# Examining the Optimization of Spray Cleaning Performance for LiDAR Sensor
## 3 Results and Discussion
### Optimized Cleaning Model for the Entire Target Area  
As a result of analyzing the experimental data designed according to face-central composite design (FCCD) using the analysis of variance (ANOVA) technique for analysis of variance, a quadratic model was selected as the most suitable model. The statistics of the model according to the number of sprays are shown in Table 2. Adjusted (adj.) R-squared expressed the percentage at which the model expressed the data, whereas the F-value (\(p\)-value) denoted the statistical significance of the model. All quadratic model responses for the first to fourth sprays exhibited suitable and significant results. The model for the second spray showed the highest adjusted explanatory power (adj. R-squared) of 89%. If the R-squared value is explained by the entire model, the adj. R-squared value is the variable mean of squared regression obtained after considering the degrees of freedom divided by the mean of the square total.  
Figure 12 shows that the residual normality verification results for all four models satisfied normality. Interactive terms were removed due to the absence of interactions between the factors. All models were found to be suitable because the lack of fit exceeded 0.05. The ANOVA results of the quadratic models based on the cleaning factor are presented in Table 13. The changes in cleaning rate by cleaning factors are shown in Figure 14.  
For all four sprays, the primary terms of spray time and washer pressure were significant at a significance level of 5%. The quadratic term of the spray angle was significant  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model Response** & **R-Squared** & **Adj.** & **Adeq.** & & \\
**R-Squared** & **R-Squared** & **Precision** & & & \\ \hline First spray & 0.8666 & 0.8158 & 13.9004 & 17.06 & \textless{}0.0001 ** \\ Second spray & 0.9205 & 0.8902 & 16.6642 & 30.39 & \textless{}0.0001 ** \\ Third spray & 0.9026 & 0.8655 & 14.173 & 24.33 & \textless{}0.0001 ** \\ Fourth spray & 0.9147 & 0.8822 & 14.573 & 28.16 & \textless{}0.0001 ** \\ \hline \hline \end{tabular}  
* \(p<0.05\).  
\end{table}
Table 2: ANOVA results for quadratic models with varying cleaning rates.  
Figure 8: Test nozzle: (**a**) Design draft and (**b**) actual prototype.  
at a significance level of 10% for the first spray, whereas the quadratic term of the washer pressure was significant at a significance level of 1% for the second to fourth sprays.  
For the first spray, the cleaning rate increased with the spray time and washer pressure. The influence of the spray angle formed a curve. For the second spray, the cleaning rate increased with the spray time and washer pressure. However, unlike the first spray, the influence of the washer pressure formed a curve. The spray angle that influenced the curve formation for the first spray exhibited no difference in the cleaning rate. For the third spray, the same results as those of the second spray were observed, and the curve formed by the washer pressure was noticeable. The fourth spray exhibited similar tendencies, and the curve formed by the washer pressure was more noticeable. The spray angle and target point caused no change.