## 4 Results of Measurements  
Using the measurement set-up shown in Figure 3, the characteristics of the dedicated mobile device charging system were measured. The measurement results were recorded using a PA1000 power analyzer and Rigol DM3058E multimeters, while the results used for further calculations were recorded using a GDS2104 oscilloscope. The oscilloscope software 1.19 version allowed for a Fast Fourier Transform (FFT) analysis of the recorded periodic current and voltage waveforms of the power supply, taking into account 30 consecutive harmonics. The total harmonic distortion coefficient calculations were performed by substituting the RMS values of the individual harmonics in Formula (1). Figures 5-7 illustrate the influence of the SoC level values of the batteries of selected mobile devices on the performance of the EVLONE140W system loaded with the two selected mobile devices, which are hereafter named Smartphone and Notebook. Detailed descriptions of the batteries used in selected mobile devices are presented in Section 3 of the article. The values of the individual operating parameters were measured for the RMS value of the power grid voltage \(\mathrm{V}_{\mathrm{inRMS}}=230\) V. The black line indicates the Smartphone load, while the red line indicates the Notebook load. Figure 5 shows the influence of the SoC level of the batteries of selected mobile devices on the RMS value of the input current \(\mathrm{I_{inRMS}}\) and the value of the output current \(\mathrm{I_{out}}\). Figure 6: Calculated dependence of the current \(\mathrm{THD_{I}}\) and voltage \(\mathrm{THD_{V}}\) coefficient on the SoC level of the batteries. Figure 7: Calculated dependence of energy efficiency and the power factor on the SoC level of the batteries. It can be seen that the RMS value of the input current I\({}_{\text{inRMS}}\) drawn from the power grid adopts an approximately constant value regardless of the change in the SoC level of the mobile device battery, and takes on a value of approximately 0.25 A for Notebook and 0.12 A for Smartphone, respectively. The value of output current I\({}_{\text{out}}\) for both the mobile devices under test increases as the battery's SoC level increases, and then, after exceeding SoC = 50% (Smartphone) and SoC = 70% (Notebook), the value of output current I\({}_{\text{out}}\) decreases to I\({}_{\text{out}}\) = 1.27 A (Notebook) and I\({}_{\text{out}}\) = 0.65 A (Smartphone), respectively. The observed dependence of output current I\({}_{\text{out}}\) for both the mobile devices is qualitatively similar, but quantitatively different due to the lower permissible power that the Smartphone battery can accept, which is only 25 W in the fast charging mode. Figure 6 shows the influence of the SoC level of the batteries of selected mobile devices on the values of THDI and THDV coefficients. The values of both the coefficients were determined using Formula (1), where the individual harmonics were determined using Fast Fourier Transformation (FFT) and a GDS2104 oscilloscope. It can be observed that the highest THDI values were obtained for the current drawn from the power grid (THDI = 95.7%) when the charging system was loaded with Smartphone and its SoC level was equal to 70%. It can also be observed that the THDI value for the tested system loaded with Notebook was a slowly decreasing function of the SoC level of the battery. The changes in the value of THDI were very small. They did not exceed 1% for Smartphone and 3% for Notebook. Slightly smaller THD values were obtained for the power grid voltage. These changed in the range from 88% to 91.5%. The high values of THDI and THDV prove that the tested charging system had an adverse effect on the power grid. This system probably did not include any power factor correction circuit. Figure 7 shows the dependence of energy efficiency \(\eta\) and the PF on the SoC level of the batteries of selected mobile devices. The energy efficiency value was determined using Formula (2), while the PF was determined using Formula (4).