Deliverables

Lab 1

In lab 1 we tested the Arduino using some simple code to make sure all of the components work properly as well as making sure we had all of the required materials for the AEV project. There was some friction with the propellers but we worked that out and got them running smoothly. The code we used to test this is below:

// Motor 1
celerate(1,0,15,2.5);
goFor(1);

// Brake motor one.
brake(1);

// Motor 2
celerate(2,0,27,4);
goFor(2.7);

celerate(2,27,15,1);

//Brake motor 2
brake(2);

reverse(2);

celerate(4,0,31,2);

motorSpeed(4,35);

goFor(1);

brake(2);

goFor(3);

brake(1);

goFor(1);

reverse(1);

celerate(1,0,19,2);

motorSpeed(2,35);

motorSpeed(1,19);

goFor(2);

motorSpeed(2,19);

goFor(2);

celerate(4,19,0,3);

brake(4);

Lab 2

The purpose of the second lab was to test the reflectance sensors because they are extremely important in the functionality of the AEV. Their purpose is to track the AEV’s movement. They do this using the reflective tape on the wheels to keep track of how much the system has moved. Obviously speed and distance are key parts of this process, so it’s important to make sure this part of the system is working at 100%.

The code we used to test this:

motorSpeed(4, 25); goFor(2);

motorspeed(4, 20); goToAbsolutePosition(295);

reverse(4);

motorSpeed(4, 30); goFor(1.5);

brake(4);

Lab 2 questions:

1. The AEV was having issues as mentioned in a previous lab with the smoothness of the blades. There was a lot of friction and noise, but unlike the first time we couldn’t resolve it. We should figure out a way to fix this soon because it will cut down the AEV’s efficiency during testing.

Lab 3

See “Evolution of Design” page for lab 3’s AEV diagrams

Lab 4

Code used to collect the data in lab 4:

 

 

 

Performance Test 1

Code from PT1

reverse(4);

motorSpeed(4,60);

goToRelativePosition(-110);

brake(4);

goFor(8);

celerate(4,0,45,4);

goToRelativePosition(-140);

brake(4);

Power vs. Time Graph PT1

Power vs. Distance Graph PT1

 

Results from PT1:

The team had a successful performance test one. On the first trial the team’s AEV tripped the sensor and failed but did not encounter the gate as it only passed the sensor by about a half inch. The second time, a team member manually braked the AEV before the gate to ensure the test could pass. This resulted in a 10% penalty, which is significantly less than not recording the test due to time constraints (30% penalty). The team has since fixed the stopping issue with slightly decreased motor power and more braking. As the Power vs. Time graph for test number one shows in the appendix, the group had not yet utilized coasting at this point in the project. After seeing the nine to fifteen second interval where the AEV was constantly using moderate amounts of energy, they made the decision to use coasting and take advantage of the inclines and declines in the track. 

Prototype A:

Prototype B:

PT2 Code

reverse(4);
motorSpeed(4,60);
goToRelativePosition(-110);
brake(4); goFor(8);
celerate(4,0,45,4);
goToRelativePosition(-140);
brake(4); reverse(4);
goToRelativePosition(-140);
brake(4); goFor(8);
goToRelativePosition(-110);

Power vs. Time PT2

Power vs. Distance PT2

PT2 Results

The group ran two tests for the second performance test. For the first test the team ran the AEV after many tests on the track, and the AEV stopped short of the first sensor. The team attributed this to the battery losing power from many test runs. After replacing the battery, the team ran the same code again, and it worked as planned. The team then ran the second run of performance test two and received full marks. This test was the first test where the group fully utilized coasting. In the appendix the Power vs. Distance graphs for test one and two look drastically different. There is much more down time on the performance test two graph relative to the amount of distance covered. The second test had the AEV covering over double the distance with about 35% more power, which is a large jump in efficiency. The Power vs. Time graph for performance test two shows the large amount of down time because of coasting, something absent in the graph from test one. 

Final Test Code

reverse(4);
motorSpeed(4,62);
goToRelativePosition(-113);
brake(4);
goFor(8);
celerate(4,0,44,4);
goToRelativePosition(-138);
brake(4);
goFor(5);
reverse(4);
celerate(4,0,50,4);
goFor(4);
brake(4);
goFor(1);
reverse(4);
motorSpeed(4,38);
goFor(.5);
brake(4);
goFor(7.4);
reverse(4);
celerate(4,0,43,4);
goFor(4);
brake(4);
goFor(2);
reverse(4);
motorSpeed(4,42);
goFor(1);

Power vs. Time Final Tests

Power vs. Distance Final Tests

Results PTF

The group ran three tests for the final performance test. For the first test the team ran the AEV and it tripped the sensor gate on the way back with the caboose due to the amount of momentum it had. The team then ran another test and manually braked the AEV on the way back with the caboose and completed the run. For the third and final test the team did the same as the second run, which is why these runs’ graphs look identical. As with performance test two the Power vs. Time overlap graph in the appendix shows a large amount of down time due to coasting. The group did have to add a slight power break to decrease the momentum of the caboose at the end of the run. Test one’s graph (blue) is different from the rest because during this run the AEV had to be removed from the track because of failure to stop before the second sensor with the caboose. Test two and three are the lines that are important because they show the coasting used by the team to create a higher level of efficiency. The runs for this also were below average on time at around fifty seconds which contributed to less energy used total. The Power vs. Distance overlap also shows that test one stopped short and confirms that the coasting method is effective, with about half of the run using no power. 

Hardware Cost Information

Total: $156,800