Performance Enhancement of PEM Fuel Cells by Use of Anode Gas Ultrahumidification via Ultrasonic Nebulization

ASME 2006 Fourth International Conference on Fuel Cell Science, Engineering and Technology, Parts A and B ◽

10.1115/fuelcell2006-97128 ◽

2006 ◽

Author(s):

Erik Snyder ◽

Thomas R. Lalk ◽

A. J. Appleby

Keyword(s):

Fuel Cell ◽

Performance Enhancement ◽

Pem Fuel Cell ◽

Energy Conversion Efficiency ◽

Pem Fuel Cells ◽

Cell System ◽

Fuel Cell System ◽

Ultrasonic Nebulization ◽

Balance Of Plant ◽

Mass Volume

A novel anode feed gas humidification method was investigated as part of an effort to reduce the mass, volume, and cost of the balance of plant for a commercial PEM fuel cell system. Ultrasonic fountain nebulization was utilized to ultrahumidify the anode feed gas for a PEM fuel cell. Ultrasonic nebulization ultrahumidification was found to increase the average voltage of the fuel cell by several percent, and reduce the amplitude of cyclic overvoltage. Most importantly, this humidification technique greatly increased the thermal fault tolerance of the PEM fuel cell; that is, this humidification technique allowed the PEM fuel cell to operate effectively at high temperatures without a need to increase the vapor pressure of the humidification water. In addition, this humidification technique shows potential to be used to increase the overall energy conversion efficiency of a PEM fuel cell system.

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Balance of Plant Concerns with Transportation-Based PEM Fuel Cell System Operation in Freezing Environments

5th International Energy Conversion Engineering Conference and Exhibit (IECEC) ◽

10.2514/6.2007-4843 ◽

2007 ◽

Author(s):

James Fletcher ◽

Sydni Credle ◽

Cheng-Chan Kuo ◽

William Lear

Keyword(s):

Fuel Cell ◽

Pem Fuel Cell ◽

Cell System ◽

Fuel Cell System ◽

System Operation ◽

Balance Of Plant

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A Parametrical Study of a Seven Serpentine Channel PEM Fuel Cell

Volume 2: Controls, Diagnostics and Instrumentation; Cycle Innovations; Electric Power ◽

10.1115/gt2008-51352 ◽

2008 ◽

Cited By ~ 1

Author(s):

Elena Carcadea ◽

D. B. Ingham ◽

L. Ma ◽

M. Pourkashanian ◽

H. Ene ◽

...

Keyword(s):

Fluid Dynamics ◽

Fuel Cell ◽

Pem Fuel Cell ◽

System Optimization ◽

Pem Fuel Cells ◽

Cell System ◽

Cell Performance ◽

Critical Parameters ◽

Fuel Cell System ◽

Serpentine Channel

Proton exchange membrane (PEM) fuel cells have been identified as a viable emerging technology for future power generation systems in terms of both stationary and mobile applications since it offers a significant economical and environmental potential in future power production. This paper presents the development of a PEM fuel cell system using a full three-dimensional computational fluid dynamics model for the system optimization. The fuel cell investigated is a seven serpentine channel cell of 100cm2 active area. The model includes a complete set of mathematical equations for the fluid flow, multi-component species transport, electrochemistry, and the transport of protons and electrical currents throughout the PEM fuel cell. The results obtained from the parametric analyses of the cell performance at different current loads have been presented. The model results provide us detailed information on the fluid dynamics and electrochemical processes that occur in the fuel cell. This generates a clear picture on the fuel/oxidant distribution, consumption, and the current density distribution in the fuel cell. This assists us in identifying the critical parameters that influence the cell performance and sheds light onto the physical mechanisms leading to the improvement of the fuel cell system performance.

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A Survey of PEM Fuel Cell System Control Models and Control Developments

ASME 2006 Fourth International Conference on Fuel Cell Science, Engineering and Technology, Parts A and B ◽

10.1115/fuelcell2006-97030 ◽

2006 ◽

Cited By ~ 5

Author(s):

Richard T. Meyer ◽

Shripad Revankar

Keyword(s):

Fuel Cell ◽

Pem Fuel Cell ◽

Cell System ◽

Current Control ◽

System Control ◽

Air Cooling ◽

Fuel Cell System ◽

Fuel Cell Stack ◽

Balance Of Plant ◽

Control Work

Proton Exchange Membrane (PEM) fuel cell system performance can be significantly improved with suitable control strategies. Control appropriate models of the fuel cell stack and balance of plant are presented along with current control research. Fuel cell stack models are zero dimensional and range from simple empirical stack polarization curves to complex dynamic models of mass flow rates, pressures, temperatures, and voltages. Balance of plant models are also zero dimensional and can be used individually to build a complete system around a stack. Models of this type are presented for the air compressor, air blower, manifolds, reactant humidification, fuel recirculation, air cooling, and stack cooling. Current control work is surveyed with regard to feedforward, feedback, observers, optimization, model prediction, rule based, neural networks, and fuzzy methods. The most promising fuel cell stack model is evaluated. Additionally, improvements to the balance of plant models are recommended. Finally, future control work is explored with a desire for system control that leads to greater output power.

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Electrical and Thermal Time Constants Fuel Cell System Identification: A Linear Versus Neural Network Approach

ASME 2008 6th International Conference on Fuel Cell Science, Engineering and Technology ◽

10.1115/fuelcell2008-65082 ◽

2008 ◽

Cited By ~ 1

Author(s):

M. T. Outeiro ◽

Alberto J. L. Cardoso ◽

R. Chibante ◽

A. S. Carvalho

Keyword(s):

Neural Network ◽

Fuel Cells ◽

Fuel Cell ◽

Pem Fuel Cell ◽

Pem Fuel Cells ◽

Cell System ◽

Thermal Time ◽

Fuel Cell System ◽

Time Constants ◽

Made In

The energy generated by PEM fuel cells can be used in many different applications with emphasis to commercial power generation and automotive application. It requires the integration of various subsystems such as chemical, mechanical, fluid, thermal and electrical ones. Their electrical and thermal time constants are important variables to analyze and consider in the development of control strategies of electronic converters. For this purpose, a mathematical model of the PEM fuel cell system was developed in Matlab/Simulink based on a set of equations describing cell operation. The model considers static and dynamic operating conditions of the PEM. Using experimental measurements at different load conditions made in a Nexa™ PEM fuel cell system, analysis based on linear ARX (Autoregressive with Exogenous Input) and neural network methods were made in Matlab in order to identify the electrical and thermal time constant values. Both linear ARX and neural network approaches can successfully predict the values of the time constants variables. However, the identification by the linear ARX is appropriated around the most significant operation points of the PEM system while neural network allows at obtaining a nonlinear global model. The paper intends to be a contribution for the identification of the electrical and thermal time constants of PEM fuel cells through these two methodologies. The linear approach is simple but presents some limitations while the non-linear one is widespread but more complex to be implemented.

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