Multi-Objective Optimization of the Structural Design of a Combustion Chamber of a Small Agricultural Diesel Engine Fueled with B20 Blend Fuel at a High Altitude Area

Zhipeng Shi, Jun Wang (), Xiangchi Guo and Xueyuan Liu
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Zhipeng Shi: School of Mechanical and Transportation, Southwest Forestry University, Kunming 650224, China
Jun Wang: School of Mechanical and Transportation, Southwest Forestry University, Kunming 650224, China
Xiangchi Guo: School of Mechanical and Transportation, Southwest Forestry University, Kunming 650224, China
Xueyuan Liu: School of Mechanical and Transportation, Southwest Forestry University, Kunming 650224, China

Sustainability, 2023, vol. 15, issue 15, 1-13

Abstract: This study focuses on a small agricultural diesel engine fueled with B20 (20% biodiesel and 80% diesel by volume) blend fuel in a plateau area. The combustion chamber’s structural parameters and fuel injection angle were taken as variables at peak torque conditions. First, a full factorial design was used for experimental design. Second, the back-propagation (BP) neural network was employed to predict the indicated thermal efficiency and the indicated specific NO x emission. Third, the non-dominated sorting genetic algorithm-II (NSGA-II) was utilized to optimize the indicated thermal efficiency and the indicated specific NO x emission. Finally, the technique for order of preference by similarity to ideal solution (TOPSIS) method was applied to obtain optimal solutions, and a three-dimensional numerical simulation was conducted to verify the optimization results. The optimization results indicate that the shape characteristics of the combustion chamber have a certain influence on the engine’s performance. The optimized design significantly reduces NO x emissions, by 22.83%, compared to the original engine, whilst maintaining the engine’s performance.

Keywords: agricultural diesel engine; combustion chamber; biodiesel; multi-objective optimization; altitude (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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