# A Smart Approach to Electric Vehicle Optimization via IoT-Enabled Recommender Systems
## 4 Numerical Results and Discussion
### Discussion
\begin{table}
\begin{tabular}{c c c c c c} \hline \multirow{2}{*}{**Parameters**} & **Boost** & **Buck-Boost** & **Interleaved Boost** & **Fly Back** & **Proposed** \\  & **Converter**[31] & **Approach**[32] & **Converter**[12] & **Approach**[37] & **Model** \\ \hline Input voltage (V) & 25 & 25 & 25 & 25 & 25 \\ \hline No. of phases & 1 & 6 & 2 & 6 & 6 \\ \hline Switching frequency (kHz) & 25 & 25 & 25 & 25 & 25 \\ \hline Duty cycle & 0.6 & 0.6 & 0.6 & 0.7 & 0.6 \\ Output voltage (V) & 200 & 208 & 205 & 213.5 & 500 \\ \hline Output power (W) & 450 & 453 & 460 & 487.6 & 343 \\ \hline \% Efficiency & 95 & 96 & 96 & 97 & 99 \\ \hline \end{tabular}
\end{table} 
Table 7: Comparison of existing with proposed approaches. Figure 6: Speed vs. Efficiency graph. Figure 8 shows the packet delivery ratio (PDR) of the system versus total messages. It can be seen that the PDR is better at a higher transmission rate. Figure 9 shows that the throughput increases with respect to the number of EVs. The proposed methodology is consistently superior to traditional and standard DVMRP methods in terms of PDR. This shows that the proposed method is more effective in providing packet delivery under different kinds of network challenges, resulting in improved communication reliability. In comparison to standard and conventional DVMRP protocols, the suggested model first shows a greater E2E latency when sending 500 packets. Due to the additional processing and control overhead of the improved features in the proposed model, there has been an increase in delay. However, the suggested model performs better in terms of delays as network conditions change. The proposed approach gradually beats conventional methods in other circumstances, proving its capacity for better routing and minimization of latency over time. Figure 8: Packet Delivery Ratio (PDR) comparison. Figure 7: Efficiency due to transferring charge. Figure 10 shows the end-to-end delay of the proposed and existing systems. It can be seen that although the delay increases with the total number of packets, the proposed system offers the lowest delay. Finally, Figure 11 compares the anticipated efficiencies of the buck-boost, fly back and proposed models where the proposed system promises the highest efficiency. Under certain situations, the proposed Enhanced DVMRP protocol might have higher delays initially; however, in in the long term, it offers more effective PDR and efficiency performance. As the system becomes stable, it also achieves reduced delays in different kinds of situations, showing its effectiveness in maximizing network efficiency and communication. The proposed model not only enhances operating efficiency but also helps to reduce the total carbon footprint. This technique helps in reducing the amount of energy required for charging and operation by optimizing energy consumption and enhancing power transfer efficiency. This reduction in energy use directly results in a lower carbon footprint, especially when the electric power used for charging is obtained from renewable sources. Figure 10: End-to-end (E2E) delay comparison. Figure 9: Throughput comparison.