Backwards Looking Summary
Since the last Progress Report, the group has completed the Advanced Research and Development (Ar&d) phase of the project. The purpose of the Ar&d was to better understand small subsets of the working AEV and how to better design the current AEV model to best suit the upcoming challenges. The first act was to choose two subjects to research. The group chose to research battery testing and track variance.
For the research of battery testing, the group decided to test how the required energy amounts change when comparing two test runs, one with a constant acceleration and one with a instant acceleration. Below, Figure 1 displays the energy consumption of the constant acceleration test. The graph, as expected, has a continuous line diagonally across the graph, with a spike around between the 25% and 30% power ranges, suggesting that this 5% power increase is a greater joule increase then previous 5% power increases. This however could also be chalked up to a margin of error unaccounted for due to testing taking longer than expected.
Figure 1
Figure 2 displays the energy consumption for instant acceleration test. As expected, the graph shows very obvious jumps in power usage, where the jumps signify that the motor increased its power output by 5%. The total joules used here equate to 80.654, versus the previous test showing a joule total of 72.206. We see that the constant acceleration has overall less joule usage then the instant acceleration, but it can be logically assumed that the constant acceleration also has less overall distance traveled.
Figure 2
Unfortunately, due to a lack of time, there was only time for the group to complete one test for each scenario described above. Since there is only one test completed for each scenario, it cannot be confirmed absolutely that the findings are correct because of the possibility of random errors. However, the group is confident that they completed the tests as accurately and thoroughly as possible in order to yield the best results.
For the groups research on track variance, the group was testing the incline at the beginning of each of the four main tracks that will be used in the performance tests. The inclines were known to be similar, but not perfectly equal. The same AEV model was ran on each track three times from the starting point. The same code was used each time with the same power output, so that the only variable was the track itself. The first track tested was the red track. The red track averaged a total of 137 inches traveled by the AEV, as shown in Figure 3. With the code used, the AEV was able to traverse to the peak of the incline before the power was cut.
Figure 3
The next track tested, the green track, resulted in similar measurements as the red track, with a average distance of 139 inches travelled, as shown in Figure 4. This means that the red track and the green track had similar incline angles, although the green did have slightly less of an angle than the red track. This also meant that to reach the same distance, the AEV on red track needed more power than the AEV on green track, albeit very little more power.
Figure 4
The next track tested was the blue track. With an average of 145 inches traveled, as shown in Figure 5, the blue track had the smallest incline of all the tracks tested. To reach the same distance as blue track, AEVs on red and green will need more energy. Blue however will have less speed gained when moving down the opposite incline due to its lower angle, and groups using blue track should prepare for such a case where they need more power to reach the end from the station than other groups on other tracks.
Figure 5
The final track tested was the purple track. With an average of 135 inches travelled by the AEV, as shown in Figure 6, the purple track had the largest incline out of the tracks tested. Therefore, more energy will be needed to get an AEV on the purple track as far as an AEV on the red, blue, or green tracks. However, an AEV on the purple track will gain more speed on the downward slope than an AEV on the red, blue, or green tracks’ downward slopes.
Figure 6
One other note: For all the track variance tests, the amount of joules used clocked in at 42 J for the red track, 44 J for the green track, 41 J for the blue track, and 41 J for the purple track. It is assumed that the change between green and blue is within a margin of error, but other reasons or causes for a spike in energy is yet known. The average of these joule counts does equal 42, therefore assuming the margin of error is 2 joules, all results do fit within the margin.
Unfortunately, due to a lack of time, the group was only able to perform three tests on each of the tracks tested. This means that calculating statistics such as standard deviation and median distance travelled would not yield meaningful data.
From the team’s research, along with the research results from other groups, there was a lot to be gained and learned. One of the key takeaways from the team’s own research was the code used in the track variance test. The code used gave a very good starting code for the AEV’s first performance test since the code propelled the AEV to approximately the correct position needed in the first performance test. With a few tweaks, the code would be able to be used in the future. From other groups’ research, it was learned that the motors used on the AEV produce more power when running backward. This information will be very useful when the group rebuilds the AEV for the performance tests. As a whole, the group learned a lot about managing working time during the engineering design process. Time has to be managed before the work begins in order to get the most efficient use out of the time given to work.
Forward Looking Plan
Now that the group has finished with the Advanced Research and Development and has seen all of the other groups’ presentations on their Advanced Research and Development, the focus is now on the Performance Tests. Before the final performance test there are an additional two tests that will have to be completed. The group will spend three days a week working on the AEV Project now that all the classes are being dedicated to the project.
The purpose of the two performance tests is to help make sure that groups are on the right path to being able to complete the final test. The first performance test is due week 9c and the second performance test is due week 10c. The first performance test focuses on the first half of the final task. The group is asked to get their vehicle to start, stop in between the gate sensors, wait for the gate to open, and then proceed through the gate. The second performance test adds on to the first performance test. Not only does the group have to be able to proceed through the gate, but they also have to pick up the load. When picking up the load the team’s AEV must wait a certain amount of time before it takes off again, and when starting back up the team must make sure they do not start back up to fast that the load disconnects. The team goal is obviously to complete these two tasks, but it is also to prepare for the final evaluation.
After the two performance tests comes the final performance test. This will take place during week 12c. This is the final tasks which puts the performance tests together. The group’s AEV will have to proceed through the gate, pick up the load and then come back through the gate.
The schedule ahead consists mostly of the performance tests. As noted before, the first performance test is conducted week 9c and the second performance test is week 10c. There is a little time in between the performance tests and the final performance test which is week 12c.
The team will try and keep in touch over the break just to make sure we have a definite plan to attack the performance tests. After break the group will meet to execute this plan. This includes writing the code for the AEV and making sure the AEV is assembled properly and everything is working. Modifications will be made to the current AEV based off of research findings, including reversing the motors. Modifications will also be made to the code based on the research findings. A code similar to that used in the track variance research will be implemented into the code and the possibility of adding power breaking to the code will be discussed. During the meetings, the group will also be sure to keep the website updated.
Appendix
Team Meeting Minutes
2/12/18
Attendance: All members present.
Location: Skype
Time: 8:00 pm
Topics of discussion: Went over what need to be finished for our committee meeting,
Set plan to work on AEV at the end of this week with more advanced research.
2/13/18
Attendance: All members present
Location: Hitchcock Hall
Time: 9:35 am
Topics of discussion: Start Advanced Research and Development (battery testing)
2/20/18
Attendance: All members present
Location: Hitchcock Hall
Time: 9:35 am
Topics of discussion: Finish Advanced Research and Development (track variance testing)
2/25/18
Attendance: All members present
Location: Smith Laboratory
Time: 7:30 pm
Topics of discussion: Completed Ar&d oral presentation. Also looked to complete our website and add a few touch ups.
3/3/18
Attendance: All members present
Location: Smith Laboratory
Time: 7:30 pm
Topics of discussion: Completed revised version of Progress Report 1.
3/6/18
Attendance: All members present
Location: Hitchcock Hall
Time: 9:35 am
Topics of discussion: Revised AEV based on research results. Discussed how to complete performance test one.
3/9/18
Attendance: All members present
Location: Virtual
Time: 10:00
Topics of Discussion: Brief meeting to clarify what needed to be completed on the progress report and delegate who was taking on which parts.
Code Used:
Figure One (Battery Testing):
celerate(1,0,5,3);
goFor(2);
celerate(1,5,10,3);
goFor(2);
celerate(1,10,15,3);
goFor(2);
celerate(1,15,20,3);
goFor(2);
celerate(1,20,25,3);
goFor(2);
celerate(1,25,30,3);
goFor(2);
celerate(1,30,35,3);
goFor(2);
Figure Two (Battery Testing)
motorSpeed(1,5);
goFor(5);
motorSpeed(1,10);
goFor(5);
motorSpeed(1,15);
goFor(5);
motorSpeed(1,20);
goFor(5);
motorSpeed(1,25);
goFor(5);
motorSpeed(1,30);
goFor(5);
motorSpeed(1,35);
goFor(5);
For All Track Variance Testing:
motorSpeed(4,35);
goToRelativePosition(197);
brake(4);