The objectives of the final test run are as follow:
- All performance test 1 and 2 objectives, and
- Return to the gate and remain within the designated zone for 7 seconds
- Go past the gate and return back to the starting zone
The team accomplished the above tasks using the final AEV design. The code used can be found in the Performance Test Code section.
The following plots show the power usage vs. time (s) and power usage vs. distance figures, respectively, of 3 successful performance test 2 runs. Note that they are the exact same as the performance test 1 plots, which also accomplished performance test 2 objectives.
Figure 1: Power vs. Time plot
Figure 2: Power vs. Distance plot
Results:
The team was able to accomplish the above tasks without any accuracy errors in the placement of the AEV, and thus received a perfect score on the accuracy of the run.
With regards to energy usage, the team’s design used 383 J over the whole run, which was about 160 J higher than the class average of 226 J. This large discrepancy suggest some sort of motor malfunction and/or inefficient design and code. However, since the team did not use servo braking and used the minimal energy required to move the AEV, the team suspects that the discrepancy cannot be explained by an inefficient code alone. In addition, while the design isn’t the most aerodynamic and lightweight, there should be no reason why so much more energy is required for the AEV to complete the run, especially during the return trip when pulling the caboose. The team suspects that the phantom power spikes experienced in performance test 2 may have partially resulted in the abnormally high power usage and/or motor inefficiency in the final run.
With regards to the time of run, the team’s AEV took approximately 51 seconds, which was slightly higher than the class average of 48 s.
With regards to the capital cost, the team’s AEV cost approximately $171,000, which is about $10,000 higher than the class average of $158,650.
With regards to the total budget, the team used about $650,000, about $480,000 of which comes from the single performance test run alone. Most of the cost is due to the abnormally high energy usage of 383 J.
The below figure summarizes the team’s AEV project budget (refer to row L) compared to class averages.
Conclusions:
While the team met the desired accuracy and durability qualities in an AEV, the team completely missed out on the efficiency factor of the AEV. The team is unsure whether the power inefficiency is due to design flaws or actual motor problems, but the team highly suspects that the latter is the main cause.
Regardless, one critical error the team made with the design process was the lack of significant analysis into energy usage. The team spent much time ensuring that the AEV traveled the exact distance and stopped at the exact locations, but never spent much time analyzing whether a potential full run with the current design would use too much power. The team also held onto a relatively bulky design (compared with rest of class) due to its success in the early performance tests. When the issues started to compound in later testing, however, the team addressed the problems by brute coding force and repetition of trial-and-error methods. This approach resulted in negligence on the energy efficiency of the team’s design.
In addition, the team should have alerted the instructional team on potential issues and flaws with the provided motors, as most (if not all) other teams were able to move their AEV with the caboose attached with relatively little problem. The team’s design had to use 80% power at the bare minimum to get the AEV to even move with the caboose attached.