Design and optimization of bio-inspired wave-like channel for a PEM fuel cell applying genetic algorithm
Genchun Cai,
Yunmin Liang,
Zhichun Liu and
Wei Liu
Energy, 2020, vol. 192, issue C
Abstract:
Channel shape design has a significant effect on the performance of a proton exchange membrane fuel cell. Inspired by the fins of cuttlefish, a bio-inspired wave-like structure is designed and applied to the channel of fuel cells. The impact of this bio-inspired wave-like channel on fuel cell performance is investigated through a three-dimensional and non-isothermal model developed in COMSOL Multiphysics. The effects of channel center amplitude and number of wave cycles on the current density and pressure drop of fuel cells are studied. Compared with fuel cells with basic straight channel and conventional wave-like channel, the results show that fuel cell with this bio-inspired wave-like channel has high efficiency and low flow resistance, which can obtain better comprehensive performance. In addition, an optimization of the waveform for bio-inspired wave-like channel is performed by genetic algorithm in consideration of the output power and power consumption of flow. The optimal channel with a center amplitude of 0.305 mm and the number of wave cycles of 3.52 improves the output power density by 2.2%.
Keywords: Proton exchange membrane fuel cell; Bio-inspired wave-like flow channel; Current density; Pressure drop; Genetic algorithm (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (43)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544219323655
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:192:y:2020:i:c:s0360544219323655
DOI: 10.1016/j.energy.2019.116670
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().