Channel geometry optimization of a polymer electrolyte membrane fuel cell using genetic algorithm. (15th May 2015)
- Record Type:
- Journal Article
- Title:
- Channel geometry optimization of a polymer electrolyte membrane fuel cell using genetic algorithm. (15th May 2015)
- Main Title:
- Channel geometry optimization of a polymer electrolyte membrane fuel cell using genetic algorithm
- Authors:
- Yang, Woo-Joo
Wang, Hong-Yang
Lee, Dae-Hyung
Kim, Young-Bae - Abstract:
- Graphical abstract: Highlights: Geometry optimization for a PEMFC is performed using a genetic algorithm. Automatic program is developed to calculate the optimum channel-to-rib ratio of a PEMFC. Channel-to-rib ratio of 2.8:0.5 shows the best performance for normal arrangement. Channel-to-rib ratio of 4.2:0.3 shows the best performance for reverse arrangement. Abstract: The study presents the use of genetic algorithm (GA) to optimize the bipolar plate channel geometry of a polymer electrolyte membrane fuel cell (PEMFC). Contrary to previous optimization techniques, laborious fuel cell design steps, including boundary setting, mesh generation, and numerical computation at every design parameter variation step, are avoided by developing an automated program via Matlab and Comsol Multiphysics software. GA with Matlab automatically checks the optimality of the present fuel cell design with a performance index obtained from Comsol Multiphysics. If a global optimal is not reached, the new geometry set of a fuel cell is generated according to GA rules toward better fuel cell performance. The new set is then fed back to Comsol Multiphysics to have the new performance index calculated through updated boundary conditions, element and mesh generations, and numerical analysis. This automated optimization technique not only saves numerous calculations, but also obtains the global optimal result of a given fuel cell geometry. Therefore, it provides a fast and efficient optimization processGraphical abstract: Highlights: Geometry optimization for a PEMFC is performed using a genetic algorithm. Automatic program is developed to calculate the optimum channel-to-rib ratio of a PEMFC. Channel-to-rib ratio of 2.8:0.5 shows the best performance for normal arrangement. Channel-to-rib ratio of 4.2:0.3 shows the best performance for reverse arrangement. Abstract: The study presents the use of genetic algorithm (GA) to optimize the bipolar plate channel geometry of a polymer electrolyte membrane fuel cell (PEMFC). Contrary to previous optimization techniques, laborious fuel cell design steps, including boundary setting, mesh generation, and numerical computation at every design parameter variation step, are avoided by developing an automated program via Matlab and Comsol Multiphysics software. GA with Matlab automatically checks the optimality of the present fuel cell design with a performance index obtained from Comsol Multiphysics. If a global optimal is not reached, the new geometry set of a fuel cell is generated according to GA rules toward better fuel cell performance. The new set is then fed back to Comsol Multiphysics to have the new performance index calculated through updated boundary conditions, element and mesh generations, and numerical analysis. This automated optimization technique not only saves numerous calculations, but also obtains the global optimal result of a given fuel cell geometry. Therefore, it provides a fast and efficient optimization process and renders optimal results. In this study, two channel and rib geometry arrangements are studied: one with a symmetric anode and cathode channel arrangement, wherein channels and ribs face each other; and another with an asymmetric arrangement, wherein a channel faces a rib and vice versa. First, the two-dimensional (2D) CFD model is used to obtain the optimal result in order to speed up the optimization calculation, slightly sacrificing the model accuracy. Afterwards, the three-dimensional CFD model is utilized and experimental verification is made with the same geometries to support the validation of the 2D optimization result. … (more)
- Is Part Of:
- Applied energy. Volume 146(2015:May 15)
- Journal:
- Applied energy
- Issue:
- Volume 146(2015:May 15)
- Issue Display:
- Volume 146 (2015)
- Year:
- 2015
- Volume:
- 146
- Issue Sort Value:
- 2015-0146-0000-0000
- Page Start:
- 1
- Page End:
- 10
- Publication Date:
- 2015-05-15
- Subjects:
- Global optimization -- Genetic algorithm (GA) -- Proton electrolyte membrane fuel cell (PEMFC) -- Computational fluid dynamics (CFD)
Power (Mechanics) -- Periodicals
Energy conservation -- Periodicals
Energy conversion -- Periodicals
621.042 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03062619 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.apenergy.2015.01.130 ↗
- Languages:
- English
- ISSNs:
- 0306-2619
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1572.300000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9051.xml