PITCH Project

 

TO:                  EASC2211 Students – Section 03

FROM:            Jinsong Yu, EASC Instructor

RE:                   PITCH Project 2 – Recommendation fora Fuel Cell Model

Date:                April10^th, 2015

 

 

The development department of a fuel cell company is working on a small fuel cell that will be used in home applications.  Data has been obtained on the performance of the latest prototype.  You are asked to use the performance data to derive a model that can be used to predict the voltage delivered by the fuel cell at different current loads.  The work should be summarized in a technical memo, due Monday, May4^th, 2015.

 

The form of the model should be similar to that used in class to model batteries, a constant current source (I_S) in parallel with an internal resistance (R_S).  Thismodel will be used by the ApplicationsDepartment to determine the ability of the fuel cell to operate various home appliances.  Engineers in that department will analyze circuit models that incorporate various loads with your model representing the source.  In addition, the model of the voltage/current behavior will also be used to find the best configuration for cells arranged in series and parallel to deliver the necessary voltage and current.

 

The data for the fuel cell areshown in Table 1 and Figure 1.  At low current draw the voltage drops steeply from the open-circuit value (zero current), but then drops more gently over the middle range of current.  At high current loads the voltage again begins to drop as the fuel cell reaches its limit.

 

In order to model this highly non-linear behavior you will need to develop 3 separate models:

 

• Model for low current densityregion, I_S-low, R_S-low

 

• Model for medium current density region, I_S-med, R_S-med

 

• Model for high current density region, I_S-high, R_S-high

 

Sketch a circuit diagram to show the source model (constant current source with parallel resistor) and generic load. Using KVL, KCL and Ohm’s law you can establish the relationship between measured terminal voltage and current drawn from the fuel cell. Use regression techniques with data in each region to obtain the constants I_S and R_Sto best fit the data in each region.You will need to exercise judgment in deciding the cut-off points for each region.  I suggest you overlap the data used in each region by one data point – that is the low and medium region will both use the data point that separates the regions. One strategy for judging the best cut-off points is to usea measure of the error across the full data set, such as the average absolute value of difference between the predicted and actual data points. Determine the value of this measurement using different cut-off points and select the best choice based on the minimum error measurement.

 

Table 1
Fuel Cell PEM-35 Performance Data
Current Density	Voltage	Current Density	Voltage	Current Density	Voltage
mA/cm2	Volts	mA/cm2	Volts	mA/cm2	Volts
0.0	1.24	8.0	0.92	22.0	0.80
0.2	1.14	10.0	0.84	24.0	0.73
0.5	1.09	12.0	0.83	26.0	0.74
1.0	1.00	14.0	0.89	28.0	0.65
2.0	0.99	16.0	0.82	30.0	0.52
4.0	0.89	18.0	0.82	32.0	0.50
6.0	0.87	20.0	0.79	34.0	0.38
Experimental data for single cell unit of PEM-35 measuring terminal voltage under varying loads.Note that the data here is organized into 3 sets for convenience in the table.  This should not be used as a grouping of the data for modeling purposes.

 

Report your results to Dr.Robin Hood, Director of Applications Department, in a technical memo, no longer than 3 pages.  The memo should include a presentation of your results along with a discussion of how you selected the regions for each model with summary tables and figures to justify your choices.  Do not include all data in your report, but select values to show in small tables and figures to make your case.  For example, you may show a table with the average error (absolute value) between experiment and model for each region, rather than the error for every point.  Attach1 or 2 sheets from your workbook to show all the results, including comparisons between the experimental data and the model predictions.

 

Students may work in pairs to develop the models, but each student must write and submit his or her own memo.Your work is due Monday, December 1^st, 2014. The memoand the spreadsheet should be emailed to me.