Development of a novel computational tool for optimizing the operation of fuel cells systems: Application for phosphoric acid fuel cells

Zervas, PL; Tatsis, A; Sarimveis, H; Markatos, NCG

dc.contributor.author	Zervas, PL	en
dc.contributor.author	Tatsis, A	en
dc.contributor.author	Sarimveis, H	en
dc.contributor.author	Markatos, NCG	en
dc.date.accessioned	2014-03-01T01:28:09Z
dc.date.available	2014-03-01T01:28:09Z
dc.date.issued	2008	en
dc.identifier.issn	0378-7753	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18731
dc.subject	CFD	en
dc.subject	Fuel cells	en
dc.subject	Modeling	en
dc.subject	Neural networks	en
dc.subject	Optimization	en
dc.subject.classification	Electrochemistry	en
dc.subject.classification	Energy & Fuels	en
dc.subject.other	Acids	en
dc.subject.other	Applications	en
dc.subject.other	Computational fluid dynamics	en
dc.subject.other	Computer networks	en
dc.subject.other	Cytology	en
dc.subject.other	Database systems	en
dc.subject.other	Dynamics	en
dc.subject.other	Electric batteries	en
dc.subject.other	Electrochemistry	en
dc.subject.other	Feedforward neural networks	en
dc.subject.other	Fluid dynamics	en
dc.subject.other	Fluid mechanics	en
dc.subject.other	Fuel cells	en
dc.subject.other	Linear programming	en
dc.subject.other	Linearization	en
dc.subject.other	Multiobjective optimization	en
dc.subject.other	Neural networks	en
dc.subject.other	Nonlinear programming	en
dc.subject.other	Optimization	en
dc.subject.other	Oxidants	en
dc.subject.other	Phosphoric acid	en
dc.subject.other	Phosphoric acid fuel cells (PAFC)	en
dc.subject.other	Radial basis function networks	en
dc.subject.other	Regression analysis	en
dc.subject.other	Solid oxide fuel cells (SOFC)	en
dc.subject.other	Statistical tests	en
dc.subject.other	Three dimensional	en
dc.subject.other	CFD	en
dc.subject.other	Modeling	en
dc.subject.other	Volumetric rates	en
dc.subject.other	Fuels	en
dc.title	Development of a novel computational tool for optimizing the operation of fuel cells systems: Application for phosphoric acid fuel cells	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.jpowsour.2008.06.081	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.jpowsour.2008.06.081	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	Fuel cells offer a significant and promising clean technology for portable, automotive and stationary applications and, thus, optimization of their performance is of particular interest. In this study, a novel optimization tool is developed that realistically describes and optimizes the performance of fuel cell systems. First, a 3D steady-state detailed model is produced based on computational fluid dynamics (CFD) techniques. Simulated results obtained from the CFD model are used in a second step, to generate a database that contains the fuel and oxidant volumetric rates and utilizations and the corresponding cell voltages. In the third step mathematical relationships are developed between the input and output variables, using the database that has been generated in the previous step. In particular, the linear regression methodology and the radial basis function (RBF) neural network architecture are utilized for producing the input-output ""meta-models"". Several statistical tests are used to validate the proposed models. Finally, a multi-objective hierarchical Non-Linear Programming (NLP) problem is formulated that takes into account the constraints and limitations of the system. The multi-objective hierarchical approach is built upon two steps: first, the fuel volumetric rate is minimized, recognizing the fact that our first concern is to reduce consumption of the expensive fuel. In the second step, optimization is performed with respect to the oxidant volumetric rate. The proposed method is illustrated through its application for phosphoric acid fuel cell (PAFC) systems. © 2008 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Journal of Power Sources	en
dc.identifier.doi	10.1016/j.jpowsour.2008.06.081	en
dc.identifier.isi	ISI:000259906600048	en
dc.identifier.volume	185	en
dc.identifier.issue	1	en
dc.identifier.spage	345	en
dc.identifier.epage	355	en