Using a Genetic Algorithm to Achieve Optimal Matching between PMEP and Diameter of Intake and Exhaust Throat of a High-Boost-Ratio Engine

Yindong Song, Yiyu Xu, Xiuwei Cheng, Ziyu Wang, Weiqing Zhu and Xinyu Fan
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Yindong Song: School of Energy and Power Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China
Yiyu Xu: School of Energy and Power Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China
Xiuwei Cheng: China North Engine Research Institute, Tianjin 300400, China
Ziyu Wang: China North Engine Research Institute, Tianjin 300400, China
Weiqing Zhu: China North Engine Research Institute, Tianjin 300400, China
Xinyu Fan: School of Energy and Power Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China

Energies, 2022, vol. 15, issue 5, 1-17

Abstract: With the increasingly stringent CO 2 emission regulations, the degree of strengthening of the engines is increasing. Under high-pressure conditions, the airway throat parts of the intake and exhaust systems have a great influence on the flow loss of the diesel engine. The reasonable distribution of the throat area of the intake and exhaust ports in the limited cylinder headspace is key to improving the performance of supercharged engines. This study took a large-bore, high-pressure ratio diesel engine as the research object. Firstly, the three-dimensional (3D) flow simulation method was used to reveal the influence law of different throat areas on the engine intake and exhaust flow under steady-state conditions, and a steady-flow test bench was built to verify the accuracy of the simulation model and law. Secondly, based on the 3D steady-state calculation and test results, a more accurate one-dimensional simulation model was constructed, and a joint optimization simulation platform was established based on the dynamic data link library. On this basis, the mathematical description of the multi-objective optimization of airway throat size was established using machine learning methods, such as a genetic algorithm, the design domain and boundary conditions of variable parameters were clarified, and the collaborative optimization objective of integrated flow coefficient and flow loss is proposed to achieve the fast and accurate optimization of intake and exhaust throat diameters.

Keywords: CFD; high-boost-ratio engine; optimization design; genetic algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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