## 3 Simulation Results  
Figure 10 shows the results of the simulation for the buck DC-DC converter controlled through the P&O algorithm without a fuzzy logic controller. Figure 11 shows the results of the simulation for the buck DC-DC converter controlled through the P&O algorithm with a fuzzy logic controller. Figure 10: Simulation results for the DC-DC converter controlled through the P&O algorithm without a fuzzy logic controller. The analysis of the power variation diagrams produced by the photovoltaic panels in the case of the two models provides the following values in function of the intensity of the incident solar radiation and ambient temperature, as shown in Table 2.  
From the results of the analysis, it may be seen that better results were obtained in the case of the DC-DC converter controlled through the P&O algorithm with a fuzzy logic controller. Thus, the hypothesis as per Ref. [22], stating that a high efficiency will be obtained on photovoltaic systems when they are controlled through the MPPT intelligent hybrid algorithm, was confirmed. 4 Construction of the DC-DC Buck-Type Converter Controlled through the Development Board Arduino Uno  
The DC-DC buck-type converter, controlled through the Perturb and Observe algorithm (P&O) with the help of the development board Arduino Uno, was built at the Laboratory of Electrical Machinery and Drives of the Engineering Faculty in Bacau. Its electric diagram is shown in Figure 12. To control the buck DC-DC converter through the MPPT (P&O) algorithm with a fuzzy logic controller, the development board Compact Rio was used, and the related results will be presented in another work. This work presents the experimental results obtained through the implementation of the MPPT-P&O algorithm by means of a program issued in the Arduino-IDE programming environment. The experimental results were then compared to the results obtained through simulation. Further to the related analysis, the following conclusions can be made. The components of the buck-type converter such as power transistor, inductance L, condenser C etc. have been well-established. As such, the buck-type DC-DC converter being designed may be used within photovoltaic systems, be it to control the charging of the accumulator batteries or to control the supply with the electricity of various consumers. A picture of the DC-DC converter is shown in Figure 13.  
The current encoder presented in Figure 14 has the following characteristics. The supply pins GND and V\({}_{\text{cc}}\) of the sensor are connected to the corresponding Arduino pins. The pin Out is connected to the analog pin A0. The sensor will be connected in series to the circuit whose current intensity needs to be measured. The current can be calculated with the help of a certain formula that is presented below. The analog-digital converter will supply the value VAL that is equal to:  
\[\text{VAL}=\frac{1024}{\text{V}_{\text{CC}}}*\text{V}_{\text{in}}, \tag{11}\]  
where \(V_{in}=\frac{V_{\text{cc}}}{2}+\text{S}*\text{I}\),  
S is the sensibility, which is 0.1 A/V for the sensor ASC712-20A,  
\[\text{VAL}=\frac{1024}{\text{V}_{\text{CC}}}*\left(\frac{V_{cc}}{2}+\text{S}* \text{I}\right)\quad=>\quad\text{VAL}=\frac{1024}{5}*\left(\frac{5}{2}+0.1* \text{I}\right), \tag{12}\]  
where I = 0.0488 * (VAL-512). \begin{table}
\begin{tabular}{l c c c c} \hline \hline Solar radiation variation (W/m\({}^{2}\)) & 1000 & 700 & 1000 & 1000 \\ \hline Temperature variation (\({}^{\circ}\)C) & 25 & 25 & 40 & 50 \\ \hline P\({}_{pv}\) power variation for the P\&O model (Kw) & 0.38 & 0.08 & 0.35 & 0.33 \\ \hline P\({}_{pv}\) power variation for the P\&O with fuzzy logic controller (Kw) & 0.47 & 0.25 & 0.45 & 0.43 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Results obtained through the simulation. Figure 12: Electrical diagram of the buck-type DC-DC converter. Figure 13: Picture of the buck-type DC-DC converter.