The humidity levels in PEM fuel cells has a profound effect on the performance. However, in large fuel cell stacks the relative humidity (RH) changes significantly along the length of the stack. This paper presents a control-oriented model with spatial considerations of the distribution of water vapor that can be used to properly predict and control the humidity levels in a PEM fuel cell stack.
This model predicts the dynamic response of the stack in real-time by tracking energy and mass flows in four basic CVs. To provide spatial information of the stack conditions, the cathode CV was further subdivided into 6 sub-volumes. The model was validated with experiments conducted on a 28-cell, 2kW fuel cell stack. The validation results show that the multiple CV approach can accurately predict the stack RH and voltage, and is capable of predicting localized voltage losses. This new modeling methodology shows the importance of a distributed understanding of the RH profile, and provides a tool to create control algorithms for PEM fuel cells that consider the health of all the sections of the stack.