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Multiobjective optimization of the cooling system of a marine diesel engine
Energy Science & Engineering ( IF 3.8 ) Pub Date : 2021-08-07 , DOI: 10.1002/ese3.960
Bo Zhang 1 , Ping Zhang 1 , Fanming Zeng 1
Affiliation  

An intelligent cooling system directly influences the thermal load of high-temperature components, heat distribution, and fuel economy of a diesel engine. An optimal coolant pump rotational speed map is a key factor in intelligent cooling control strategies. In this study, we designed an experimental variable coolant flow system for a maritime diesel engine. Experiment design and D-optimal designs were used to optimize the parameters of the diesel engine cooling system. The diesel engine speed, load, and freshwater rotational pump speed were selected as variables. The temperature of the high-thermal-load zone of the combustion chamber components, fuel consumption rate, effective power, and peak cylinder pressure were selected as response variables, and the D-optimal method was used to sample the experimental points. Polynomial response surface models were obtained using a stepwise algorithm. A multiobjective optimization problem was converted into a simple-objective optimization problem using the ideal point method. A genetic algorithm was used to optimize the single-objective function globally to obtain the optimal freshwater pump speed map for a diesel engine under all conditions. On average, the optimized cooling system decreased the fuel consumption by 1.901%. Six typical propulsive conditions were selected to confirm the validity of the optimization results. The experimental results indicate that the fuel consumption decreased by 2.35%, the effective power increased by 2.26%, and the power consumption of the water pump decreased by 17.83%. The combination of experiment design and D-optimal designs offers the advantages of low cost, high efficiency, and high precision in solving multiobjective optimization problems involving strong coupling and nonlinear systems. The results of this research provide data support and a theoretical basis for intelligent cooling control strategies.

中文翻译:

船用柴油机冷却系统多目标优化

智能冷却系统直接影响柴油机高温部件的热负荷、热分布和燃油经济性。最佳冷却剂泵转速图是智能冷却控制策略的关键因素。在这项研究中,我们为船用柴油发动机设计了一个实验性的可变冷却剂流量系统。采用实验设计和D-最优设计对柴油机冷却系统参数进行优化。柴油发动机转速、负载和淡水旋转泵转速被选为变量。选取燃烧室部件高热负荷区温度、燃料消耗率、有效功率、峰值气缸压力作为响应变量,采用D-最优方法对实验点进行采样。多项式响应面模型是使用逐步算法获得的。使用理想点法将多目标优化问题转化为简单目标优化问题。使用遗传算法对单目标函数进行全局优化,以获得柴油机在所有条件下的最佳淡水泵速度图。优化后的冷却系统平均降低油耗1.901%。选取了六个典型的推进工况来验证优化结果的有效性。实验结果表明,油耗降低2.35%,有效功率提高2.26%,水泵功率消耗降低17.83%。实验设计与 D 最优设计相结合,具有成本低、效率高、高精度求解涉及强耦合和非线性系统的多目标优化问题。本研究结果为智能冷却控制策略提供了数据支持和理论依据。
更新日期:2021-10-03
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