# Generic Component-Based Mission-Centric Energy Model for Micro-Scale Unmanned Aerial Vehicles
## 4 Experiments
### Results  
Table 2 shows the results of the polynomial regression-based training of the power functions of the _Motor_ component of the FINken 3 quadcopter. It is visible that all training flights are fitted homogeneously well. The cumulative relative error of each flight is less than 1%. Additionally, the standard deviation of the error for all flights is less than 0.032, which is very small considering the hover energy consumption of the copter (104 \(W\)). Consequently, the used third-order polynomials are valid models for the energy consumption of the _Motor_ component of a FINken copter. Figure 3 shows the measured energy consumption and predicted energy consumption errors of the four different models, see Section 3.5 for the two indoor validation flights which were not included in the training data. The figures show that even for untrained flights, the models predict the consumed energy very accurately with an error of less than 0.6 \(Wh\). The prediction error for the horizontal and the _Combined Model_ are very similar. The _Hover Model_ seems to be too simplistic and ignores the additional energy necessary for moving, as indicated by the generally lesser energy predicted by the _Hover Model_. However, for such a simplistic model the results are still fairly good indicating that the energy consumption of the FINken is strongly governed by the energy necessary for hovering. The _Vertical Model_ shows a sudden jump in the middle of the flight for both validation flights. We assume that these jumps are caused by overfitting of the flights data in case of purely vertical flights. This may be induced because the vertical training flights do not include much horizontal movement. The horizontal flights contain vertical movements automatically, because the thrust needs to be adjusted when the quadcopter pitches or rolls. This induces vertical movement that is not perfectly compensated by the pilot or the autonomous height control of the copter creating data for the fitting of the vertical movement component. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Training** & **Flight 1** & **Flight 2** & **Flight 3** & **Flight 1** & **Flight 2** & **Flight 1** & **Flight 2** & **Flight 1** \\  & **Comb** & **Comb** & **Hover** & **Hover** & **Hover** & **Horiz** & **Horiz** & **Vertical** \\ \hline mean & 0.0462 & 0.0345 & 0.0851 & 0.0095 & 0.0177 & 0.0273 & 0.0705 & 0.0270 \\ std & 0.0322 & 0.0180 & 0.0279 & 0.0055 & 0.0043 & 0.0186 & 0.0176 & 0.0152 \\ \hline
25\%-quantile &  
The error statistics of the indoor validation flights, as shown in Table 3, shows the degradation of the _Vertical Model_ for the validation flights. A relative error of more than 10% disqualifies the model for practical usage. The other three models are very close to an accumulated relative error of 1%. This shows that the models do estimate the consumed energy even for unknown flights very accurately. Figure 3: Estimation results and error of differently trained models tested in two indoor validation flights. The two figures on the top (**a**,**b**) show the measured and predicted energy values for the two indoor validation flights. The two bottom figures (**c**,**d**) show the prediction error of the two indoor validation flights. Comparing the constant hover estimation with the extended movement model trained with horizontal flights shows an increase in estimation accuracy of approximately factor 3. This gain is bought by a more complex model and the need for more training flights to parametrise the model. It also shows the major domination of the energy consumption of a quadcopter by the energy necessary to hover. Consequently, an energy optimisation of swarms of quadcopters should aim to minimise flight time of the individual quadcopters. In the case of a landed copter the resulting energy consumption is still \(\sim\)4 \(W\), which needs to be taken into account for long missions. Table 4 show the results of the additional validation flights done with another copter of same build outdoors.