The AEV is nearing the final stretch of completion for the purposes of this project. The focus is now on optimizing and finalizing various parts of the AEV. The AEV ran on the track a couple more times until a successful outcome was achieved. The AEV recorded data along this run, such as energy consumption and time. The data was then gathered from that run to gain more insight on how to improve the AEV.
Figure 1: Power vs. Time without phases.
Figure 2: Power vs. Time with phases.
| Phase | Arduino Code | Time(seconds) | Total Energy(Joules) |
| 1 | celerate(4,0,24,2) | 8.64 | 43.84 |
| 2 | celerate(4,0,30,2) | 7.80 | 41.91 |
| 3 | motorSpeed(4,16) | 4.08 | 15.02 |
| 4 | celerate(4,0,flat,3) | 5.88 | 43.28 |
| 5 | goToAbsolutePosition(s2) | 6.90 | 34.83 |
| 6 | celerate(4,0,36,3) | 12.18 | 99.11 |
| 7 | celerate(4,0,flat,2) | 9.18 | 34.14 |
| 8 | celerate(4,0,22,2) | 7.98 | 44.58 |
| 9 | celerate(4,0,flat,2) | 20.16 | 243.60 |
| 10 | motorSpeed(4,21) | 9.48 | 32.55 |
| Total Energy Used: | 632.57 |
Table 1: Time used and total energy of three phases.
As shown in Figure 2, the greatest power output occurred in phase 6. The function used during phase 6 was the celerate command, the AEV was set to accelerate to 36% speed in 3 seconds, however the entire process took more than 3 seconds. Table 1 shows the energy used in phase 6 was relatively greater than others. When the motorSpeed command was used in phase 3, the AEV had the least power output. Phase 9 was the greatest power output and longest time phase. The AEV was accelerated to the sped of the flat variable. The cart was picked up after phase 3. As shown in Table 1, the energy used as AEV went down from the incline in phase 4 was similar with when AEV was climbing up the incline. The battery was not fully charged when the data was taken, things would vary and might need to be changed to ensure the performance in the future that depends on the battery percentage. The most amount of power was used in phase 6, which was the stop on the incline. After multiple runs the battery would quickly drain, changing the performance of the AEV. In order to fix this the AEV was charged between trials, which led to more consistent results.