Diagnosis of hydrogen crossover and emission in proton exchange membrane fuel cells

Abstract

Keywords: EIS PEM fuel cells Hydrogen leak Hydrogen pumping Air starvation Fuzzy logic a b s t r a c t When hydrogen leaks through holes or cracks in membrane-electrode assemblies (MEAs) in Proton Exchange Membrane (PEM) fuel cells, it recombines directly with air. This recombination results in a reduction in oxygen concentration on the cathode side of the MEA. In this paper, the signatures of electrochemical impedance spectroscopy (EIS) are analyzed in different multi-cell stack configurations to show the relation betweenhydrogen leak rate and reduced oxygen concentrations. The reduction in concentration was made by mixing oxygen with nitrogen at different rates, and the increase in hydrogen leak rate was made by controlling the differential pressure (dP) between anode and cathode. To analyze the impedance signatures, we fit the data of oxygen concentration and dP with the parameters of a Randles circuit. The correlation between the parameters of the two data sets allows us to understand the change in impedance signatures with respect to reduction of oxygen in the cathode side. To have a better insight on the effect of insufficient oxygen at the cathode, a model that establishes a relationship between impedance and voltage was considered. Using this model along with the impedance signatures we were able to detect the reduction of oxygen concentrations at the cathode with the help of fuzzy rule-base. However, resolution of detection was reduced with the reduction of leak rate and/or increases in the stack cell count.

Hydrogen Leakage Diagnosis for Proton Exchange Membrane Fuel Cell Systems: Methods and Suggestions on Its Application in Fuel Cell Vehicles

“…In the output voltage diagnosis, hydrogen leakage in the stack (or single cell) is diagnosed by detecting the abnormality of the stack (or single cell) output voltage caused by the hydrogen leakage in the stack (or single cell). In [10,100,[104][105][106][107][108][109][110], the different diagnosis methods based on the output voltage diagnosis for diagnosing hydrogen crossover leakage in the stack (or single cell) have been proposed respectively.…”

“…Under the condition of normal and hydrogen crossover leakage, Mousa et al [104,105] analyzed the influence of different oxygen concentration and the pressure difference between the cathode and anode on the output impedance. In their studies, the impedance signature model of the fuel cell stack was established based on the Randles model, and the output voltage of the stack was estimated by the impedance signature.…”

“…In the existing research, there are many diagnosis methods, either for the hydrogen leakage from the hydrogen supply system or for the hydrogen leakage in the stack. As shown in Figure 1, these methods used different strategies to diagnose hydrogen leakage, mainly including environmental hydrogen concentration diagnosis [24][25][26][27][28][29][30], hydrogen pressure decay diagnosis [9,10,[32][33][34]100,[112][113][114], gas leakage diagnosis by model-based methods or data-driven methods [36][37][38][39][40][41][42][43][44][45][46][47][48][49][50]115,123], cross-current diagnosis [10,[100][101][102][103], and diagnosis by stack (or cells) output voltage [10,100,[104][105][106][107][108]…”

Fault detection and isolation of high temperature proton exchange membrane fuel cell stack under the influence of degradation

“…Common for many of these diagnostics methods are that the fuel cell characterization often is done by electrochemical impedance spectroscopy 45 (EIS) [12,13], which has the main advantage that it can be done in-situ at low energy cost [10]. When using EIS as fuel cell characterization technique, the model based methods utilize the parameters of an electrical equivalent circuit (EEC) as features [14,15,16]. For the non-model based methods, using 50 EIS as fuel cell characterization method, often uses parts of the impedance spectrum as features for fault detection [17,18,19].…”

Fault Diagnosis of Practical Polymer Electrolyte Membrane (PEM) Fuel Cell System with Data‐driven Approaches

“…In addition the performance framework is studied using test data from a practical fuel cell system. Compared to the fault diagnostics using EIS, etc., this fault diagnostic framework can identify the fuel cell faults without interrupting its operation, while measurement of EIS requires a relatively specialized technique with expensive and bulky equipment . Moreover, the fuel cell fault diagnosis under dynamic load current conditions can be performed with the fault diagnostic framework, this makes this approach more suitable for practical fuel cells system subjected to dynamic load conditions, especially in automotive applications.…”