Control approaches of pem fuel cells: a review

  • 1 Jožef Stefan International Postgraduate School, Ljubljana, Slovenia


Over the last two decades, polymer electrolyte membrane fuel cell technology has been increasing its share in power generation systems. In this work, the basic polymer electrolyte membrane fuel cell (PEMFC) system operation is presented first. Some most controloriented modeling approaches are reviewed as the model is essential for further control. Optimal control of such a system can improve efficiency and hence reduce the cost of ownership. The objective of this work is to present the concept of control and depict some of the possible applications of PEMFC systems



  1. A. P. Vega-Leal, F. R. Palomo, F. Barragán, C. García, and J. J. Brey, Design of control systems for portable PEM fuel cells, J. Power Sources, vol. 169, no. 1, pp. 194–197, 2007, doi: 10.1016/j.jpowsour.2007.01.055.
  2. J. Wisniak, Historical Notes: Electrochemistry and Fuel Cells: The Contribution of William Robert Grove, Indian J. Hist. Sci., vol. 50, no. 4, 2015, doi: 10.16943/ijhs/2015/v50i4/48318.
  3. J. M. Nail, G. Anderson, C. Gerald, and H. C. J., The Role of the U.S. National Innovation System in the Development of the PEM Stationary Fuel Cell, NIST Interagency/Internal Report (NISTIR), 2005.
  4. J. Marquis and M. O. Coppens, Achieving ultra-high platinum utilization via optimization of PEM fuel cell cathode catalyst layer microstructure, Chem. Eng. Sci., vol. 102, pp. 151– 162, 2013, doi: 10.1016/j.ces.2013.08.003.
  5. M. L. S. Carnevali, Modelling and Control of PEM Fuel Cells (Doctoral dissertation, Polytechnic University of Catalonia, Barcelona, Spain), p. 183, 2017.
  6. F. Barbir, PEM fuel cells : theory and practice. 2nd edition. Elsevier. 2005.
  7. A. Baroutaji, J. G. Carton, M. Sajjia, and A. G. Olabi, Materials in PEM Fuel Cells, no. November 2017, Elsevier Ltd., 2016.
  8. W. R. W. Daud, R. E. Rosli, E. H. Majlan, S. A. A. Hamid, R. Mohamed, and T. Husaini, PEM fuel cell system control: A review, Renew. Energy, vol. 113, pp. 620–638, 2017, doi: 10.1016/j.renene.2017.06.027.
  9. P. Lin, P. Zhou, and C. W. Wu, A high efficient assembly technique for large PEMFC stacks: Part I. Theory, J. Power Sources, vol. 194, no. 1, pp. 381–390, 2009, doi: 10.1016/j.jpowsour.2009.04.068.
  10. A. M. Niroumand, Integrated Systems, Design and Technology 2010, Integr. Syst. Des. Technol., no. December 2010, doi: 10.1007/978-3-642-17384-4.
  11. Z. dan Zhong, H. bo Huo, X. jian Zhu, G. yi Cao, and Y. Ren, Adaptive maximum power point tracking control of fuel cell power plants, J. Power Sources, vol. 176, no. 1, pp. 259–269, 2008, doi: 10.1016/j.jpowsour.2007.10.080.
  12. S. Ahmadi, S. Abdi, and M. Kakavand, Maximum power point tracking of a proton exchange membrane fuel cell system using PSO-PID controller, Int. J. Hydrogen Energy, vol. 42, no. 32, pp. 20430–20443, 2017, doi: 10.1016/j.ijhydene.2017.06.208.
  13. J. A. Salva, A. Iranzo, F. Rosa, E. Tapia, E. Lopez, and F. Isorna, Optimization of a PEM fuel cell operating conditions: Obtaining the maximum performance polarization curve, Int. J. Hydrogen Energy, vol. 41, no. 43, pp. 19713–19723, 2016, doi: 10.1016/j.ijhydene.2016.03.136.
  14. K. Ondrejička, V. Ferencey, and M. Stromko, Modeling of the air-cooled PEM fuel cell, IFAC-PapersOnLine, vol. 52, no. 27, pp. 98–105, 2019, doi: 10.1016/j.ifacol.2019.12.740.
  15. D. Hissel, C. Turpin, S. Astier, L. Boulon, and a Bouscayrol, A review of existing modelling methodologies for PEM fuel cell systems, Journal of fuel cell science and technology, vol. m, no. October, 2008.
  16. Z. Ural and M. T. Gencoglu, Mathematical Models of PEM Fuel Cells, 5th Int. Ege Energy Symp. Exhib., no. June, pp. 27–30, 2010.
  17. M. Hatti, M. Tioursi, and W. Nouibat, Static modelling by neural networks of a PEM fuel cell, IECON Proc. Industrial Electron. Conf., pp. 2121–2126, Paris, France, 2006, doi: 10.1109/IECON.2006.347589.
  18. A. J. del Real, A. Arce, and C. Bordons, Development and experimental validation of a PEM fuel cell dynamic model, J.Power Sources, vol. 173, no. 1, pp. 310–324, 2007, doi: 10.1016/j.jpowsour.2007.04.066.
  19. Z. Abdin, C. J. Webb, and E. M. A. Gray, PEM fuel cell model and simulation in Matlab–Simulink based on physical parameters, Energy, vol. 116, pp. 1131–1144, 2016, doi: 10.1016/
  20. A. R.Seyezhai and A. B.L.Mathur, Mathematical Modeling of Proton Exchange Membrane Fuel Cell, Int. J. Comput. Appl., vol. 20, no. 5, pp. 1–6, 2011, doi: 10.5120/2433-3272.
  21. A. Saengrung, A. Abtahi, and A. Zilouchian, Neural network model for a commercial PEM fuel cell system, J. Power Sources, vol. 172, no. 2, pp. 749–759, 2007, doi: 10.1016/j.jpowsour.2007.05.039.
  22. A. Sari, A. Balikci, S. Taskin, and S. Aydin, A proposed artificial neural network model for PEM fuel cells, ELECO - 8th Int. Conf. Electr. Electron. Eng., pp. 205–209, Bursa, Turkey, 2013, doi: 10.1109/eleco.2013.6713832.
  23. I. S. Han and C. B. Chung, Performance prediction and analysis of a PEM fuel cell operating on pure oxygen using data-driven models: A comparison of artificial neural network and support vector machine, Int. J. Hydrogen Energy, vol. 41, no. 24, pp. 10202–10211, 2016, doi: 10.1016/j.ijhydene.2016.04.247.
  24. J. Golbert and D. R. Lewin, Model-based control of fuel cells: (1) Regulatory control, J. Power Sources, vol. 135, no. 1–2, pp. 135–151, 2004, doi: 10.1016/j.jpowsour.2004.04.008.
  25. M. Li, J. Lu, Y. Hu, and J. Gao, Oxygen Excess Ratio Controller Design of PEM Fuel Cell, IFAC-PapersOnLine, vol. 51, no. 31, pp. 493–498, 2018, doi: 10.1016/j.ifacol.2018.10.108.
  26. M. Raceanu, A. Marinoiu, M. Culcer, M. Varlam, and N. Bizon, Preventing reactant starvation of a 5 kW PEM fuel cell stack during sudden load change, 6th Int. Conf. Electron. Comput. Artif. Intell. ECAI, pp. 55–60, Prague, Czech Republic, 2014, doi: 10.1109/ECAI.2014.7090147.
  27. V. Khubchandani, K. Pandey, V. K. Tayal, and S. K. Sinha, PEM Fuel Cell integration with using Fuzzy PID technique, 1st IEEE Int. Conf. Power Electron. Intell. Control Energy Syst. ICPEICES, pp. 3–6, Delhi, India, 2016, doi: 10.1109/ICPEICES.2016.7853450.
  28. Z. Fan, X. Yu, M. Yan, and C. Hong, Oxygen Excess Ratio Control of PEM Fuel Cell Based on Self-adaptive Fuzzy PID, IFAC-PapersOnLine, vol. 51, no. 31, pp. 15–20, 2018, doi: 10.1016/j.ifacol.2018.10.004.
  29. Z. Baroud, M. Benmiloud, and A. Benalia, Fuzzy self-tuning PID controller for air supply on a PEM fuel cell system, 4th Int. Conf. Electr. Eng. ICEE, pp. 3–6, Aswan, Egypt, 2015, doi: 10.1109/INTEE.2015.7416690.
  30. I. M. Safwat, X. Wu, X. Zhao, and W. Li, Adaptive fuzzy logic control of boost converter fed by stand-alone PEM fuel cell stack, IEEE Transp. Electrif. Conf. Expo, Asia-Pacific, Harbin, China, 2017, doi: 10.1109/ITEC-AP.2017.8080956.
  31. W. Garcia-Gabin, F. Dorado, and C. Bordons, Real-time implementation of a sliding mode controller for air supply on a PEM fuel cell, J. Process Control, vol. 20, no. 3, pp. 325–336, 2010, doi: 10.1016/j.jprocont.2009.11.006.
  32. H. Deng, Q. Li, W. Chen, and Y. Cui, Robust control of PEM fuel cell air-feed system using an improved sliding mode strategy, Chinese Autom. Congr, pp. 1466–1471, Jinan, China, 2017, doi: 10.1109/CAC.2017.8242998.
  33. I. Matraji, S. Laghrouche, S. Jemei, and M. Wack, Robust control of the PEM fuel cell air-feed system via sub-optimal second order sliding mode, Appl. Energy, vol. 104, pp. 945–957, 2013, doi: 10.1016/j.apenergy.2012.12.012.
  34. A. G. S. Jay T. Pukrushpan and and H. Peng, Control of Fuel Cell Power Systems. Springer. 2011.
  35. J. Golbert and D. R. Lewin, Model-based control of fuel cells (2): Optimal efficiency, J. Power Sources, vol. 173, no. 1, pp. 298–309, 2007, doi: 10.1016/j.jpowsour.2007.04.062.
  36. A. Arce, D. R. Ramirez, A. J. del Real and C. Bordons, "Constrained explicit predictive control strategies for PEM fuel cell systems," 46th IEEE Conference on Decision and Control, New Orleans, LA, 2007, pp. 6088-6093.
  37. C. Ziogou, S. Voutetakis, M. C. Georgiadis, and S. Papadopoulou, Model predictive control (MPC) strategies for PEM fuel cell systems – A comparative experimental demonstration, Chem. Eng. Res. Des., vol. 131, pp. 656–670, 2018, doi: 10.1016/j.cherd.2018.01.024.
  38. S. M. Rakhtala Rostami, R. Ghaderi, A. Ranjbar, T. Fadaeian, and S. A. N. Niaki, PEM fuel cell voltage-tracking using artificial neural network, IEEE Electr. Power Energy Conf. EPEC, Montreal, QC, Canada, 2009, doi: 10.1109/EPEC.2009.5420935.
  39. A. Arce, D. R. Ramírez, A. J. Del Real, and C. Bordons, Constrained explicit predictive control strategies for PEM fuel cell systems, Proc. IEEE Conf. Decis. Control, pp. 6088–6093, New Orleans, LA, USA, 2007 doi: 10.1109/CDC.2007.4434556.
  40. E. F. C. and C. Bordons, Model Predictive Control. 2th edition. Springer. 2007.
  41. M. Rubagotti, P. Patrinos, and A. Bemporad, Stabilizing linear model predictive control under inexact numerical optimization, IEEE Trans. Automat. Contr., vol. 59, no. 6, pp. 1660–1666, 2014, doi: 10.1109/TAC.2013.2293451.
  42. B. B. Alagoz, G. Kavuran, A. Ates, and C. Yeroglu, Reference-shaping adaptive control by using gradient descent optimizers, PLoS One, vol. 12, no. 11, pp. 1–20, 2017, doi: 10.1371/journal.pone.0188527.
  43. A. Bemporad, "A Multiparametric Quadratic Programming Algorithm With Polyhedral Computations Based on Nonnegative Least Squares," in IEEE Transactions on Automatic Control, vol. 60, no. 11, pp. 2892-2903, Nov. 2015.
  44. J. K. Gruber, M. Doll, and C. Bordons, Design and experimental validation of a constrained MPC for the air feed of a fuel cell, Control Eng. Pract., vol. 17, no. 8, pp. 874–885, 2009, doi: 10.1016/j.conengprac.2009.02.006.
  45. C. Ziogou, S. Papadopoulou, M. C. Georgiadis, and S. Voutetakis, On-line nonlinear model predictive control of a PEM fuel cell system, J. Process Control, vol. 23, no. 4, pp. 483–492, 2013, doi: 10.1016/j.jprocont.2013.01.011.

Article full text

Download PDF