Fuel cells are emerging as alternate green power producers for both large power production and for use in automobiles. Hydrogen is seen as the best option as a fuel; however, hydrogen fuel cells require recirculation of unspent hydrogen. A supersonic ejector is an apt device for recirculation in the operating regimes of a hydrogen fuel cell. Optimal ejectors have to be designed to achieve best performances. The use of the vector evaluated particle swarm optimization technique to optimize supersonic ejectors with a focus on its application for hydrogen recirculation in fuel cells is presented here. Two parameters, compression ratio and efficiency, have been identified as the objective functions to be optimized. Their relation to operating and design parameters of ejector is obtained by control volume based analysis using a constant area mixing approximation. The independent parameters considered are the area ratio and the exit Mach number of the nozzle. The optimization is carried out at a particular entrainment ratio and results in a set of nondominated solutions, the Pareto front. A set of such curves can be used for choosing the optimal design parameters of the ejector.
Skip Nav Destination
e-mail: srisharao@aero.iisc.ernet.in
e-mail: jaggie@aero.iisc.ernet.in
Article navigation
August 2010
This article was originally published in
Journal of Fuel Cell Science and Technology
Research Papers
Vector Evaluated Particle Swarm Optimization (VEPSO) of Supersonic Ejector for Hydrogen Fuel Cells
Srisha Rao M V,
Srisha Rao M V
Department of Aerospace Engineering,
e-mail: srisharao@aero.iisc.ernet.in
Indian Institute of Science
, Bangalore, Karnataka PIN 560012, India
Search for other works by this author on:
G. Jagadeesh
G. Jagadeesh
Department of Aerospace Engineering,
e-mail: jaggie@aero.iisc.ernet.in
Indian Institute of Science
, Bangalore, Karnataka PIN 560012, India
Search for other works by this author on:
Srisha Rao M V
Department of Aerospace Engineering,
Indian Institute of Science
, Bangalore, Karnataka PIN 560012, Indiae-mail: srisharao@aero.iisc.ernet.in
G. Jagadeesh
Department of Aerospace Engineering,
Indian Institute of Science
, Bangalore, Karnataka PIN 560012, Indiae-mail: jaggie@aero.iisc.ernet.in
J. Fuel Cell Sci. Technol. Aug 2010, 7(4): 041014 (7 pages)
Published Online: April 8, 2010
Article history
Received:
January 17, 2009
Revised:
August 4, 2009
Online:
April 8, 2010
Published:
April 8, 2010
Citation
M V, S. R., and Jagadeesh, G. (April 8, 2010). "Vector Evaluated Particle Swarm Optimization (VEPSO) of Supersonic Ejector for Hydrogen Fuel Cells." ASME. J. Fuel Cell Sci. Technol. August 2010; 7(4): 041014. https://doi.org/10.1115/1.4000676
Download citation file:
Get Email Alerts
Cited By
Optimization of Thermal Non-Uniformity Challenges in Liquid-Cooled Lithium-Ion Battery Packs Using NSGA-II
J. Electrochem. En. Conv. Stor (November 2025)
In Situ Synthesis of Nano PtRuW/WC Hydrogen Evolution Reaction Catalyst for Acid Hydrogen Evolution by a Microwave Method
J. Electrochem. En. Conv. Stor (November 2025)
Intelligently Constructing Polyaniline/Nickel Hydroxide Core–Shell Nanoflowers as Anode for Flexible Electrode-Enhanced Lithium-/Sodium-Ion Batteries
J. Electrochem. En. Conv. Stor (November 2025)
State of Health Estimation Method for Lithium-Ion Batteries Based on Multifeature Fusion and BO-BiGRU Model
J. Electrochem. En. Conv. Stor (November 2025)
Related Articles
Optimizing a New Configuration of a Proton Exchange Membrane Fuel Cell Cycle With Burner and Reformer Through a Particle Swarm Optimization Algorithm for Residential Applications
J. Electrochem. En. Conv. Stor (November,2019)
Feasibility Analysis of a Fuel Cell-Based Tri-Generation Energy System Via the Adoption of a Multi-Objective Optimization Tool
J. Energy Resour. Technol (September,2023)
Related Proceedings Papers
Related Chapters
Risk Mitigation for Renewable and Deispersed Generation by the Harmonized Grouping (PSAM-0310)
Proceedings of the Eighth International Conference on Probabilistic Safety Assessment & Management (PSAM)
Research on Autobody Panels Developmental Technology Based on Reverse Engineering
International Conference on Measurement and Control Engineering 2nd (ICMCE 2011)
A Novel Particle Swarm Optimizer with Kriging Models
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17