**4.2 System mass distribution analysis**

As mentioned in the previous sections, the weight (mass) of the aircraft plays an important role as it will directly affect the maximum payload of the aircraft. In order to be able to accurately determine the payload of an aircraft, the weight of all aircraft components/subsystems has to be known. Taking into account the choice of propulsion components, and the configuration of the aircraft, the choice of the energy subsystem will greatly affect the carrying capacity of the aircraft. **Figure 12** graphically

*Autonomous Aerial Robotic System for Smart Spraying Tasks: Potentials and Limitations DOI: http://dx.doi.org/10.5772/intechopen.103968*

**Figure 12.** *System mass distribution for three conventional configurations.*

shows the dependence of the mass distribution of the aircraft subsystems in the case of three conventional aircraft configurations and various battery capacities. It can be seen that the mass of the avionics (control) subsystem can be considered fixed since the components that make up the control subsystem do not change in relation to the changes of other subsystems. The mass of the propulsion subsystem varies with the number of EPUs required to perform certain missions and significantly affects the total mass of the system. In terms of energy consumption, more units will require more energy, which means that more batteries will be needed, and the mass of the batteries, i.e., the mass of the energy subsystem, has the greatest impact on the total mass. All this affects the maximum payload of the aircraft. A larger number of EPUs will generally provide higher thrust and a higher payload mass, although they will also require a heavier energy subsystem with the ability to deliver more energy. The process of designing a multirotor aircraft is extremely demanding, especially given the limitations that exist in the size of the aircraft, but also energy consumption (**Figure 12**).

Although a change in battery capacity will not change the overall thrust generated by the propulsion subsystem, it will affect the overall mass of the system and thus the payload of the aircraft and the flight time. The higher-capacity batteries have an expected higher mass, thus leaving less space for payload mass and requiring higher energy consumption to compensate for heavier aircraft. Thus, a higher-capacity battery does not always result in a longer flight time.

Since the system is divided into four key subsystems, as mentioned earlier, a certain degree of modularity is allowed. In the further work, special attention will be paid in the design phase to the construction of modular elements, which would allow easy assembly of aircraft configurations with different numbers of rotor arms, thus further expanding the diversity of the system and potentially reducing energy consumption. In this sense, the guidelines presented in the previous work [47] regarding the small educational aircraft will be used.

#### **4.3 Simulation results**

In the use of UAV for spraying or similar tasks such as fertilization or even seed sowing, the payload capacity is specific. As the aircraft tank is filled with the required chemicals (either fertilizer or seed) and depleted during usage, the weight (mass) of the aircraft will also continuously decrease. In order to efficiently conduct the spraying task with low energy and time losses, the flight path needs to be planned with regard to the tank size and the chemical consumption rate. The rate of chemical consumption is also not fixed for the whole parcel but depends on the crop health condition estimated based on sensor readings. Flight planning is an extremely complex process that includes many parameters, which will be the subject of future research.

To determine the energy consumption of the aircraft during the spraying mission and to approximately determine the required flight time, it is necessary to conduct computer simulations in the development phase of the prototype. In this way, the development time and the price of the product can be significantly shortened, as the possibility of incorrect selection of system components and parameters is reduced. Preliminary simulations are presented in this paper, where typical spraying parameters are taken: nozzle spraying rate of 0.375 L/min, spray width of 5 m, and flying speed of 2 m/s. The aircraft is equipped with a spraying tank of 25 L volume, and four spraying nozzles, which gives a total spraying rate of 1.5 L/min. Based on those specifications, a minimum flight time of 16.5 min is required to deplete the whole tank, and in that time area of approximately 10000 m<sup>2</sup> can be covered. The aircraft parameters (mass and inertia) were obtained based on a simplified 3D CAD model. **Figure 13** shows the most elementary case when the mission consists of uniform spraying of the crop. Air resistance or any disturbances are not included in the simulations, this is planned in the next phases of the research.

Based on the planned flight consisting of take-off, horizontal flight in the pattern, and landing, the angular velocities of individual EPUs or direct control signals (PWM) can be extracted from the model, as shown in **Figure 14**. As mentioned, with the consumption of the chemical, the mass of the aircraft is reduced, which results in fewer forces and moments of the propulsion subsystem required for motion in 3D space, which can be seen in the figure where the control signals are continuously reduced. The main goal of the simulation is to determine the energy consumption of the aircraft by approximating the individual energy consumption of each EPU, which can be determined if the flight pattern and the change in aircraft mass are known. Since

**Figure 13.** *An example of the aircraft trajectory in a spraying mission.*

*Autonomous Aerial Robotic System for Smart Spraying Tasks: Potentials and Limitations DOI: http://dx.doi.org/10.5772/intechopen.103968*

**Figure 14.** *Motor control signals related to given spraying mission.*

there are characteristics of propulsion units, it is easy to connect electrical quantities (electric current, voltage, and electric power) with the control signal or the angular velocity of the rotor. This can further allow the selection of optimal system components and parameters, which is extremely important in the system design phase.
