## 3 Results
### Real Flight Experiments  
The in-flight experiments (Figure 25) were divided into two stages:  
1. VTOL (quadcopter) mode flights and onboard systems check: stabilize mode, hover, GPS position hold mode, GPS return-to-land mode, smooth auto-landing using the laser rangefinder, and low-speed forward flight with the pusher motor. 2. In-flight mode transition test and plane mode performance analysis. The first stage of test flights went without any serious issues. We discovered some instability in the onboard barometer readings--most likely due to pressure changes inside the fuselage caused by wind gusts. The barometer is not crucial for the flights; GPS provides a redundant coarse altitude value. The laser rangefinder provides precise and accurate low altitude readings necessary for the auto-landing feature. The drone behaves correctly in hover, responds sharply to pilot commands, and proved to be quite resistant to wind gusts. Crosswind gusts induced some mild roll oscillations due to the presence of wing surfaces. Low-speed horizontal flight using the pusher motor did not reveal any stability issues. The drone maintained its attitude correctly. The second stage of test flights revealed a few issues, some severe enough to lead to a few crash landings eventually. Figure 26 shows a telemetry log from an experimental flight when at about the 120 th second, the mode was changed from quadcopter to Elka1Q. The drone dived rapidly. Immediate manual intervention (switching back to the quadcopter mode) rescued the drone while it still stayed airborne. The situation repeated in a few other attempts, sometimes flipping the drone by 180\({}^{\circ}\) (a half-loop). We concluded that the drone could have misplaced its CG. The eCalc CG tool states that the calculation results should be carefully examined in test flights due to numerous limitations, including, but not limited to \"fat\" fuselage effects and aerodynamic performance analysis. The overall static and dynamic plane stability will also depend on the control surface effectiveness and the attitude controller robustness. Eventually, we fixed that issue by moving the CG by ca. 10 mm forward. Figure 24: The drone locked in a limited-freedom test harness. Further flights showed that the pitch controller still is not always stable enough--in some flights, after accelerating the drone and switching it to plane mode, the drone became extremely pitch-unstable (Figure 27). Fast horizontal flights in quadcopter mode (using the pusher motor to accelerate) also revealed some pitch instability (oscillations in Figure 28 starting from the 111 th second). Figure 29 presents power usage in quadcopter mode (<55 s), during the transition phase (55-65 s; the drone accelerates with pusher motor; quadcopter motors still work) and plane mode (>65 s; only pusher motor works; other motors were shut down). It is worth mentioning that the electric power needed during the hover phase and the level flight in plane mode is nearly identical (total current drawn from the battery was ca. 20 A). The key difference is related to the horizontal speed of the drone in plane mode (above 100 km/h), while any non-zero forward flight speed in quadcopter mode requires more power than in hover. The eCalc predicts (see Figures 5 and 6) that in quadcopter mode,  
Figure 26: Telemetry log from an in-flight experiment: a sudden pitch down (a dive) after the transition into plane mode because of misplaced CG—eventually rescued thanks to an immediate switch back to quadcopter mode. Figure 25: Flight experiments. the practical maximum speed will be less than 35 km/h at maximum main motor power (current readings over 60 A!). That proves the plane mode's efficiency--the drone can fly 3\(\times\) faster while consuming 3\(\times\) less electric energy! Due to safety reasons, we performed the top speed test only partially. Figure 30 shows that we measured ca. 105 km/h top speed in a level flight.