A dynamic model of a stationary proton exchange membrane (PEM) fuel cell system has been developed in MATLAB-SIMULINK ®. The system model accounts for the fuel processing system, PEM stack with coolant, humidifier with anode tail-gas oxidizer, and an enthalpy wheel for cathode air. Four reactors are modeled for the fuel processing system: (1) an autothermal reformation (ATR) reactor, (2) a high temperature shift (HTS) reactor, (3) a low temperature shift (LTS) reactor, and (4) a preferential oxidation reactor. Chemical kinetics for ATR that describe steam reformation of methane and partial oxidation of methane were simultaneously solved to accurately predict the reaction dynamics. The chemical equilibrium of CO with was assumed at HTS and LTS reactor exits to calculate CO conversion corresponding to the temperature of each reactor. A quasi-one-dimensional PEM unit cell was modeled with five control volumes for solving the dynamic species and mass conservation equations and seven control volumes to solve the dynamic energy balance. The quasi-one-dimensional cell model is able to capture the details of membrane electrode assembly behavior, such as water transport, which is critical to accurately determine polarization losses. The dynamic conservation equations, primary heat transfer equations and equations of state are solved in each bulk component, and each component is linked together to represent the complete system. The model predictions well matched the observed experimental dynamic voltage, stack coolant outlet temperature, and catalytic partial oxidation (CPO) temperature responses to perturbations. The dynamic response characteristics of the current system are representative of a typical stationary PEM fuel cell system. The dynamic model is used to develop and test a proportional-integral (PI) fuel flow controller that determines the fuel flow rate to maintain the uniform system efficiency. The dynamic model is shown to be a useful tool for investigating the effects of inlet conditions, load, and fuel flow perturbations and for the development of control strategies for enhancing system performance.