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Parametric study of combustion characteristics of diesel/methanol dual fuel engine using global sensitivity analysis and multi-objective optimization

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  • Ma, Yinjie
  • Zhao, Yuanhao
  • Yang, Dong
  • E, Jiaqiang
  • Zhao, Jialuo
  • Pan, Mingzhang

Abstract

The pursuit of clean and efficient internal combustion engine power necessitates the substitution of fossil fuels with methanol and the adoption of advanced combustion strategies. This study examines the combustion and emission characteristics of methanol/diesel dual-fuel compression ignition engines. To understand the intricate interplay between critical parameters and engine performance, the global sensitivity analysis (GSA) method is employed, utilizing Sobol sensitivity as the quantitative metric. The investigated parameters include methanol substitution rate, diesel injection parameters, and five thermodynamics parameters concerning in-cylinder conditions. A validated computational fluid dynamics (CFD) model, coupled with a chemical kinetic mechanism, is developed to predict the combustion behavior of the dual-fuel engine accurately. This predictive capability forms the basis for utilizing the tree-based process optimization (TPOT) algorithm. By implementing TPOT, a significant reduction in the mean square error (MSE) of the predicted characteristics model is achieved, averaging a decrease of 73.59 %. Subsequently, a multi-objective optimization is conducted, exploring the impact of varying target weights on the optimal outcomes. Results show the initial pressure significantly impacts the engine's economy, power and emission characteristics, and NOx formation should be carefully considered in the combustion optimization of dual-fuel engines.

Suggested Citation

  • Ma, Yinjie & Zhao, Yuanhao & Yang, Dong & E, Jiaqiang & Zhao, Jialuo & Pan, Mingzhang, 2024. "Parametric study of combustion characteristics of diesel/methanol dual fuel engine using global sensitivity analysis and multi-objective optimization," Renewable Energy, Elsevier, vol. 237(PB).
    • Handle: RePEc:eee:renene:v:237:y:2024:i:pb:s0960148124017580
    DOI: 10.1016/j.renene.2024.121690
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    References listed on IDEAS

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    1. Liu, Xinlei & Wang, Hu & Zheng, Zunqing & Liu, Jialin & Reitz, Rolf D. & Yao, Mingfa, 2016. "Development of a combined reduced primary reference fuel-alcohols (methanol/ethanol/propanols/butanols/n-pentanol) mechanism for engine applications," Energy, Elsevier, vol. 114(C), pages 542-558.
    2. Muhammad Amin & Muhammad Qasim & Muhammad Amanullah & Saima Afzal, 2020. "Performance of some ridge estimators for the gamma regression model," Statistical Papers, Springer, vol. 61(3), pages 997-1026, June.
    3. Zádor, J. & Zsély, I.Gy. & Turányi, T., 2006. "Local and global uncertainty analysis of complex chemical kinetic systems," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1232-1240.
    4. Farzad Jaliliantabar & Barat Ghobadian & Gholamhassan Najafi & Talal Yusaf, 2018. "Artificial Neural Network Modeling and Sensitivity Analysis of Performance and Emissions in a Compression Ignition Engine Using Biodiesel Fuel," Energies, MDPI, vol. 11(9), pages 1-24, September.
    5. Wang, Bin & Yao, Anren & Yao, Chunde & Chen, Chao & Wang, Hui, 2020. "In-depth comparison between pure diesel and diesel methanol dual fuel combustion mode," Applied Energy, Elsevier, vol. 278(C).
    6. Zhou, Haiqin & Li, Xiangrong & Chen, Yanlin & Kang, Yuning & Liu, Dong & Liu, Fushui, 2020. "The effect of spray angle on the combustion and emission performance of a separated swirl combustion system in a diesel engine," Energy, Elsevier, vol. 190(C).
    7. Yilmaz, Nadir, 2012. "Comparative analysis of biodiesel–ethanol–diesel and biodiesel–methanol–diesel blends in a diesel engine," Energy, Elsevier, vol. 40(1), pages 210-213.
    8. Su, Li-Wang & Li, Xiang-Rong & Sun, Zuo-Yu, 2013. "The consumption, production and transportation of methanol in China: A review," Energy Policy, Elsevier, vol. 63(C), pages 130-138.
    9. Ma, Baodong & Yao, Anren & Yao, Chunde & Chen, Chao & Qu, Guofan & Wang, Wenchao & Ai, Youkai, 2021. "Multiple combustion modes existing in the engine operating in diesel methanol dual fuel," Energy, Elsevier, vol. 234(C).
    10. Leandro da Silva Pereira & Lucas Monteiro Chaves & Devanil Jaques de Souza, 2017. "An Intuitive Geometric Approach to the Gauss Markov Theorem," The American Statistician, Taylor & Francis Journals, vol. 71(1), pages 67-70, January.
    11. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    12. Li, Yaopeng & Li, Hua & Pang, Bin & Liu, Fei & Jia, Ming & Long, Wuqiang & Tian, Jiangping & Guo, Lijun, 2023. "Co-optimization of injection parameters and injector layouts for a methanol/diesel direct dual-fuel stratification (DDFS) engine," Energy, Elsevier, vol. 284(C).
    13. Park, Sangjun & Cho, Jungkeun & Park, Jungsoo & Song, Soonho, 2017. "Numerical study of the performance and NOx emission of a diesel-methanol dual-fuel engine using multi-objective Pareto optimization," Energy, Elsevier, vol. 124(C), pages 272-283.
    14. Tang, Yuanyou & Wang, Yang & Long, Wuqiang & Xiao, Ge & Wang, Yongjian & Li, Weixing, 2023. "Analysis and enhancement of methanol reformer performance for online reforming based on waste heat recovery of methanol-diesel dual direct injection engine," Energy, Elsevier, vol. 283(C).
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