Motor Amount Code
reverse();
motorSpeed(4,25);
goFor(2);
motorSpeed(4,20);
goToAbsolutePosition(100);
reverse(4);
motorSpeed(4,30);
goFor(1.5);
brake(4);
Motor Amount Graphs
One Motor
Two Motors
When comparing the one motor power vs time and power vs distance graphs, it is clear that one motor is more energy efficient, because less power is outputted per unit distance. However, two motors clearly causes the AEV to go farther, but at the cost of more energy consumption. We can conclude from these graphs that one motor is the most cost effective and energy efficient route to take, given our current resources.
Motor Configuration Code
reverse();
motorSpeed(4,25);
goFor(2);
motorSpeed(4,20);
goToAbsolutePosition(100);
reverse(4);
motorSpeed(4,30);
goFor(1.5);
brake(4);
Motor Configuration Graphs
Configuration One
Configuration Two
The main difference between the two configurations was the motor placement. Configuration one consisted of one motor on the left side of the AEV, and configuration two consisted of one motor in the middle. It is clear from the graphs that configuration two was more energy efficient. This occurs because the motor is set in the middle of the base, meaning the AEV will be moved straight down the track. Due to the fact that the motor in the first configuration was set to the left side of the base, energy was wasted when the AEV was being propelled straight down the track.
Performance Test 1:
The goal of performance test 1 was to direct our AEV through the first gate of the test track. To accomplish this our AEV had to travel a certain distance and stop at the first gate for 7 seconds, and then proceed through the gate. The team tested this with the two designs that were decided upon after the concept screening and scoring matrices were completed.
The team knew from AR&D motor amount testing that the one motor design would be the most energy efficient and it completed the objectives set in the MCR with full marks. The team also used this time to see which functions would be more consistent in the code such as time vs position commands and decided on position commands for this performance test.
Performance Test 2:
For the second performance test the team had to build on the first performance test code by creating code that would have the Advanced Energy Vehicle (AEV) travel to the caboose, dock with the caboose within the loading zone without pushing the AEV past a tape marker, wait for 5 seconds, then pull the AEV out of the loading zone. Along with this the team had to create a second program accomplishing the same objectives and then compare the two programs in terms of consistency and energy efficiency.
Initially the team started using the one motor design that was used for PT1 and although it worked just fine 70% power was needed just to pull out the caboose out of the loading zone, and that power couldn’t pull the caboose up the hill. After being told that anything above 70% would burn out the motors the team decided to use the lower cost 2 motor design, to lower the power needed from each motor as to prevent burnout. After that the team created 2 programs that completed the objectives listed above. One program used more power and braked harder and the other used less power and used more coasting before power braking. The team decided to use the program that used less power and speed to conserve energy.
Performance Test 3:
For the third performance test the team had to add to the code used in PT2 to stop at the gate again for 7 seconds and then go to the end of the track and stop between the last 2 posts. The team successfully completed the test with the code shown in the Group G code tab. This performance test was also used to fine tune values in the code for reliability and energy efficiency.
Final Test:
The final test was to run the AEV through the full track, stopping at the gate, waiting, picking up the caboose, then returning to the gate, waiting, then going to the “loading” point with the AEV and caboose. The Code used can be seen in the Group G code tab. The final results with Power Vs. Time can be seen below:
AEV COST ($) Energy(J) Time(seconds) Run ($) Total ($) 
Although the AEV was low cost compared to the average ($150,290 vs. $158,650) the team ended up above the budget by $95,237. This was due to the high energy usage and a time above the median(50.82 seconds). Energy could have been saved by implementing a servo brake instead of power braking and time could have been saved by going faster using higher motor speeds.