Research Papers

Adaptive Control of a Nonlinear Fuel Cell-Gas Turbine Balance of Plant Simulation Facility

[+] Author and Article Information
Alex Tsai

United States Coast Guard Academy,
New London, CT 06320
e-mail: alex.j.tsai@gmail.com

David Tucker

U.S. Department of Energy,
National Energy Technology Laboratory,
Morgantown, WV 26507
e-mail: david.tucker@netl.doe.gov

Tooran Emami

United States Coast Guard Academy,
New London, CT 06320
e-mail: tooran.emami@uscga.edu

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF FUEL CELL SCIENCE AND TECHNOLOGY. Manuscript received April 20, 2014; final manuscript received May 26, 2014; published online September 16, 2014. Editor: Nigel M. Sammes.

This material is declared a work of the US Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited.

J. Fuel Cell Sci. Technol 11(6), 061002 (Sep 16, 2014) (8 pages) Paper No: FC-14-1049; doi: 10.1115/1.4028157 History: Received April 20, 2014; Revised May 26, 2014

A 300 kW solid oxide fuel cell gas turbine (SOFC-GT) power plant simulator is evaluated with the use of a model reference adaptive control (MRAC) scheme, implemented for a set of nonlinear empirical transfer functions. The SOFC-GT simulator allows testing of various fuel cell models under a hardware-in-the-loop configuration that incorporates a 120 kW auxiliary power unit and balance-of-plant components in hardware, and a fuel cell model in software. The adaptation technique is beneficial to plants having a wide range of operation, and strong coupling interaction. The practical implementation of the adaptive methodology is presented through simulation in the Matlab/Simulink environment.

Copyright © 2014 by ASME
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Tucker, D., Manivannan, A., and Shelton, M. S., 2009, “The Role of Solid Oxide Fuel Cells in Advanced Hybrid Power Systems of the Future,” Interface, 18(3), pp. 45–48.
Winkler, W., Nehter, P., Tucker, D., Williams, M., and Gemmen, R., 2006, “General Fuel Cell Hybrid Synergies and Hybrid System Testing Status,” J. Power Sources, 159(1), pp. 656–666. [CrossRef]
Williams, M. C., Strakey, J., and Surdoval, W., 2006, “U.S. DOE Fossil Energy Fuel Cells Program,” J. Power Sources, 159(2), pp. 1241–1247. [CrossRef]
Tucker, D., Gemmen, R., and Lawson, L., 2005, “Characterization of Air Flow Management and Control in a Fuel Cell Turbine Hybrid Power System Using Hardware Simulation,” ASME Paper No. PWR2005-50127. [CrossRef]
Tsai, A., Banta, L., Tucker, D., and Gemmen, R., 2010, “Multivariable Robust Control of a Simulated Hybrid Solid Oxide Fuel Cell Gas Turbine Plant,” ASME J. Fuel Cell Sci. Technol., 7(4), p. 041008. [CrossRef]
Tsai, A., Tucker, D., and Groves, C., 2010, “Improved Controller Performance of Selected Hybrid SOFC-GT Plant Signals Based on Practical Control Schemes,” ASME J. Eng. Gas Turbines Power, 133(7), p. 071702. [CrossRef]
Tsai, A., Tucker, D., and Perez, E., 2013, “Adaptive Control of Balance of Plant Components in a Fuel Cell Gas Turbine Power Plant Simulator,” ASME Paper No. GT2013-95872. [CrossRef]
Haynes, C., Tucker, D., Hughes, D., Wepfer, W., Davies, K., and Ford, C., 2011, “A Real-Time Spatial SOFC Model for Hardware-Based Simulation of Hybrid Systems,” ASME Paper No. FuelCell2011-54591. [CrossRef]
Hughes, D., Tucker, D., Tsai, A., Haynes, C., and Rivera, Y., 2010, “Transient Behavior of a Fuel Cell/Gas Turbine Hybrid Using Hardware-Based Simulation With a 1-D Distributed Fuel Cell Model,” 10th International Colloquium on Environmentally Preferred Advanced Power Generation (ICEPAG 2010), Costa Mesa, CA, Feb. 9–11.
Tao, G., 1992, “Model Reference Adaptive Control of Multivariable Plants With Delays,” Int. J. Control, 55(2), pp. 393–414. [CrossRef]
Hoagg, J., 2011, “Model Reference Adaptive Control for Nonminimum Phase Systems Using a Surrogate Tracking Error,” 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), Orlando, FL, Dec. 12–15, pp. 360–365. [CrossRef]
Mirkin, B., Gutman, P., and Falcone, P., 2008, “Adaptive Output Feedback Control of MIMO Plants With Unknown Time-Varying State Delay,” American Control Conference, Seattle, WA, June 11–13, pp. 4761–4766. [CrossRef]
Ioannou, P., and Sun, J., 1996, Robust Adaptive Control, Prentice-Hall, Upper Saddle River, NJ.
Tao, G., and Ioannou, P., 1988, “Robust Model Reference Adaptive Control for Multivariable Plants,” Int. J. Adapt. Control Signal Process.,” 2(3), pp. 217–248. [CrossRef]
Restrepo, B., Banta, L., and Tucker, D., 2011, “Characterization of a Solid Oxide Fuel Cell Gas Turbine Hybrid System Based on a Factorial Design of Experiments Using Hardware Simulation,” ASME Paper No. FuelCell2011-54146. [CrossRef]
Harun, N. F., Tucker, D., and Adams, T., 2014, “Fuel Composition Transients in Fuel Cell Turbine Hybrid for Polygeneration Applications,” Fuel Cell Science, Engineering, and Technology Conference, Boston, MA, June 16–20, ASME Paper No. ES-FuelCell2014-6509.
Pezzini, P., Celestin, S., and Tucker, D., 2014, “Cold Air as a Function of Pressure Drop in Fuel Cell Turbine Hybrid Systems,” Fuel Cell Science, Engineering, and Technology Conference, Boston, MA, June 16–20, ASME Paper No. ES-FuelCell2014-6523.


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Fig. 1

NETL HyPer test facility

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Fig. 2

CAD rendering of HyPer hardware facility

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Fig. 3

Diagram of the HyPer facility real-time fuel cell model

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Fig. 4

Bode plot of ω/FV and m·/CA

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Fig. 5

Nonlinear interactions of FV and CA on ω and m·

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Fig. 6

Simulink plant model

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Fig. 7

Direct MRAC scheme [13]

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Fig. 8

First order MRAC adaptive laws—state feedback

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Fig. 9

First order MRAC with reference model

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Fig. 11

Simulink plant model and controller

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Fig. 12

PI versus MRAC control, nominal TF

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Fig. 13

PI versus MRAC control, deviation from nominal

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Fig. 14

PI versus MRAC close up

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Fig. 15

Plant gain change response—m· step [7]

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Fig. 16

Plant gain change response—ω step [7]



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