Dynamic Simulation of a Stationary Proton Exchange Membrane Fuel Cell System

Kyoungdoug Min,Fabian Mueller,John Auckland,Sanggyu Kang,Jacob Brouwer

doi:10.1115/1.3008029

Abstract

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 H2O 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.

Highlights

proton exchange membrane (PEM) fuel cellPEMFCtechnology has received attention as a promising future stationary power source because of its high power density, low temperature operation, quick start-up, system robustness, the ability to respond to rapid changes in power demand, and low emissions1–4͔
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
The chemical equilibrium of CO with H2O was assumed at HTS and LTS reactor exits to calculate CO conversion corresponding to the temperature of each reactor

Summary

Introduction

PEM fuel cellPEMFCtechnology has received attention as a promising future stationary power source because of its high power density, low temperature operation, quick start-up, system robustness, the ability to respond to rapid changes in power demand, and low emissions1–4͔. Fuel cell and stack level transient modeling include the bulk dynamic model of a PEM fuel cell developed by Shan and Choe, and Yuyao and Choe investigated the mechanisms of PEMFC dehydration14,15͔ Another bulk dynamic model used for developing a control system was presented by Yerramalla et al using MATLAB-SIMULINK® ͓16͔. While a one-dimensional dynamic model is useful for investigating the dynamic response of PEMFC, it cannot capture the distribution of current, species, temperature, and membrane water content in the cell. The three-dimensional mixed-domain PEM fuel cell model of Meng, which integrates the various transport phenomena, has been applied to investigate the effects of the fully coupled transport phenomena on the cell performance, current distribution, and net water transfer across the membrane23͔. The threedimensional computational fluid dynamicsCFDmodel of Maher et al accounts for detailed species mass transport, heat transfer in NOVEMBER 2009, Vol 6 / 041015-1

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