Sunil K. Roy

Interpretation of Low-Frequency Inductive Loops in PEM Fuel Cells

Impedance models were developed to account for reaction mechanisms that may be responsible for the inductive impedance response often seen at low frequencies in proton exchange membrane (PEM) fuel cells. Models that incorporate reactions without surface intermediates cannot account for these inductive features. Inductive loops can be predicted by models that account for formation of hydrogen peroxide as an intermediate in a two-step oxygen reduction reaction. Hydrogen peroxide is considered to be a degrading agent for materials used in the fuel cell components (membrane, electrodes), and its formation under the fuel cell operating conditions is reported in the literature. Inductive loops can also be predicted by models that account for Pt dissolution and associated deactivation of catalytic activity. These interpretations are supported by experimental evidence reported in the literature. Interpretation of impedance spectra in terms of side reactions may prove useful for predicting the lifetime of fuel cell performance.

Error analysis of the impedance response of PEM fuel cells

2polymer electrolyte membrane PEM fuel cell. The stochastic errors were found to be roughly independent of frequency and were similar for the two instruments used. The measurement-model approach was found to be capable of identifying both high-frequency and low-frequency artifacts in the spectra. The low-frequency inductive loops were found, in some cases, to be consistent with the Kramer–Kronig relations. In other cases, nonstationary phenomena were found to have influenced the low-frequency response. This work showed that once steady-state operation was achieved, the low-frequency inductive loops in the impedance response could be associated with physical phenomena within the fuel cell. In addition, the formalism of the measurement-model error analysis provides a means for determining whether a steady state has been achieved. Polymer electrolyte membrane PEM fuel cells are electrochemical devices capable of continuous conversion of the chemical energy of reactants into electrical energy. They are currently in development for a wide range of commercial applications and are especially important for stationary power sources. Impedance measurements of PEM fuel cells provide the opportunity for in situ identification and quantification of physical phenomena which influence cell performance, but the small value of cell impedance complicates measurement. Impedance spectra typically exhibit inductive features at high frequency, and some authors report inductive loops at low frequencies. The high-frequency inductive features are understood to be caused by instrument artifacts, but the interpretation of the low-frequency inductive loops is less clear. While the low-frequency loops have been tentatively attributed to side reactions, 1,2 they could also be caused or influenced by nonstationary phenomena. The objective of this work was to use the measurement-model concept 3-6 to assess the error structure of the impedance measurements taken for a PEM fuel cell.

Graphical Estimation of Interfacial Capacitance of PEM Fuel Cells from Impedance Measurements

Graphical methods were used to extract values of constant-phase element CPE parameters and interfacial capacitance from the high-frequency part of impedance data collected on a polymer electrolyte membrane PEM fuel cell. The impedance data were recorded as a function of current density, time, temperature, backpressure, and flow channel and gas diffusion layer design. The effective capacitance was estimated under the assumption that the CPE behavior could be attributed to two-dimensional 2D potential and current distributions. The value of the interfacial capacitance was reduced when the cell was operated under dry or flooded conditions. The interfacial capacitance decreased with time over a time scale consistent with the approach to a steady state. In addition to providing insight into physical processes, the parameters obtained from graphical methods can be used for model reduction when regressing impedance data. The methodology presented can be applied to electrochemical systems for which the high-frequency data reveal CPE behavior caused by 2D potential and current distributions.