Apps.FuelCell History

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November 24, 2010, at 08:11 PM by 206.180.155.75 -
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(:title Solid Oxide Fuel Cell:) (:keywords nonlinear, model, predictive control, APMonitor, differential, algebraic, modeling language, solid oxide fuel cell:) (:description High fidelity nonlinear model of a Solid Oxide Fuel Cell with APMonitor:)

November 13, 2010, at 12:43 PM by 206.180.155.75 -
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A solid oxide fuel cell (SOFC) is an electrochemical conversion device that produces electricity directly from oxidizing a fuel. Fuel cells are characterized by their electrolyte material; the SOFC has a solid oxide or ceramic, electrolyte. Advantages of this class of fuel cells include high efficiency, long-term stability, fuel flexibility, low emissions, and relatively low cost. The largest disadvantage is the high operating temperature which results in longer start-up times and mechanical and chemical compatibility issues.

The objective of the SOFC model is to maintain performance and operational integrity subject to load-following, efficiency maximization, and disturbances using advanced process control.

to:

A solid oxide fuel cell (SOFC) is an electrochemical energy conversion device that produces electricity directly from oxidizing a fuel. Fuel cells are characterized by their charge transfer mechanism; the SOFC has a solid oxide electrode-electrolyte assembly. Advantages of this class of fuel cells include high efficiency, long-term stability, fuel flexibility, low emissions, and relatively lower catalyst cost. The largest challenge is preserving oxide integrity and fuel cell lifetime due to mechanical and chemical compatibility issues. Also, the high operating temperature can increase startup times but also provides benefits of internal reforming and waste heat which can be utilized downstream.

The objective of the SOFC model is to investigate advanced process control to maintain performance and operational integrity subject to load-following, efficiency maximization, and disturbances.

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The distributed parameter approach produces a large number of states: 220 states for 10 finite volumes in the axial direction. The model is expressed as a collection of differential and algebraic equations that are solved simultaneously (without algebraic loops). With APMonitor modeling language, the algebraic equations are expressed in an implicit form. The nonlinearities are introduced by reaction and electrochemical terms.

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The distributed parameter approach produces a large number of states: 220 states for 10 finite volumes in the axial direction. The model is expressed as a collection of differential and algebraic equations that are solved simultaneously, without algebraic loops. With APMonitor modeling language, the algebraic equations are expressed in an implicit form. The model contains many nonlinearities which are introduced by reaction and electrochemical terms and temperature dependent properties.

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B.J. Spivey and T.F. Edgar, Dynamic Modeling of Thermal Profiles in Solid Oxide Fuel Cells and Implications for Advanced Control, AIChE Fall 2010 Annual Meeting, Salt Lake City, Utah, November 2010.

Presentation (PDF)

to:

B.J. Spivey and T.F. Edgar, Dynamic Modeling of Reliability Indicators in Solid Oxide Fuel Cells and Implications for Advanced Control, AIChE Fall 2010 Annual Meeting, Salt Lake City, Utah, November 2010.

Presentation (PDF)

November 13, 2010, at 09:59 AM by 206.180.155.75 -
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The distributed parameter approach produces a large number of states: 220 states for 10 finite volumes in the axial direction. The model is expressed as a collection of differential and algebraic equations that are solved simultaneously (without algebraic loops). With APMonitor modeling language, the algebraic equations are expressed in an implicit form. The nonlinearities introduced by reaction and electrochemical terms.

to:

The distributed parameter approach produces a large number of states: 220 states for 10 finite volumes in the axial direction. The model is expressed as a collection of differential and algebraic equations that are solved simultaneously (without algebraic loops). With APMonitor modeling language, the algebraic equations are expressed in an implicit form. The nonlinearities are introduced by reaction and electrochemical terms.

November 12, 2010, at 02:28 PM by 158.35.225.231 -
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Solid Oxide Fuel Cell

A solid oxide fuel cell (SOFC) is an electrochemical conversion device that produces electricity directly from oxidizing a fuel. Fuel cells are characterized by their electrolyte material; the SOFC has a solid oxide or ceramic, electrolyte. Advantages of this class of fuel cells include high efficiency, long-term stability, fuel flexibility, low emissions, and relatively low cost. The largest disadvantage is the high operating temperature which results in longer start-up times and mechanical and chemical compatibility issues.

The objective of the SOFC model is to maintain performance and operational integrity subject to load-following, efficiency maximization, and disturbances using advanced process control.

The distributed parameter approach produces a large number of states: 220 states for 10 finite volumes in the axial direction. The model is expressed as a collection of differential and algebraic equations that are solved simultaneously (without algebraic loops). With APMonitor modeling language, the algebraic equations are expressed in an implicit form. The nonlinearities introduced by reaction and electrochemical terms.

One of the solution challenges is that multiple time scales of a significantly different magnitude. This creates a stiff problem unless steady-state or quasi-steady-state assumptions are considered. For example, electrical changes occur in milli-seconds, chemical changes occur in a few seconds, and thermal changes occur in minutes or hours.

Model results are consistent with other research publications and experimental validation.


Reference

B.J. Spivey and T.F. Edgar, Dynamic Modeling of Thermal Profiles in Solid Oxide Fuel Cells and Implications for Advanced Control, AIChE Fall 2010 Annual Meeting, Salt Lake City, Utah, November 2010.

Presentation (PDF)