Modeling and control of a PEM fuel cell system: A practical study based on experimental defined component behavior

Abstract In this contribution, the dynamical behavior of a polymer electrolyte membrane (PEM) fuel cell system is modeled; related control approaches are developed. The system model used for experimental and modeling purposes describes a 1.2 kW PEM fuel cell stack and an air blower. Due to the dynamical fuel cell–blower interaction the fuel cell stack and the blower model are validated to real systems respectively. Additionally, a feedback based on PI-control is used for hydrogen pressure control with an anode inlet valve. This controller is able to eliminate a stationary error between the anode and cathode pressures. For principal investigations three control approaches, a classical static feed-forward control approach, a state-space feedback control, and a novel gain-scheduling approach are developed, applied, and compared. As result, it can be shown that the feed-forward approach lacks in performance recovering the excess oxygen ratio to the desired level. The state-space feedback control shows stationary error. The introduced gain-scheduling control approach leads to a fast excess oxygen ratio recovery without stationary deviations.

[1]  E H Law,et al.  Model-based control strategies in the dynamic interaction of air supply and fuel cell , 2004 .

[2]  Mohammad S. Alam,et al.  Dynamic modeling, design and simulation of a PEM fuel cell/ultra-capacitor hybrid system for vehicular applications , 2007 .

[3]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[4]  James Larminie,et al.  Fuel Cell Systems Explained , 2000 .

[5]  Anna G. Stefanopoulou,et al.  Control of Fuel Cell Power Systems: Principles, Modeling, Analysis and Feedback Design , 2004 .

[6]  S. Pierfederici,et al.  Differential flatness based-control of fuel cell/photovoltaic/wind turbine/supercapacitor hybrid power plant , 2013, 2013 International Conference on Clean Electrical Power (ICCEP).

[7]  Bei Gou,et al.  Nonlinear control of PEM fuel cells by exact linearization , 2005, Fourtieth IAS Annual Meeting. Conference Record of the 2005 Industry Applications Conference, 2005..

[8]  William Leithead,et al.  Survey of gain-scheduling analysis and design , 2000 .

[9]  T. Springer,et al.  Polymer Electrolyte Fuel Cell Model , 1991 .

[10]  Huei Peng,et al.  Model predictive control for starvation prevention in a hybrid fuel cell system , 2004, Proceedings of the 2004 American Control Conference.

[11]  Ilya Kolmanovsky,et al.  Turbocharger Modeling for Automotive Control Applications , 1999 .

[12]  John E. Warnock,et al.  Dynamic modeling , 1977, SIGGRAPH.

[13]  Dirk Söffker,et al.  RETRACTED: Modeling and Control of an Elastic Ship-mounted Crane Using Variable Gain Model-based Controller , 2007 .

[14]  David J. Friedman,et al.  Requirements for a Flexible and Realistic Air Supply Model for Incorporation into a Fuel Cell Vehicle (FCV) System Simulation , 1999 .

[15]  Guidong Liu,et al.  Adaptive control of the airflow of a PEM fuel cell system , 2008 .

[16]  M. J. Moran,et al.  Fundamentals of Engineering Thermodynamics , 2014 .

[17]  P. Müller,et al.  State estimation of dynamical systems with nonlinearities by using proportional-integral observer , 1995 .

[18]  Amit Kapur,et al.  Roots blowers: Understanding twin lobe operation , 2002 .

[19]  Michael A. Danzer,et al.  Model-based control of cathode pressure and oxygen excess ratio of a PEM fuel cell system , 2008 .