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A novel control strategy for DDF/PPCI combustion mode in a diesel micro-pilot ignited dual-fuel engine

Author

Listed:
  • Hu, Deng
  • Wang, Hechun
  • Yang, Chuanlei
  • niu, Xiaoxiao
  • Mu, Hongyu
  • Wang, Yinyan
  • Zhao, Xingtian

Abstract

The target of this paper is to study two combustion control strategies, partial premixed compression ignition (PPCI) and dual fuel combustion (DDF), to solve the problems of low efficiency and high emissions of micro-ignition dual fuel engines. Firstly, the effects of different control parameters on engine performance and emissions in two combustion modes were studied. Then, the encoder-decoder convolutional neural network-gated recurrent unit (ED CNN-GRU) is used for the first time to establish a predictive regression model between the operating parameters and performance of the diesel micro-ignition dual-fuel engine. Finally, NSGA III is used to drive ED CNN-GRU to perform multi-objective optimization of engine performance. The results show that under 75 % load, the predicted results of the model and test results show that the corresponding THC emissions in the PPCI combustion mode are 50.65 % and 53.18 % lower than those in the DDF combustion mode, the corresponding CO emissions in the PPCI combustion mode are 69.05 % and 70.26 % lower than those in the DDF combustion mode respectively. The prediction results of the model and the test results meet the Tier III emission regulations, and the emission is minimized while taking into account the economy. Under the propulsion characteristics, PPCI combustion mode is selected for 0–75 % load, and DDF combustion mode is selected for more than 75 % load. The control strategy of micro ignition dual fuel engine can effectively promote the development of micro ignition dual fuel engine in the field of marine engine.

Suggested Citation

  • Hu, Deng & Wang, Hechun & Yang, Chuanlei & niu, Xiaoxiao & Mu, Hongyu & Wang, Yinyan & Zhao, Xingtian, 2024. "A novel control strategy for DDF/PPCI combustion mode in a diesel micro-pilot ignited dual-fuel engine," Energy, Elsevier, vol. 313(C).
    • Handle: RePEc:eee:energy:v:313:y:2024:i:c:s0360544224037101
    DOI: 10.1016/j.energy.2024.133932
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    References listed on IDEAS

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    1. Shouying Jin & Jinze Li & Longfei Deng & Binyang Wu, 2021. "Effect of the HPDI and PPCI Combustion Modes of Direct-Injection Natural Gas Engine on Combustion and Emissions," Energies, MDPI, vol. 14(7), pages 1-17, April.
    2. Jia, Dongdong & Qiao, Junhao & Wang, Shuqian & Guan, Jinhuan & Liu, Jingping & Fu, Jianqin & Li, Yangyang & Wang, Rumin, 2024. "Influence of variable enhanced LIVC miller cycle coupled with high compression ratio on the performance and combustion of a supercharged spark ignition engine," Energy, Elsevier, vol. 309(C).
    3. Kale, Aneesh Vijay & Krishnasamy, Anand, 2023. "Experimental study of homogeneous charge compression ignition combustion in a light-duty diesel engine fueled with isopropanol–gasoline blends," Energy, Elsevier, vol. 264(C).
    4. Li, Yangyang & Zhou, Shi & Liu, Jingping & Tong, Ji & Dang, Jian & Yang, Fuyuan & Ouyang, Minggao, 2023. "Multi-objective optimization of the Atkinson cycle gasoline engine using NSGA Ⅲ coupled with support vector machine and back-propagation algorithm," Energy, Elsevier, vol. 262(PA).
    5. Kumar, A. Naresh & Kishore, P.S. & Raju, K. Brahma & Ashok, B. & Vignesh, R. & Jeevanantham, A.K. & Nanthagopal, K. & Tamilvanan, A., 2020. "Decanol proportional effect prediction model as additive in palm biodiesel using ANN and RSM technique for diesel engine," Energy, Elsevier, vol. 213(C).
    6. Wang, Yuhua & Wang, Guiyong & Yao, Guozhong & Shen, Qianqiao & Yu, Xuan & He, Shuchao, 2023. "Combining GA-SVM and NSGA-Ⅲ multi-objective optimization to reduce the emission and fuel consumption of high-pressure common-rail diesel engine," Energy, Elsevier, vol. 278(PA).
    7. Zhang, Zhiqing & Lv, Junshuai & Li, Weiqing & Long, Junming & Wang, Su & Tan, Dongli & Yin, Zibin, 2022. "Performance and emission evaluation of a marine diesel engine fueled with natural gas ignited by biodiesel-diesel blended fuel," Energy, Elsevier, vol. 256(C).
    8. Novella, Ricardo & Gomez-Soriano, Josep & González-Domínguez, David & Olaciregui, Orlando, 2024. "Optimizing hydrogen spark-ignition engine performance and pollutants by combining VVT and EGR strategies through numerical simulation," Applied Energy, Elsevier, vol. 376(PB).
    9. Lu, Yao & Que, Jinhao & Xia, Yu & Li, Xingqi & Jiang, Qingli & Feng, Liyan, 2024. "A comparative study of the effects of EGR on combustion and emission characteristics of port fuel injection and late direct injection in hydrogen internal combustion engine," Applied Energy, Elsevier, vol. 375(C).
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