## 4 Simulation Process and Results of Train Energy-Saving Optimization
### Analysis of Simulation Results
#### 4.3.2 Energy-Saving Performance Evaluation  
The running curve of the final running strategy is shown in Figure 7. The simulated high-speed train reaches the speed limit when it goes from the starting point to more than 20,000 m, continues to cruise to more than 70,000 m at a speed close to the speed limit, and then begins to slow down. Compared with the original real running curve, the optimized traction control makes the change in speed smoother and ensures that the train runs within the speed limit range, which ensures safety. Based on the original manual driving data, the time error of two minutes is acceptable. The line data after the implementation of the strategy are shown in Table 9.  
In the table, the running time of the optimized driving scheme obtained in this study is 1 min 24 s faster than that of the original scheme. This can be explained by the fact that the strategy in this study achieves the punctuality and accurate parking of trains on the basis of safe driving, which are the preconditions for verifying energy saving.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline  & **OC** & **REL** & **1A** & **1B** & **2** & **3** & **4** & **5** & **6** & **7** & **8** \\ \hline VGAE & 0.008 & 0.96 & 0.17 & 0.39 & 0.63 & 0.95 & 0.24 & 0.65 & 0 & 0.09 & 0 \\ NBM & 0.01 & 0.98 & 0.54 & 0.31 & 1 & 0.33 & 0.23 & 1 & 0 & 0.08 & 0 \\ BP & 0.005 & 0.95 & 0 & 0.46 & 0.4 & 0.92 & 0.95 & 0.45 & 0 & 0.05 & 0 \\ \hline \end{tabular}
\end{table}
Table 6: Comparison of \(P_{i}\) calculation results.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline  & **OC** & **REL** & **1A** & **1B** & **2** & **3** & **4** & **5** & **6** & **7** & **8** \\ \hline VGAE & 0.5 & 0.88 & 0.15 & 0.34 & 0.15 & 0.6 & 0.53 & 0.25 & 0 & 0.39 & 0 \\ NBM & 0.5 & 0.86 & 0.28 & 0.53 & 0.22 & 0.33 & 0.8 & 0.17 & 0 & 0.29 & 0 \\ BP & 1 & 0.69 & 0 & 0.49 & 0.04 & 0.4 & 0.5 & 0.87 & 0 & 0.43 & 0 \\ \hline \end{tabular}
\end{table}
Table 7: Comparison of \(R_{i}\) calculation results.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline  & **OC** & **REL** & **1A** & **1B** & **2** & **3** & **4** & **5** & **6** & **7** & **8** \\ \hline VGAE & 0.01 & 0.92 & 0.16 & 0.36 & 0.24 & 0.74 & 0.33 & 0.36 & 0 & 0.15 & 0 \\ NBM & 0.02 & 0.91 & 0.37 & 0.39 & 0.36 & 0.33 & 0.36 & 0.29 & 0 & 0.13 & 0 \\ BP & 0.009 & 0.79 & 0 & 0.47 & 0.07 & 0.55 & 0.65 & 0.59 & 0 & 0.09 & 0 \\ \hline \end{tabular}
\end{table}
Table 8: Comparison of \(F_{i}\) calculation results.  
The traction energy consumption of the train is a piecewise function, and the calculation needs to be segmented. Combined with whether the brake handling is switched and the speed changes, the energy consumption of different segments is counted, and the curve of the total energy consumption with the driving distance based on the strategy proposed in this paper is obtained, as shown in Figure 8.  
After the high-speed train goes 30,000 m in the diagram, the energy saving of this research strategy begins to show. For each interval of 10,000 m, the cumulative energy consumption of the original and the optimized strategy is shown in Table 10.  
Figure 8: Relationship between total energy consumption and running distance comparison.  
Figure 7: Running simulation.  
In Table 10, with the increase in driving distance, the energy-saving percentage in this study increases continuously, saving about 18.78% of the traction energy for the whole journey. In the normal driving environment, compared with the manual driving strategy, the optimized driving strategy in this study shows that some energy is saved.