The purpose of the Performance Test 2 (PT 2) lab was to develop an Arduino code for the Advance Energy Vehicle (AEV) in order for it to successfully complete the scenario listed in the Mission Concept Review (MCR). Based on the chosen design from Performance Test 1 (PT 1) post-analysis, the code used in PT 1 was modified and improved, as the existing code failed to successfully complete the full scenario from the MCR. According to MCR, the correctly modified code should be able to operate the AEV from the starting (drop-off) point to the gate, and stop the AEV at the first sensor for seven seconds to wait for the gate to open. Then, the AEV should travel to and stop at the cargo area to pick up the cargo. After waiting for five seconds, the vehicle traveled back towards the gate and stop at the sensor, waited for seven seconds, and then returned to the starting point.
The goal of PT 2 was to develop two sets of Arduino codes to successfully operate the AEV according to the MCR so that the efficiency of each run and each code could be compared and analyzed. Previously, the team’s strategy to create an energy efficient AEV was to apply the concept of gliding to stop the AEV. The team expected that by cutting the power of the AEV at some distance before the intended stopping point of the AEV to allow it to glide before halting would cost less power from the motors, and less overall energy would be exerted. However, it was observed that this method proved to be too inconsistent for the AEV on track. Slight variations, including the inconsistencies of the track’s length between two different labs used by the team and the depleted power in the battery after each caused the AEV to stop at different positions on the track on each run. As a solution, the team decided to include a new braking mechanism by utilizing the “reverse()”, “motorSpeed()”, and “goFor()” commands. As it reached the open gate sensor, the propellers’ direction of rotation was reversed and the power motors’ power was decreased to generate a small negative thrust for several seconds before the motors’ power was cut to control the gliding effect. This braking mechanism was then applied every time the AEV was required to stop at the gate, the cargo area, and when it returned back the starting point.
Two different Arduino codes were developed by the team, and the two differed in terms of the value used for the “goToAbsolutePosition()” commands. After further analyzing the energy and power cost of the AEV runs of each code using the MATLAB based design analysis tool, the AEV ran by the second code managed to complete the full-track scenario with a lower total energy cost compared to the first code. The results yielded by the second code were favorable, and the team had chosen the second code to be the most consistent and energy efficient code. See executive summary and lab memo below for further information.