Focus Areas Supported

Support for key point 1 was found by looking at the balance of each prototype designed by the team on the table-side suspended rail and by looking at how the vehicle swayed going down the track as well as if the wheels were both on the track at all times or not. Furthermore, supporting the key points 1 and 2, the results for the energy analysis portion of the advanced research and development are as follows: the marks error found for the tested AEV was 13.0 marks which was significantly higher than the class average of 7.0 marks. To account for this, the group decided to rerun our reflectance sensor test to try and fix the issue and in the next lab time, the newly fixed sensors will be tested using the same code to determine if the marks error decreases.  The calculated propeller force was found to be 13.3gmf which was greater than the class average of 12.1gmf meaning the tested design was able to get more force from the given energy based on the type of blade used and its specific placement on the AEV. The frictional force was calculated to be 3.1gmf which was the smallest in the class with an average of 4.9gmf although the tested AEV had the greatest mass (264.3g) in the class with an average of 251.5g. This was explained by the incredible precision in the balance of the group’s AEV as the balance on the rail keeps the wheel from bounding and rumbling which would in fact reduce the frictional force. This small frictional force makes up for the high mass of the tested AEV. The net force for the tested AEV was 10.2gmf which was greater than the class average of 7.3gmf. This was due to the fact that the tested AEV had a propeller force larger than the average and the smallest frictional force, yielding a relatively large net force.

Key point 3 was the fact that the AEV was consistent in its results without the use of a servo. Data to support this was the fact that the trials within each performance tests were relatively consistent and the graphs of each of the runs looked basically identical with only minimal changes in the amounts of energy used as shown in the graphs below.

These three graphs represent the code’s run for performance test 1, and this was the result of running the code three consecutive times. The difference in amount of energy used between all 3 trials was only 3J and this was mostly seen as a result of trial 2. Trial 2 used the most energy while trials 1 and 3 were approximately the same. These results show that without using the servo, a consistent AEV can still be obtained and the money saving from the capital cost can be put towards a slight increase in amount of energy used. The codes run for PT2, 3, and 4 followed the same consistent pattern.

For key point 4, there was not much data to support this as it was more of an observed behavior that was made by altering the design of the AEV. Much like as was stated in the sales pitch, the new design of AEV which can be viewed below allowed for easier connection to the caboose without having the front wheel roll past the tape. The design change took place after performance test 2 when the team realized the AEV was going over the tape and getting an accuracy penalty. This change consisted of moving the arm farther back along the T-shaped base and moving the arduino into the vertical part of the T-shaped base. This gave approximately a 7 inch distance between the front wheel of the AEV and the caboose connection bracket (The old distance was about 3 inches).  This allowed for the AEV to more effectively and efficiently connect to the caboose without worrying about going past the tape since such a great impact speed was needed for that to happen. The group decided to do this due to not having to worry about the accuracy penalty and not having to program the code to just barely connect to the caboose as that is inconsistent. This also saved the need to use energy with power braking and/or the use of rotating the servo arm. The team was able to increase the motor speed goFor() command by a total of 0.8 seconds before the AEV would roll past the tape. This showed that the team could increase the goFor() slightly so that the AEV would not just barely touch the caboose, while still not pushing it too far. This was in essence the team’s desire by increasing accuracy by not having to just barely touch the caboose.