Lab 2- External Sensors + System Analysis 1

Summary

During the second week of the AEV project, the team performed various tests to become more familiar with the propulsion system efficiency and the wind tunnel testing equipment as well as the external hardware components, troubleshooting techniques, and program function calls for using the external sensors with AEV control.  This week of lab also allowed the team to relate the AEV to real life objects as well as the wind tunnel testing tube.

First, the team built the basic structure of the AEV and added the sensors.  The Arduino software was opened, the battery was plugged in, and the board was turned on.  The sensors were oriented and then tested by programming simple commands to move the forward or backward for a certain amount of marks using a certain amount of power.  After the sensors were installed and tested, they were zip tied down and a line of code was tested and demonstrated to the instructional team.  Next, a team member recorded and observed the effects of varying power levels on a wind turbine.  The percent power, current, and thrust scale reading was recorded at a 7.4 voltage setting and with the velocity speed indicator set to 2.8 meters/second.  

Results and Analysis

The results from the Wind Tunnel Analysis Lab are shown below in Table 1. The thrust values from the table were measured in grams and the baseline measurement was 146 grams.

Table 1: Wind Tunnel Data

From the data, it can be observed that as the power setting on the Arduino increased, the current, thrust and RPMs all increased. An important inference to taken away from this is that all of the variables are related to each other directly. As a more graphical representation, Figure 1, below, shows the relationship between the thrust scale reading and the power setting on the Arduino.

Figure 1: Thrust Produced by 3030 Puller Configuration

From the data in Table 1, quantities such as a calibrated thrust, power input and output, propulsion efficiency, and advance ratio can all be calculated. The data is available in the Appendix, Table 2, along with sample calculations. These values are important in determining what power is the most efficient to run the AEV.

Figure 2: Propulsion Efficiency vs Advance Ratio

By graphing the propulsion efficiency vs. advance ratio, as shown above in Figure 2, the way to run the AEV while using the least amount of energy can be determined. Because the graph is set up right to left, in regards to power input, the maximum efficiency occurs at 30 percent power. This can be determined because each data point is 5 percent away from the one next to it and the furthest point to the right is 15 percent power. This means that running the Arduino at roughly 30 percent power will be the most efficient. This power setting is plausible because it generates enough force to overcome the static friction in the propeller’s motor.

Table 2: Wind Tunnel Data Analysis