Data Analysis Tool:
The Data Analysis Tool enables the team to record and analyze the running data from the Arduino. It allows the team to immediately pinpoint problems and optimize the Arduino program. In Lab 5, two codes, Arduino Code (with no distance traveled) and Lab4 Code (with distance of travelling seen by the team), were tested with data analysis tool.
Results & Analysis:
The change of the AEV power with respect to time is presented below in Figure 1. The code that was used to operate the AEV can be found below here under the Preliminary R&D > Data Analysis Tool.
Figure 1: Power vs. Time for Arduino Code and Data Analysis Tool (Lab 4) Code
During the first 3 seconds, the power of AEV increase from 0% to 25%. From Figure 1, it is obvious that the power stays the same (with fluctuation within a certain amount of range) while the code is running all motors at a constant speed. The power did not change with the direction of the motor, and it goes to zero when the code brakes all motors. The graph of Power vs. Time responded well to the code.
The change of power with respect to distance is presented below in Figure 2. The vertical line on the y-axis shows that the distance stays zero while the power increase with time. The comparison of the Arduino code and Lab4 Code also reflected the problem. At first, the team thought that the problem was due to the reflectance sensor. After readjusting the AEV arm and completing multiple test runs, the team found that the inefficient propellers are the main cause of the problem.
Figure 2: Power vs. Distance for Arduino Code and Data Analysis Tool (Lab 4) Code