## 6 Simulation Results and Analysis
### The Recharging Efficiency under Different Kinds of Network Partition  
In AEBDC, the \"recharging efficiency\" is defined as the ratio between the total amount of energy recharged for nodes in a round of recharging and the battery capacity of WCV. From Figure 12, it is not difficult to see that no matter what the value of \(n\) and \(k\) is, the recharging efficiency of WCV in each annulus is relatively high except for the last one or two rounds. For example, in the case of \(k=3\) and \(n=8\), the recharging efficiency of WCV in the innermost annulus is still higher than 90% during the first three recharging cycles. In this case, the energy consumption rates of nodes in each RCCH are basically stable, so the most appropriate recharging request thresholds of them can be accurately calculated out by Equations (31)-(34). Furthermore, according to Equations (37), (39) and (40), the total amount of energy recharged for nodes in each RCCH during a round of recharging can also be calculated. Therefore, the energy that the WCV carries before each recharging is made full use of.  
It can also be found from Figure 12 that the closer the WCV is to the center of the network, the higher recharging efficiency it has, regardless of the network partition modes. In this case, the moving path of the WCV is shorter than those of the other annuluses, so the energy consumption on moving is lower. Furthermore, the RCCHs that close to the center of the network consume more energy, so the amount of energy recharged for nodes is also slightly higher. It can also be found in this figure that, the recharging efficiency of the last two rounds decreases greatly. As mentioned before, in AEBDC, the moment when the first dead node appears in the outermost annulus is regarded as the end of the network lifetime. Therefore, in order to avoid energy waste, all nodes are do not need to be fully recharged in the last one or two rounds. The detailed recharging strategy has been described in Section 5.4.  
It should be pointed out that we try to make the values of the various parameters in this paper as close as possible to that in the real scene. As is known to all, the development of current wireless recharging technology is still at an initial stage and the recharging rate is relatively slow. Therefore, there are not many recharging cycles during the simulation process.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & & \(k=3\), \(n=8\) & \(k=4\), \(n=5\) & \(k=5\), \(n=4\) \\ \hline \multirow{3}{*}{Average Energy Consumption of Nodes in the RCCH} & of the First Annulus & 0.0037 & 0.0040 & 0.0051 \\  & of the Second Annulus & 0.0045 & 0.0040 & 0.0049 \\ \cline{1-1}  & of the Third Annulus & 0.0030 & 0.0037 & 0.0047 \\ \cline{1-1}  & of the Fourth Annulus & - & 0.0035 & 0.0049 \\ \cline{1-1}  & of the Fifth Annulus & - & - & 0.0050 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Average energy consumption of nodes in the RCCH under different values of \(k\).  
Table 7 shows the total recharging efficiency and WCV's energy distribution under the three kinds of network partition modes. It can be seen that when \(k=3\) and \(n=8\), the total recharging efficiency of WCV is the highest, while in other two cases, there is little difference between the total recharging efficiency.