The purpose of the Performance Test 3 (PT 3) lab was to test the chosen Arduino code and Advance Energy Vehicle (AEV) design on the track and make any necessary changes in order for the AEV to complete the scenario listed in the Mission Concept Review (MCR) while being the most energy efficient, consistent vehicle. From the previous performance tests, the team came up with a new braking mechanism for the Arduino code to control the gliding effect of the AEV. For PT 3, the team decided to carry out test runs only on the track that would be used in the final test run, due to the inconsistent track length in the two different lab rooms. The team carried out many test runs under the same code to test for efficiency and consistency of the energy consumed and the success of the runs to determine any other factors that would affect the efficiency of the AEV.
Due to the inconsistent track lengths between the two labs used for the AEV’s performance tests’ runs, the team decided to move forward with PT 3 by carrying out test runs on the track that would be used for the final test run where the team’s AEV would be evaluated. The team programming’s strategy was to continue using the chosen code from the previous performance test, since the code was the only code that allowed the AEV to consistently complete all scenario listed in the MCR while consuming consistent amount of energy. The team decided to not change the amount of power used to move and to brake the AEV at this point, as every changes in power that were done in the previous labs had altered the AEV’s run significantly, and the AEV would not be able complete the scenario in time for the final test run. For PT 3, the team decided to carry out test runs on the shorter track because the data from test runs on the shorter track were consistent.
From the lab, it was observed that the AEV successfully complete the full scenario on the track for the majority of the runs. The AEV appeared stable on the track while travelling on every portion of the track. The AEV managed to stop at the intended locations on the track before continued moving. The AEV also managed to complete the run within the time constraint without encountering major problems such as derailing and falling from the track. After analyzing recorded data from each run, it was found out that the total energy cost of the AEV was optimized, as the pattern of energy increments and total energy consumed by the AEV were similar for all runs, and total energy was minimized by retaining all decisions from the previous performance tests. The team concluded that the AEV had successfully completed the full scenario listed on the MCR, and the AEV would be ready by the time for the final test. See executive summary and lab memo below for further information.