proposed technique is proved.

Suggested Citation

  • Li, Hui & Eghbalian, Nasrin, 2021. "Numerical studies of effect of integrated through-plane array flow field on novel PEFC performance using BWO algorithm under uncertainties," Energy, Elsevier, vol. 231(C).
  • Handle: RePEc:eee:energy:v:231:y:2021:i:c:s0360544221010203
    DOI: 10.1016/j.energy.2021.120772
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    1. Song, Ke & Fan, Zhixin & Hu, Xiao & Ding, Yuhang & Li, Haiyang & Xu, Hongjie & Zhang, Tong, 2021. "Effect of adding vortex promoter on the performance improvement of active air-cooled proton exchange membrane fuel cells," Energy, Elsevier, vol. 223(C).
    2. He, Pu & Mu, Yu-Tong & Park, Jae Wan & Tao, Wen-Quan, 2020. "Modeling of the effects of cathode catalyst layer design parameters on performance of polymer electrolyte membrane fuel cell," Applied Energy, Elsevier, vol. 277(C).
    3. Akrami, Ehsan & Ameri, Mohammad & Rocco, Matteo V., 2021. "Conceptual design, exergoeconomic analysis and multi-objective optimization for a novel integration of biomass-fueled power plant with MCFC-cryogenic CO2 separation unit for low-carbon power productio," Energy, Elsevier, vol. 227(C).
    4. Ji-chao, Yang & Sobhani, Behrooz, 2021. "Integration of biomass gasification with a supercritical CO2 and Kalina cycles in a combined heating and power system: A thermodynamic and exergoeconomic analysis," Energy, Elsevier, vol. 222(C).
    5. Iranzo, Alfredo & Navas, Sergio J. & Rosa, Felipe & Berber, Mohamed R., 2021. "Determination of time constants of diffusion and electrochemical processes in Polymer Electrolyte Membrane Fuel Cells," Energy, Elsevier, vol. 221(C).
    6. Ahmed M. Agwa & Attia A. El-Fergany & Gamal M. Sarhan, 2019. "Steady-State Modeling of Fuel Cells Based on Atom Search Optimizer," Energies, MDPI, vol. 12(10), pages 1-14, May.
    7. Zhao, Jian & Ozden, Adnan & Shahgaldi, Samaneh & Alaefour, Ibrahim E. & Li, Xianguo & Hamdullahpur, Feridun, 2018. "Effect of Pt loading and catalyst type on the pore structure of porous electrodes in polymer electrolyte membrane (PEM) fuel cells," Energy, Elsevier, vol. 150(C), pages 69-76.
    8. Modiri-Delshad, Mostafa & Aghay Kaboli, S. Hr. & Taslimi-Renani, Ehsan & Rahim, Nasrudin Abd, 2016. "Backtracking search algorithm for solving economic dispatch problems with valve-point effects and multiple fuel options," Energy, Elsevier, vol. 116(P1), pages 637-649.
    9. Lyu, Zewei & Meng, Hao & Zhu, Jianzhong & Han, Minfang & Sun, Zaihong & Xue, Huaqing & Zhao, Yongming & Zhang, Fudong, 2020. "Comparison of off-gas utilization modes for solid oxide fuel cell stacks based on a semi-empirical parametric model," Applied Energy, Elsevier, vol. 270(C).
    10. Kang, Yun Sik & Won, Phillip & Ko, Seung Hwan & Park, Taehyun & Yoo, Sung Jong, 2019. "Bending-durable membrane-electrode assembly using metal nanowires for bendable polymer electrolyte membrane fuel cell," Energy, Elsevier, vol. 172(C), pages 874-880.
    11. El-Fergany, Attia A., 2018. "Extracting optimal parameters of PEM fuel cells using Salp Swarm Optimizer," Renewable Energy, Elsevier, vol. 119(C), pages 641-648.
    Full references (including those not matched with items on IDEAS)

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