Algorithm development for electrochemical impedance spectroscopy diagnostics in PEM fuel cells

The purpose of this work is to develop algorithms to identify fuel cell faults using electrochemical impedance spectroscopy. This has been done to assist with the development of both onboard and off-board fuel cell diagnostic hardware. Impedance can identify faults that cannot be identified solely by a drop in cell voltage1. Furthermore, it is able to conclusively identify electrodelflow channel flooding, membrane drying, and CO poisoning of the catalyst faults. In an off-board device an equivalent circuit model fit to impedance data can provide information about materials in an operating fuel cell. It can indicate if the membrane is dry or hydrated, and whether or not the catalyst is poisoned. In an onboard device, following the impedance at three frequencies can differentiate between drymg, flooding, and CO poisoning behaviour. An equivalent circuit model, developed through a process of iterative design and statistical testing, is able to model fuel cell impedance in the 50 Hz to 50 kHz frequency range. The model, consisting of a resistor in series with a resistor and capacitor in parallel and a capacitor and short Warburg impedance element in parallel, is able to consistently fit the impedance of fuel cells in normal and fault conditions. The values of the fitted circuit parameters can give information about membrane resistivity, and can be used to consistently differentiate between the fault conditions studied. This method requires the acquisition of many data points in the 50 Hz to 50 kHz frequency range and an iterative fitting process and thus is more suitable for off-board diagnostic applications. Monitoring the impedance of a fuel cell at 50 Hz, 500 Hz, and 5 kHz can also be used to differentiate between flooding, drying and CO poisoning conditions. The real and imaginary parts, and the phase and magnitude of the impedance can each be used to differentiate between faults. The real part of the impedance has the most consistent change with each fault at each of the three frequencies. This method is well suited to an . . . 111 onboard diagnostic device because the data acquisition and fitting requirements are minimal. Complete implementation of each of these methods into a final diagnostic device, be it onboard or off-board in nature, requires the development of reasonable threshold values. These threshold values can be developed through testing done at normal fuel cell operating conditions. Table of