Performance Modeling of the Ballard Mark IV Solid Polymer Electrolyte Fuel Cell: I . Mechanistic Model Development

Abstract

A parametric model predicting the performance of a solid polymer electrolyte, proton exchange membrane (PEM) fuel cell has been developed using a combination of mechanistic and empirical modeling techniques. This paper details the mechanistic model development. Mass transport properties are considered in the mechanistic development via StefanMaxwell equations. Thermodynamic equilibrium potentials are defined using the Nernst equation. Activation overvoltages are defined via a Tafel equation, and internal resistances are defined via the Nernst-Planck equation, leading to a definition of ohmic overvoltage via an Ohm's law equation. The mechanistic model cannot adequately model fuel cell performance, since several simplifying approximations have been used in order to facilitate model development. Additionally, certain properties likely to be observed in operational fuel cells, such as thermal gradients, have not been considered. Nonetheless, the insights gained from the mechanistic assessment of fuel cell processes were found to give the resulting empirical model a firmer theoretical basis than many of the models presently available in the literature. Correlation of the empirical model to actual experimental data was very good.A model mapping overvoltage in a proton exchange membrane (PEM) fuel cell as a function of val~ious contributing variables would be of great utility to researchers and operators. Two common modeling approaches are: (i) theoretically based mechanistic approaches and (it) empirically based analysis. Although, many mechanistic models can be found in the literature, ~-4 they generally require the knowledge of parameters which are not readily available, such as, transfer coefficients, humidity levels, membrane, electrode, and active catalyst layer thicknesses. Empirical modelsy on the other hand, are generally accurate over a small operating range. They fail to reflect the actual processes involved in fuel cell operation and thus are not applicable over a broad range of conditions. An approach combining both mechanistic and empirical modeling techniques has the potential to couple both mechanistic validity and the inherent simplicity of the empirical approach.The goal of the present work was to couple a mechanistic evaluation of fuel cell processes with the application of empirical linear regression modeling techniques, in order to develop a performance model for a FEM fuel cell. A three-stage approach was followed. Initially, mechanistic modeling techniques were employed to determine the characteristic dependencies of fuel cell operation. This yielded simple algebraic expressions defining the thermodynamic equilibrium potential, as well as overvoltages due to activation, ohmic resistance, and mass transport. In the second stage, numerical parametric equations for each of the voltage loss terms were determined from experimental data. These equations reflected the form of the algebraic expressions developed in stage I. The third stage involved the statistical analysis of the resulting param...

Dynamic Modelling and Simulation of a Fuel Cell Generator

“…(3)) gives the open circuit cell potential, E, as a function of cell temperature, T, and the reactant partial pressures [4,7]:…”

“…The activation drop can be analysed by Tafel's equation and the empirical model outlined in [7] is considered in this regard. …”

“…An empirical differential equation, given in [9], could be solved to determine the proton concentration, C H+ , and Eqs. (11) and (12) could be used to estimate the membrane conductivity, r [7,9,16]:…”

Study of the Effect of Gas Channels Geometry on the Performance of Polymer Electrolyte Membrane Fuel Cell

“…A number of studies have examined various aspects of PEM fuel cell performance as a function of operating conditions (see [5][6][7][8][9][10][11][12][13] for examples) in order to find ways to improve its performance. One significant tool in the optimization study of fuel cell performance is computational modelling, which can help understand the fundamental phenomena taking place in the fuel cell system [14].…”

Control of Incoming H2/O2 Flows in a PEM Fuel Cell

“…Since the very early development, the control of fuel cells has caught the attention of many authors (Biyikoglu, 2005;Caux et al, 2005;Amphlett et al, 1995a;1995b). Different approaches for fuel cell models are found in the literature (Wahdame et al, 2006;Candusso et al, 2002;Pukrushpan et al, 2002).…”