Diesel Engine Urea Injection Optimization Based on the Crested Porcupine Optimizer and Genetic Algorithm

As a major emission pollutant from diesel engines, NOx is extremely harmful to the environment and human health. In order to reduce NOx emissions, countries around the world have been implementing increasingly stringent emissions regulations. The urea injection strategies of the Selective Catalytic Reduction (SCR) system are the main factors affecting NOx emissions and NH3 slips of diesel engines. In this study, test data were obtained from an engine test stand and a Support Vector Machine (SVM) was developed using the test data to predict NOx conversion efficiency and NH3 slip. The SVM model was optimized using the Crested Porcupine Optimizer (CPO) to improve its prediction accuracy and was made to replace the mathematical model to save computational time. Finally, the Nondominated Sorting Genetic Algorithm II (NSGA-II) was used to optimize the urea injection volume for all conditions. The optimized urea injection volume maximizes the NOx conversion efficiency of the SCR system while controlling the NH3 slip within 10 ppm. In addition, based on this method, the urea injection pulse spectrum under full operating conditions was obtained, and the optimized urea injection amount can effectively reduce the NOx accumulation of the WHTC cycle by about 7.5%, as shown through bench testing.