## 5 Validation Experiment and Discussion  
### Validation Experiment  
To verify the performance of the optimized shoveling trajectory, the corresponding trajectories were planned at different engine speeds according to the data in Table 8, and the research line of thought is shown in Figure 12. Three experiments at each of three different engine speeds with optimized trajectories in a gravel pile and sand pile and the results of the shoveling experiments with the shoveling operation parameters are shown in Table 9. Due to the large randomness of the shoveling operation itself and the accuracy problem in the data collection process, which led to certain errors in the testing process, it was difficult to ensure that the trajectory remained the same as the theoretical trajectory even by using the automatic shoveling platform. Therefore, in the insertion phase, when the error between the actual insertion distance of the wheel loader and the theoretical distance is less than 20 mm, it can be considered as basically conforming to the theoretical trajectory. Figure 11: IPSO optimization iterative process. (**a**) Gravel-900 RPM; (**b**) Gravel-1200 RPM; (**c**) Gravel-1500 RPM; (**d**) Sand-900 RPM; (**e**) Sand-1200 RPM; (**f**) Sand-1500 RPM. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Type of Pile**} & \multirow{2}{*}{\
\begin{tabular}{c} **Engine Speed** \\ **(RFM)** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Initial** \\ **Velocity** \\ **(m\(\cdot\)s\({}^{-1}\))** \\ \end{tabular} } & \multicolumn{2}{c}{**Displacement of Wheel**} & \multicolumn{2}{c}{**Displacement of Wheel**} & \multicolumn{2}{c}{**Fuel**} \\  & & **Velocity** & **Loader in Insertion** & **Loader in Scooping** & **Consumption** \\  & & **(m\(\cdot\)s\({}^{-1}\))** & **Phase (mm)** & **Phase (mm)** & **(mL)** \\ \hline \multirow{3}{*}{Gravel} & 900 & 0.59 & 704 & 1778 & 55.05 \\  & 1200 & 0.86 & 686 & 1843 & 59.58 \\  & 1500 & 1.16 & 698 & 1799 & 48.59 \\ \hline \multirow{3}{*}{Sand} & 900 & 0.48 & 839 & 1272 & 48.12 \\  & 1200 & 0.79 & 749 & 1520 & 48.16 \\ \cline{1-1}  & 1500 & 1.25 & 733 & 1569 & 56.87 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Optimization results. The average fuel consumption of the validation experiment, the theoretical fuel consumption of IPSO optimization, the minimum fuel consumption of the sample, the maximum fuel consumption of the sample are shown in Figure 13. The deviation between the average fuel consumption of the validation experiment and the theoretical fuel consumption of IPSO optimization is small. The maximum deviation value is 8.23%, and the accuracy of the fuel consumption model is high. The deviation from the actual shoveling operation is small. In Gravel-1200 RPM, the experimental average fuel consumption is slightly higher than the minimum fuel consumption of the sample, and the fuel consumption is improved by 0.62%. However, in the other models, the average fuel consumption of the validation experiment is reduced compared with the minimum fuel consumption of the sample. Among them, the maximum reduction in fuel consumption is 22.63% in Gravel-900 RPM. The average fuel consumption of the validation experiment is substantially reduced compared to the sample maximum fuel consumption, with a maximum reduction of 73.65% and a minimum reduction of 55.70%. In the gravel  
Figure 12: The research line of thought.