Abstract or Introduction
This thesis targets the multi-scale modeling and optimization of Polymer
Electrolyte Membrane Fuel Cells (PEMFCs). We focus our research on two types of PEMFCs, i.e., liquid-feed direct methanol fuel cell (DMFC) and hydrogen PEMFC (H2 PEMFC). These two types of PEMFCs attract more attention
recently due to its high power density and energy efficiency, low temperature operating condition, and system simplicity.
First, we examine a direct methanol fuel cell (DMFC) model that captures the essence of electrode kinetics and methanol crossover through the polymer electrolyte membrane (PEM). Model parameters and key factors for the DMFC model including methanol crossover are identified. Moreover, we established a relationship between the methanol feed concentration and the power density at a given current density. To gain insight into the effect of the methanol feed concentration, we also performed sensitivity analysis between the cell voltage and the methanol feed concentration. From the sensitivity curve, we are able to identify the optimal feed concentration, which provides the highest power density output for a set value of the current density. Finally, the optimal response of the cell voltage to the change of the feed concentration is studied via dynamic optimization to the differential algebraic equation system. This dynamic optimization results provide a constant feeding strategy that achieves the highest
power density at given operating condition specified by a set current density.
In the H2 PEMFC modeling, a one-dimensional model is adopted to examine the
transport phenomena at the anode backing and catalyst layer. For the cathode part, a standard curve is used to describe its voltage response to the current density. We focus on describing the “CO poisoning” effect at the anode catalyst layer and the fuel utilization (or H2 dilution) effect on the anode flow channel. The complicated anode reaction kinetics is modeled to describe the CO effects, yielding a quantitative fit to the measured dependence of voltage loss at the inlet CO level. From this model, we find that voltage losses associated with CO poisoning are amplified significantly with diluted hydrogen feed streams and particularly so under high fuel utilization. CO poisoning effect can be relieved via O2 bleeding. We incorporate O2 bleeding in the new model and couple it further with reduced-Hessian sequential quadratic programming (rSQP) optimization scheme.[...]
- Quote paper
- Dr. Cong Xu (Author), 2005, Multi-scale Modeling and Optimization of PEM Fuel Cells, Munich, GRIN Verlag, https://www.grin.com/document/183932