基于模型的船用柴油机多目标优化

在船用发动机第一阶段排放法规将要实施的情况下,为兼顾发动机的经济性和排放性,采用基于模型的多目标优化标定方法对船用发动机进行优化。根据排放法规的要求并结合船用发动机的推进特性和工况点,采用混合试验设计(Do E)设计试验工况点,在发动机台架上收集发动机试验数据,通过对试验数据进行分析建立优化标定模型,以经济性最好及满足氮氧化物(NOX)和碳氢化合物(HC)排放要求为目标,以其他排放物和排温为约束条件,应用基于Pareto概念的遗传算法进行优化求解。验证结果表明:法规排放点满足船用发动机一阶段排放法规的要求,氮氧化物(NOX)和碳氢化合物(HC)排放、油耗分别比原机降低12.34%、3.65%,一氧化碳(CO)和颗粒物(PM)排放分别比原机降低33.29%、13.21%;推进特性下工况点得到了较好的优化效果。

Research on Model-based Multi-objective Optimization of Marine Diesel Engine

The model based multi-objective optimization calibration method is adopted to improve the engine economy under the premise of satisfying the first phase emission regulation in China. According to the requirement of the emission regulation, the test scheme is designed with the mixed experimental design, and the optimization model is established by collecting the experimental data of the engine. The optimal calibration model is established through the analysis of experimental data, and the optimal goal is to optimize the best economic emission using the genetic algorithm based on the Pareto concept. The experimental results show that meet emission regulations, NOx + HC emissions and fuel consumption decreased by 12.34 % and 3.65 %, respectively, and CO emission and PM emission decreased by 33.29 % and 13.21 % compared to the original machine; The optimization results of the propulsion performance are also obtained.