Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31168
Optimal Feedback Linearization Control of PEM Fuel Cell

Authors: E. Shahsavari, R. Ghasemi, A. Akramizadeh


This paper presents a new method to design nonlinear feedback linearization controller for PEMFCs (Polymer Electrolyte Membrane Fuel Cells). A nonlinear controller is designed based on nonlinear model to prolong the stack life of PEMFCs. Since it is known that large deviations between hydrogen and oxygen partial pressures can cause severe membrane damage in the fuel cell, feedback linearization is applied to the PEMFC system so that the deviation can be kept as small as possible during disturbances or load variations. To obtain an accurate feedback linearization controller, tuning the linear parameters are always important. So in proposed study NSGA (Non-Dominated Sorting Genetic Algorithm)-II method was used to tune the designed controller in aim to decrease the controller tracking error. The simulation result showed that the proposed method tuned the controller efficiently.

Keywords: PEMFC, Optimal control, Feedback Linearization controller, NSGA

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1891


[1] J. Purkrushpan, A. G. Stefanopoulou, and H. Peng, “Control of fuel cell breathing,” IEEE Control Systems Magazine, vol. 24, N. 2,2004, pp. 30– 46.
[2] M. J. Khan and M. T. Labal, “Dynamic modeling and simulation of a fuel cell generator,” Fuel Cells – from Fundamentals to Systems, vol. 5, no. 1, 2005, pp. 97–104.
[3] P. Famouri and R. S. Gemmen, “Electrochemical circuit model of a PEM fuel cell”, in 2003 IEEE Power Engineering Society General Meeting, vol. 3, pp. 13–17.
[4] C. Wang, M. H. Nehrir, and S. R. Shaw, “Dynamic model and model validation for PEM fuel cells using electrical circuits,” IEEE Trans. Energy Convers, vol. 20, no. 2, 2005, pp. 442–451.
[5] L. Y. Chiu, B. Diong, and R. S. Gemmen, “An improve small-signal mode of the dynamic behavior of PEM fuel cells,” IEEE Trans. Ind. Appl, vol. 40, no. 4, 2004, pp. 970–977.
[6] J. M. Correa, F. A. Farret, and L. N. Canha, “An analysis of the dynamic performance of proton exchange membrane fuel cells using an electrochemical model,” in Proc. 27th Annu. Conf. IEEE Ind. Electron. Soc. IECON 2001, Vol. 1, pp. 141–146.
[7] C. J. Hatiziadoniu, A. A. Lobo, F Pourboghrat, and M. Daneshdoot, “A simplified dynamic model of grid connected fuel-cell generators” IEEE Trans. Power Del, Vol. 17, No. 2, 2002, pp. 467–473.
[8] M. Y. El-Sharkh, A. Rahman, M. S. Alamm, A. A. Sakla, P. C. Byrne, and T. Thomas, “Analysis of active and reactive power control of a standalone PEM fuel cell power plant” IEEE Trans. Power Del, vol. 19, no. 4, 2004, pp. 2022–2028.
[9] A Sakhare, A Davari, and A Feliachi, “Fuzzy logic control of fuel cell for stand-alone and grid connection” , Journal. Power Sources, vol. 135, no. 1/2, 2004, pp. 165–176.
[10] P. E. M. Almeida and M. Godoy, “Neural optimal control of PEM fuel cells with parametric CMAC network” IEEE Trans. Ind. Appl, vol. 41, no. 1, 2005, pp. 237–245.
[11] Woon ki Na and Bei Gou, “Feedback Linearization Based Nonlinear Control for PEM Fuel Cells”, IEEE Transaction on Energy Conversion, Vol. 23, Issue 1, 2008, pp.179 – 190.
[12] A. Rezazadeh, A. Askarzadeh, M. Sedighizadeh, “Adaptive Inverse Control of Proton Exchange Membrane Fuel Cell Using RBF Neural Network”, International Journal of electrochemical science, Vol.6, 2011, pp.3105 – 3117.
[13] Alin C. Fărcaş, Petru Dobra “Adaptive control of membrane conductivity of PEM fuel cell”, Journal of Procedia Technology , 2014, Vo.12, pp:42 – 49.
[14] Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and T. Meyarivan “A Fast and Elitist Multi objective Genetic Algorithm:NSGA-II. ”, IEEE transactions on evolutionary computation, vol. 6, no. 2, april 2002.
[15] J.Larminie and A. “Dicks, Fuel Cell Systems Explained”. NewYork: Wiley, 2002.
[16] J. Purkrushpan and H. Peng, “Control of Fuel Cell Power Systems: Principle, Modeling, Analysis and Feedback Design”. Berlin, Germany: Springer-Verlag, 2004.
[17] F. Barbir, “PEM Fuel Cells: Theory and Practice". London, U.K. Elsevier, 2005.
[18] Reiner, J., Balas, G. J., and Garrard, W . L, “Robust Dynamic Inversion for Control of Highly Maneuverable Aircraft” Journal of Guidance, Control and Dynamics, V ol. 18, No. 1, 1995, pp. 18–24.
[19] Enns, D., Bugajski, D., Hendrick, D., & Stein, G. “Dynamic inversion: An evolving methodology for flight control design." International Journal of Control, vol, 59, 1994, pp.71–90.
[20] W. Yang, B. Bates, N. Fletcher, and R. Pow, “Control challenges and methodologies in fuel cell vehicle development,” presented at the SAE, Paper, 1998.
[21] L. Y. Chiu, B. Diong, and R. S. Gemmen, “An improve small-signal mode of the dynamic behavior of PEM fuel cells,” IEEE Trans. Ind. Appl, vol. 40, no. 4, 2004, pp. 970–977.
[22] A. Isidori,"Nonlinear Control Systems", in 3rd ed. London, U.K.: SpringerVerlag, 1995.
[23] M. A. Henson and D. E. Seborg, “Critique of exact linearization strategies for process control” J. Process Control, vol. 1, 1991, pp. 122– 139.
[24] J. J. E. Slotine and W. Li, “Applied Nonlinear Control." Englewood Cliffs, NJ: Prentice-Hall, 1991.