Feedback control of DMFCs

Regulating methanol feed in DMFCs is important for improving electrical performance and fuel utilization.  Low methanol concentration reduces the reaction rate at the anode due to Nernstian effects resulting in a lower operating voltage. However, simply increasing the methanol concentration does not always lead o improved performance due to increased methanol crossover from the anode to the cathode resulting in mixed potential losses, and the associated fuel loss. Hence, there exists an optimal intermediate value of methanol concentration for each current density that will yield the highest electrical performance (voltage). Additionally, there is a two phase flow of methanol solution and gaseous CO2 bubbles in the anode side of DMFC, which reduces the effective mass transfer to the cathode catalyst layer. Evacuation of these bubbles is also necessary for good performance. Typically, the concentration of methanol in DMFCs is monitored with concentration sensors which operate on the principle of sensing either the physical or electrochemical properties of the methanol solution .However; concentration sensors for fuel cells must meet a wide range of requirements such as resolution, accuracy, and rapid response time. Sensor-less monitoring of the methanol feed can increase the overall efficiency of the DMFC system.

We are working to develop of an in-situ methodology using the feedback of cell voltage and anode pressure drop to regulate the methanol feed concentration and flow rate for maximum power density. This methodology with voltage as feedback is demonstrated at the current densities of 50, 100, and 250 mA/cm2 and the results for optimal concentration are presented. Fuel loss as a function of methanol concentration is evaluated by oxidizing the crossover methanol at the cathode exhaust and measuring the CO2 mass flux.  Currently we are developing a methodology be to utilize the feed back of anode flow field pressure drop to regulate methanol flow rate.

Figure 1.  Schematic of the experimental set up to optimize methanol methanol feed concentration for maximum performance/p>

Figure 2.  Modeling of one design parameter