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The influence of the air cooling flow rate and current density on the temperature, voltage and power density is a challenging issue for air-cooled, open cathode fuel cells. Electro-thermal maps have been generated using large datasets (530 experimental points) to characterise these correlations, which reveal that the amount of cooling, alongside with the load, directly affect the cell temperature. This work uses the design of experiment (DoE) approach to tackle two challenges. Firstly, an S-optimal design plan is used to reduce the number of experiments from 530 to 555 to determine the peak power density in an electro-thermal map. Secondly, the design of experiment approach is used to determine the fastest way to reach the highest power density, yet limiting acute temperature gradients, via three intermediate steps of current density and air cooling rate.

Design of experiments to generate a fuel cell electro-thermal performance map and optimise transitional pathways