## 5 Conclusions  
In this study, engine test data were obtained from an engine test stand under 176 operating conditions. The urea injection volume was varied under each operating condition to obtain 25 sets of data corresponding to the NOx concentration at the SCR outlet and  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Test Value Before Optimization** & **Test Value After Optimization** \\ \hline WHTC cyclic NOx accumulation (g) & 1.75 & 1.62 \\ \hline \hline \end{tabular}
\end{table}
Table 10: WHITC transient cyclic NOx accumulation.  
Figure 5: Comparison of results before and after optimization of the SCR system.  
NH\({}_{3}\) slip. An SVM model was built to predict the NOx conversion efficiency and NH\({}_{3}\) slip from the experimental data and was optimized using the CPO algorithm to improve its prediction accuracy; the optimized SVM model was used instead of the mathematical model to save computational time. Then, it was used as an objective function to optimize the urea injection volume for all operating conditions using the NSGA-II algorithm. As the urea injection volume increases, although it leads to an increase in NOx conversion efficiency, it also leads to an increase in NH\({}_{3}\) slip, which is not permitted by emission regulations. Therefore, the optimization aims to find the optimal urea injection rate for each condition to maximize the NOx conversion efficiency, keeping at the same time the NH\({}_{3}\) slip within 10 ppm. Finally, the optimized urea injection rate can effectively reduce the NOx accumulation of the WHTC cycle by about 7.5% via the bench test.  
The results show that the calibration of the urea injection rate of the SCR system can be accomplished by using the method based on the CPO-SVM-NSGA-II model. The optimal urea injection map established using this method can help the engine bench test to complete the calibration of some urea injection quantities, which can greatly shorten the calibration period and provide a reference or benchmark for the control system and calibration work.  
The contributions of this paper are mainly as follows:  
1. Urea injection optimization is transferred to a computer, which can be done in only 15 s for each working condition. The calibration cycle is shortened substantially.
2. Based on the CPO and genetic algorithms, the optimization of urea injection amount is completed while ensuring the model has high prediction accuracy.
3. The study provide a reference or benchmark for diesel engine control systems and urea injection calibration.  
X.C.: Investigation, experiment, Data curation, Writing--original draft. C.M.: Formal analysis, Validation. Q.D.: Data analysis, Software. K.S.: Conceptualization, Methodology. S.B.: Project administration, Writing--review & editing, Funding acquisition. Z.L.: Visualization, Supervision. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Shandong Province Key R&D Program, China (2021 CXGC010207), and the open funds of the National Engineering Laboratory of Mobile Source Pollution Control Technology of China (Grant No. NELMS2019A01).  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.  
The authors would like to thank the reviews whose constructive and detailed critique contributed to the quality of this paper.  
Authors [PERSON] and [PERSON] were employed by the company Weichai Power Co. Ltd. Author [PERSON] was employed by the company China Automotive Technology & Research Center Co. Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.  
The following abbreviations are used in this manuscript:  
EGR exhaust gas recirculation  
SCR selective catalytic reduction  
TDSI time-discretized and space-integrated  
NSGA-II Nondominated Sorting Genetic Algorithm II  
SVM Support Vector Machine  
DOC  
Diesel Oxidation Catalyst