Lab 04-System Analysis 2 and Design Analysis Tool

This lab contained two main aspects to it: analyzing performance data and becoming familiar with the design analysis tool which is MATLAB based. For the first part of the lab, analyzing performance data, the group used the AEV controller to record data as the vehicle ran using Electrically Erasable Programmable Read-Only Memory (EEPROM) on the Arduino. The data collected using this will include the time in milliseconds, the current and voltage supplied to the motors, and the wheel counts from the reflectance sensors. The data collected from the EEPROM was downloaded using MATLAB and converted to physical parameters and performance characteristics like input power, energy consumption, total distance traveled, and the velocity of the AEV. This data will be used by the team to make future design and operational modifications to improve the AEV.

For the second part of the lab, using the design analysis tool, the group will become familiar with and understand how to use the MATLAB based design analysis tool to provide a time efficient method to evaluate the performance of the AEV. The group will need to download the AEV Design Analysis Tool and install onto MATLAB, which will allow the team to use the EEPROM data collected and plot the data collected on MATLAB. This data will help the team know how the vehicle is performing. The cycle of analyzing data, making design decisions from the analyzed data, researching design decisions, and testing the new designs will be used throughout the duration of the lab until a final AEV design is reached.

The team started the lab by coding a program on the Arduino software for the AEV to run on the outside track. The code the team decided to use incorporated much of what was learned in Lab 01 and Lab 02, incorporating basic function calls as well as sensor function calls. The attached code is in the Appendix. When the team uploaded the program onto the Arduino nano microprocessor and tested the AEV on the track, the team found that the AEV would not start to move, even as the motor speed was increased from 20% to 30%. After multiple attempts to troubleshoot, with the team even removing the propellers already installed and adding new propellers, the team found that the mass distribution of the AEV was not even throughout the AEV structure, and somehow the wheels were stuck to such an extent that the wheels on the AEV would not spin. This was discovered after the team called over a TA to inspect our AEV, who then notified us that the wheels were not moving to its full capacity.

However, even after this issue was fixed and the AEV was seen to move on the outside track, another issue had arisen due to the reflective sensors. The code related to the reflectance sensors, which called for the AEV to move to a certain position (i.e. the code goToAbsolutePosition(XXX)) did not cause the AEV to stop once the AEV reached the location specified, even as the value was decreased. The team also  tried uploading different versions of code onto the Arduino microprocessor by decreasing the value of the goToAbsolutePosition as well as adding brake commands. Each time the code was compiled and uploaded, the team found that the AEV motors would keep running, even though there had been multiple troubleshooting attempts to make them stop.

The team found that the reflective sensors were not correctly detecting the movement of the AEV after performing a reflective sensor test. The reflective sensors were not working for the time, and so the team could not complete the AEV test run that was required of Lab 04a and use that data for the EEPROM time, current, voltage and marks and convert that data into the physical parameters time, current, voltage, distance and position.  As a result, the team could also not calculate power, incremental energy and plot the data received in the performance analysis to create a plot of power vs. time and analyze that plot. However, after completing Lab 04b, the team was able to take the data from the AEV test run (albeit unsuccessful) and make plots for power vs. time and power vs. distance.

In Lab 04b, the team downloaded the AEV Design Analysis Tool and opened up the ‘AEV Analysis’ app under my apps in MATLAB. This opened up a graph which allowed the group to plot Power vs. Time and Power vs. Distance. The data for the AEV run was uploaded  from the Arduino microprocessor for the test run onto the computer. The AEV run was unsuccessful due to the fact that the reflective sensors did not function correctly, and so the Arduino program would keep running the motors as it would never ‘reach’ the point where the goToAbsolutePosition was met. The code that was stored and used for the graph can be seen in the Appendix (note: the absolute position used in the graph was 500, whereas the correct code the team figured out was meant to be 463, which was uploaded in the Appendix for future lab use). The graphs are shown below.


Team Meeting Notes

Meeting 4

Date:  11-Feb-2017

Time:  12:00-2:00 PM

Location: Hitchcock Hall, Room 324

Members Present: Omar Mahboob, Xander Riggio, Matthew Spishakoff (Eric Fogle worked online)

Method: Face to Face

Meeting Objectives: Work on Week 4 Progress Report, Discuss future plans

Roles for Meeting 4:

O Eric: Forwards Looking Plan and Project Portfolio

o Omar: Data Graphing, Results and Analysis

o Xander: Arduino Code, Week 4 Reflections, Proofreading and Final Submission

o Matthew: Team Meeting Notes, Week 4 Situation

 

Tasks Completed in Previous Meeting:

o Eric: Week 4 Situation, Weekly Goals, Weekly Schedule, Finalizing Project Portfolio

o Omar: Week 3 Takeaways, Team Meeting Notes.

o Xander: Arduino code, Re-submitting Progress Report 1, Proofreading and Final Submission

o Matthew:  Week 3 Situation, Results and Analysis