Experimental study of the performance degradation of proton exchange membrane fuel cell based on a multi-module stack under selected load profiles by clustering algorithm

In order to investigate the impact of actual vehicle conditions on the durability of fuel cell, the hierarchical clustering algorithm is used to select two representative driving cycles, which are urban driving cycle and expressway driving cycle. Then a durability test is performed under two dynamic conditions and one steady-state condition. This study chooses a newly designed fuel cell with four modules which can be applied different loading conditions simultaneously. It ensures operating conditions of each module are consistent during the experiment. Eventually, the polarization curve, electrochemical impedance spectroscopy and voltage are measured as health assessment indexes. The degradation of different modules can be compared more precisely by above methods. The results show that the fuel cells have the fastest performance degradation under urban driving cycle, followed by expressway driving cycle, finally steady-state condition. There is a certain time threshold, ohmic and activation resistance has a significant increase and fuel cell has a significant performance degradation after it, the severe driving conditions cause it to be advanced. Otherwise, the voltage degrades faster at high currents by extracting the voltage at different currents. The voltage degradation percentages of module 1 and 2 at 40A both exceed the threshold of 10%.