Prediction and Optimization of Integrated Performance of a Marine Dual-Fuel Engine

被引：0
|
作者：
Xu D. [1 ]
Yao C. [1 ]
Ma C. [1 ]
Song E. [1 ]
机构：
[1] College of Power and Energy Engineering, Harbin Engineering University, Harbin
来源：
Neiranji Xuebao/Transactions of CSICE (Chinese Society for Internal Combustion Engines) | 2022年 / 40卷 / 05期
关键词：
Dual-fuel engine; Multi-objective optimization; Prediction modeling;
D O I：
10.16236/j.cnki.nrjxb.202205051
中图分类号：
学科分类号：
摘要：
In order to enable a dual-fuel marine engine to meet increasingly stringent emission regulations and obtain higher economic benefits, it is necessary to comprehensively optimize full operating performances of the engine to obtain a better compromise between emissions and fuel consumption. First of all, based on the long shortterm memory(LSTM) neural network, a prediction model for engine-out NOx and brake specific fuel consumption(BSFC) was established, and then the built model was combined with the NSGA-Ⅱ algorithm to optimize NOx and BSFC and to obtain the corresponding optimal Pareto frontier solution set. Finally, the optimal control parameter combination was calibrated to the electronic control unit(ECU) for experimental verification. The experimental results show that the optimized NOx emissions decrease by 76.4% on average, the BSFC decreases by 3.5% on average, and the NOx emissions meet the limit requirements of IMO Tier-Ⅲ. © 2022, Editorial Office of the Transaction of CSICE. All right reserved.
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页码：403 / 411
页数：8
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