Deliverables

Exercise 2:

The reflectance sensors allow the AEV to keep track of where it is on the track. The sensors measure the revolutions of the wheel by reflecting infrared light off metallic surfaces on the wheel. These sensors are calibrated for the amount of space between each surface on the wheel, which can give distance traveled. Having this data allows for the programmer to design the AEV for the specific scenario.

Exercise 3:

Arduino Code Used for the Data associated with these plots:

reverse(2);
celerate(4,0,35,3);
motorSpeed(4,35);
goFor(1);
motorSpeed(4,30);
goFor(2);
reverse(2);
reverse(1);
motorSpeed(4,25);
goFor(2);
brake(4);

The plots show that the AEV used a significant amount of energy at the beginning of the test due to the acceleration, then remained at its top speed. This would correlate to a lower power draw. The AEV later reversed at around 1.5 m which caused the second large spike in power draw. After hitting the desired speed, the power draw decreased again.

Concept Screening:

Concept Screening
Success Criteria Reference Design 1 Design 2 Design 3 Design 4 Revised Design
Aerodynamic 0  +  +  +  +  +
Reduced Drag 0 0 0 0  +  +
Energy Efficient 0 0 0 0 0  +
Covers Arduino Board 0 0  +  +  +  +
Sum +’s 0 1 2 2 3 4
Sum 0’s 4 3 2 2 1 0
Sum -‘s 0 0 0 0 0 0
Net Score 0 1 2 2 3 4
Continue? Combine No No No Revise Yes

Concept Scoring:

      Concept Scoring:              Reference          Design 1        Design 2
Success Criteria Weight Rating Weighted Score Rating Weighted Score Rating Weighted Score
Aerodynamics 35% 3 0.6 3 0.6 4 0.8
Reduced Drag 25% 2 0.4 3 0.6 3 0.6
Energy Efficient 25% 2 0.4 3 0.6 3 0.6
Covers Arduino Board 15% 1 0.2 1 0.2 4 0.8
Total Score 1.6 2 2.8
Continue? No No Revise
Design 3 Design 4 Revised Design
Rating Weighted Score Rating Weighted Score Rating Weighted Score
3 0.6 4 0.8 5 1.0
2 0.3 4 0.8 4 0.8
3 0.6 4 0.8 5 1.0
4 0.8 3 0.6 5 1.0
2.3 3 3.8
No Revise Yes

All individual designs, (referred to as individual design 1, 2, 3, and 4), have improved aerodynamics in comparison with the reference AEV. Improved aerodynamics will allow the AEV to travel along the monorail system with greater ease. Individual designs 2, 3, and 4 also cover the Arduino and battery. It is necessary for the design to cover the Arduino and battery, not only to reduce drag, but to protect and stabilize the AEV, which was consistently tilted in test runs. Individual designs 2 and 4 were also found to reduce the drag caused by the original AEV setup. Based on the design’s ratings, individual designs 2 and 4 were carried forward to create the team’s revised design. The revised design meets every criterion by increasing the aerodynamics, reducing drag, increasing the energy efficiency of the vehicle, and covering the Arduino board. This is show in the concept screening and concept scoring tables above.

Methodologies: Reflectance Sensor Testing

The reflectance sensor test tested the accuracy of the reflectance sensor distance measurements. This was done using the absolute position command, measuring how far the vehicle actually traveled verses how far the vehicle was programmed to travel, for two separate tests.  The actual distance traveled is measured using the tape ruler built into the monorail track. For the first test, the AEVprogrammed at 0%, will be pulled along the track by hand in five trials. In the first trial the vehicle was pushed 96.00 inches. The measurement on the track is taken from the front of the back wheel. The marks traveled by the AEV is converted to inches using the conversion factor of 0.4875 inches=1 mark. This will be used to calculate percent error. In the second test, the vehicle will still be pulled by hand, but programmed to run 197 marks, approximately 96 inches. The measured distance, in inches, that the AEV travels will be converted to marks. Finally, the difference between the measured marks value and the programmed marks value will be used to calculate percent error. 

Methodologies: SolidWorks Simulations

The SolidWorks simulations tested the team’s prototypes using SolidWorks. Concept scoring was used to choose the best design. The best design was discovered to be our SolidWorks prototyped  design.

Reference the MCR here