D.4 Conclusion and Discussion

When searching for a power source for a specific application, a first guesstimate during the concept phase can be done very well with the Power Source Selector from Liang Fu and the general overview in Flipsen (2006). In Section D.3, an analytical model, the transfer function, was introduced that produces weight and volume characteristics of a FC hybrid system based on general input parameters like load profile and use time. The model is optimized to predict the volume for a FC hybrid system based on general input parameters.

Besides analytical models for FCs and FC hybrids, other power sources and combinations of power sources have to be developed:

• Power sources of interest are hydrogen FCs, micro internal combustion engines, and photovoltaic cells.
• Energy sources of interest are hydrogen and other fuels.
• Combined power sources like primary and secondary batteries and capacitors are also of interest.

Because the basic parameters, like the power density of FC stacks, will change over time, a database of subcomponents has to be made. The database should be updated regularly, and new characteristics of components should be added. In Figure D.3.1, the flowchart for the power source (hybrid) selection algorithm is shown.

Notes

1. This method specifically compares lithium-ion batteries with DMFCs, but it can also compare other power sources or combinations thereof.

2. Volumetric canister coefficient: 15% of the total volume consists of the canister, based on figures from Xie et al.(2004).

3. Mass canister coefficient: 20% of the total mass consists of the canister, based on figures from Xie et al.(2004).

4. This is the direct power output over the stacks volume. The power density as used in this case is based on the systems power output over the fuel cell stacks volume (77.3 W L⁻¹).

5. It is assumed that the overall system efficiency equals the systems voltage efficiency. The overall system efficiency (E_out/E_in) of the Motorola FC system is 20%.