A-Nicholas Brendle, Lars Kristenson, and Brayden Skall Progress Report 1
Instructor – Professor Busick, GTA – Benjamin Richetti 13 February 2019
Report of Progress:
Lab 1:
Situation:
Using the Arduino, Battery and two motors connected to a stationary base, each group member practiced with the programming software by writing the code (A.1) to perform scenario one in exercise one. One each member completed their code, each member uploaded their code to the Arduino and ran it.
Results and Analysis:
Each group member observed the fans while their program ran. It was determined that everyone’s programs worked as intended by counting out seconds and observing changes in fan speed or reversals of the fans direction. This setup did not have wheels and reflectance sensors attached so we did not have any data outside of observations.
Takeaways:
Having each group member write and test their code ensures that everyone will be capable of using the software to program the AEV in the future. This also allowed us to observe how the different commands cause the hardware to function. While there was a slight delay in the Arduino’s execution of the code, the propeller rotated at the start with zero resistance. This was observed qualitatively by noticing the rapid movement of the propellers and the little to no movement of the AEV.
Lab 2:
Situation:
The group was given the AEV Kit and required to take inventory of the kit. Inventory was recorded using a checklist and any extra or needed parts were dealt with. Other paperwork also needed to be done with the kit including the label sheet and the team working agreement. While this was being completed, the sample AEV design was built. Along with these steps, code (A.2) was also being written to perform the scenario in exercise two. Once the AEV was built, the reflectance sensor test was performed to verify correct placement of the sensors as shown in (B.1). The reflectance sensor is directly attached to the AEV to record the position of the vehicle. This is done by the sensor recording its passage over a non-reflective surface, thus sending the amount of revolutions to the controller and registering as a mark, or 0.4875 inches. To ensure the accurate measurement of data, the sensor should be applied as close to the wheels as possible – a feature that ensures the movement of the vehicle. The group never got the chance to test the code due to issues with completing the reflectance sensor test.
Results and Analysis:
All of the paperwork was completed and the group ended up getting all of the proper parts. While the code was written properly, it was never tested due to a widespread issue that occurred with performing the reflectance sensor test. The issue was eventually resolved and the sensors were verified to be working properly.
Takeaways:
Although the code was not able to be tested that day, the group gained experience in properly testing the reflectance sensors so tasks could be completed more quickly in future labs. The paperwork that was completed will also help with the safekeeping of the AEV parts outside of the classroom. Some limitations were also discovered with the code in this lab. Users should thoroughly understand the function calls used to program the AEV. When the brake command is initialized, this does NOT stop the AEV immediately as it only stops the motor from running. Since the propeller will continue to run for a short amount of time due to lingering kinetic energy, engineers should factor it into the decision-making progress.
Lab 3:
Situation:
Code (A.3) was uploaded to the AEV, while a sensor test was being run. Once complete, the AEV was put on the monorails, and the code was run. The wrong propellers were put on, causing the AEV to not function as planned. By the time the correct ones were put on, time had run out. The reason for the two actions being completed was, so that the AEV’s data could be graphed, so that the members of Group A could be exposed to the data analysis tool on MATLAB.
Results and Analysis:
Once the sensor test was complete and the AEV was ready to be put on the track, it executed the code properly, and functioned as it should have. The problem was, that the AEV did not move vary far, and as a result, the wheels did not turn much. The problem is that the MATLAB data analysis tool relies heavily on the distance traveled. Therefore, the data collected was deemed worthless and was not uploaded. Finally, through observations, the small propeller props do not produce enough thrust to move the AEV at power levels around 25%.
Takeaways:
Although the smaller propellers weigh less, they decrease the level of efficiency because they do not produce large enough amounts of thrust to justify their minor weight reduction.
Lab 4:
Situation:
Code (A.3) was uploaded and completed. A sensor test was run. The AEV was put on the monorail and the code was executed. The data that the AEV collected was then uploaded and graphs (C.1, C.2) were made. Finally, design four (D.4) was decided upon and build by the group because of its score in the criteria of aerodynamics, mass, balance, area used, and a minimal amount of parts used (C.3).
Results and Analysis:
The correct propellers were used, and the AEV moved considerably more compared to when the same code was run during lab 3. Because of that, the data was worth keeping and was graphed. All the AEV’s (D.1-4) were compared by aesthetics because there was no data to back up any one design. The first design (D.1) received a score of 27, but the group member had a created part in it and was not considered. Design two (D.2) received a score of 25, design three received a score of 22, and design four (D.4) received a score of 26. Design four was the design that was then agreed upon by the group.
Takeaways:
- The larger prop works better than the smaller prop as observed by the group, and not supported by data.
- Design four was essentially the most minimalist design and therefore was though to be the most efficient of the four and is supported by the composite score given to it.
- Aerodynamics does not matter because the AEV’s are not traveling at high enough speeds.
- Mass and balance are of highest precedent because they presumably have the largest effect on the efficiency of a design and is not supported by data.
Future Work:
Situation:
Design four is going to be built and tested using the same commands as the sample AEV in order to see if there are any differences in efficiency among the two. Also, another design should be made, so that research can be conducted without changing too many of the parts, in order to reduce the amount of variables.
Upcoming Goals:
Determine the appropriate amount of motors that will maximize efficiency and analyze the effect that the placement of motors has on the efficiency of the AEV.
Upcoming schedule:
During lab 5, Nicholas will run the sensor test, and the data analysis tool. Lars, will construct the AEV in different ways in order to test the effect that the amount of motors and the placement of motors has on the efficiency. Brayden will write the code and upload it to the AEV and help Lars to construct different designs.
During lab 6, group A will discuss the results of the data that Nicholas will compile and organize prior to coming to lab. Then they will apply the information gathered to their AEV design and make minor adjustments as they see fit.
Appendix A: Codes used
A.1
// Accelerates motor one from start to 15% power in 2.5 seconds.
celerate(1,0,15,2.5);
// Run motor one at a constant speed (15% power) for 1 second
goFor(1);
// Brake motor one
brake(1);
// Accelerate motor two from start to 27% power in 4 seconds.
celerate(2,0,27,4);
//Motor two at constant speed (27% power) for 2.7 seconds.
goFor(2.7);
// Decelerate motor two to 15% power in 1 second.
celerate(2,27,15,1);
// Brakes motor two.
brake(2);
// Reverses direction of motor two.
reverse(2);
// Accelerates all motors from start to 31% power in 2 seconds.
celerate(4,0,31,2);
// Goes for 1 seconds.
goFor(1);
// Brakes motor two.
brake(2);
// Motor one keeps running at a constant speed (35% power) for 3 seconds.
goFor(3);
// Brakes motor one.
brake(1);
// Reverses motor one.
reverse(1);
// Accelerates motor one from start to 19% power in 2 seconds.
celerate(1,0,19,2);
// Motor two goes to 35% power.
motorSpeed(2,35);
// Motor one goes to 19% power.
motorSpeed(1,19);
// Goes for 2 seconds.
goFor(2);
// Motor one goes to 19% power.
motorSpeed(1,19);
// Goes for 2 seconds.
goFor(2);
// Decelerates all motors from 19% power to 0% in 3 seconds.
celerate(4,19,0,3);
// Brakes all motors.
brake(4);
A.2
// Run all motors at a constant speed (25% power) for 2 seconds.
motorSpeed(4,25);
goFor(2);
// Run all motors at a constant speed (20% power) and travel a distance of 12 ft. from the starting point.
motorSpeed(4,20);
goToAbsolutePosition(295);
// Reverse all motors
reverse(4);
// Run all motors at a constant speed (30% power) for 1.5 seconds.
motorSpeed(4,30);
goFor(1.5);
// Brake all motors.
brake(4);
A.3
// Reverse all motors
reverse(4);
// Accelerate all motors from start to 25% in 3 seconds.
celerate(4,0,25,3);
// Run all motors at constant speed (25%) for 1 second.
goFor(1);
// Run all motors at 20% power for 2 seconds.
motorSpeed(4,20);
goFor(2);
// Reverse all motors
reverse(4);
// Run all motors at constant speed (25%) for 2 seconds.
motorSpeed(4,25);
goFor(2);
// Brake all motors.
brake(4);
Appendix B: Pictures
B.1
Appendix C: Graphs and Charts
C.1
C.2
C.3
Lars’ Design | Sean’s design | Nicholas’ Design | Brayden’s Design | Base Design | |||||||
Success Criteria | Weight | Rating | Weighted Score | Rating | Weighted Score | Rating | Weighted Score | Rating | Weighted Score | Rating | Weighted Score |
Aerodynamics | 10% | 3 | 0.3 | 6 | 0.6 | 4 | 0.4 | 7 | 0.7 | 5 | 0.5 |
Mass | 30% | 5 | 1.5 | 7 | 2.1 | 4 | 1.2 | 4 | 1.2 | 5 | 1.5 |
Minimize the Parts Used | 20% | 4 | 0.8 | 4 | 0.8 | 4 | 0.8 | 3 | 0.6 | 5 | 1.0 |
Balance | 25% | 9 | 2.25 | 4 | 1.0 | 7 | 1.75 | 6 | 1.5 | 5 | 2.75 |
Area used | 15% | 6 | 0.9 | 4 | 0.6 | 3 | 0.45 | 6 | 0.9 | 5 | .75 |
Total | 27 | 25 | 22 | 26 | 25 |
Appendix D: Designs of AEV
D.1 D.2
D.3 D.4