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Genetic algorithm optimization applied to the fuel supply parameters of diesel engines working at plateau

Author

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  • Zhu, Zhenxia
  • Zhang, Fujun
  • Li, Changjiang
  • Wu, Taotao
  • Han, Kai
  • Lv, Jianguo
  • Li, Yunlong
  • Xiao, Xuelian

Abstract

In order to enhance the power performance for the diesel engines working at plateau, the method to adjust fuel injecting parameters had been adopted. However, the diesel engine is considered as a complicated nonlinear multiple-inputs and multi-boundary system. Hence, it is difficult to find out the appropriate value for fuel injecting parameters for all conditions, this is the reason why we study the Genetic Algorithm method for optimization. Firstly, the numerical model of a turbocharged diesel engine with the predictable combustion model was established and then verified by experimental data. Base on the engine model, the relation between injecting parameters and performance was studied. Secondly, the optimization model is constructed, including the objective and the boundary conditions with a novel parameter introduced, measuring the surge margin of the operating points. Then, the Fitness function is proposed employing penalty functions to express constraints. Based on the impact of injecting parameters on constraint conditions, the method was put forward about how to choose the penalty parameter values, named “Fitness Equal to Zero at the Worst Point”. In order to explain this method, 4500m rated operation point was illustrated and four schemes with different plenty values were compared. After the comparison of the population distributions and the optimizing processes, the Scheme II is proofed to be accurate and efficient, which adopted the plenty value chosen method (Fitness (w)=0). Finally, this GA model was used for the fuel supply parameters optimization of full-load operation at 4500m altitude. The result demonstrates that the rated engine power is enhanced by 22.7% and the fuel consumption reduces by 6.4%.

Suggested Citation

  • Zhu, Zhenxia & Zhang, Fujun & Li, Changjiang & Wu, Taotao & Han, Kai & Lv, Jianguo & Li, Yunlong & Xiao, Xuelian, 2015. "Genetic algorithm optimization applied to the fuel supply parameters of diesel engines working at plateau," Applied Energy, Elsevier, vol. 157(C), pages 789-797.
    • Handle: RePEc:eee:appene:v:157:y:2015:i:c:p:789-797
    DOI: 10.1016/j.apenergy.2015.03.126
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    References listed on IDEAS

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    Cited by:

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    4. Yi Dong & Jianmin Liu & Yanbin Liu & Xinyong Qiao & Xiaoming Zhang & Ying Jin & Shaoliang Zhang & Tianqi Wang & Qi Kang, 2020. "A RBFNN & GACMOO-Based Working State Optimization Control Study on Heavy-Duty Diesel Engine Working in Plateau Environment," Energies, MDPI, vol. 13(1), pages 1-24, January.
    5. Xiao, Renxin & Liang, Daping & Ba, Tingjie & Sun, Min & Chen, Guisheng & Yao, Guozhong & Zheng, Yongming, 2024. "Integrated optimization of dedicated engine and energy management strategy for the plug-in hybrid commercial vehicle at high altitude," Energy, Elsevier, vol. 290(C).
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    7. Jaliliantabar, Farzad & Ghobadian, Barat & Najafi, Gholamhassan & Mamat, Rizalman & Carlucci, Antonio Paolo, 2019. "Multi-objective NSGA-II optimization of a compression ignition engine parameters using biodiesel fuel and exhaust gas recirculation," Energy, Elsevier, vol. 187(C).
    8. Liu, Jinlong & Wang, Bosen & Meng, Zhongwei & Liu, Zhentao, 2023. "An examination of performance deterioration indicators of diesel engines on the plateau," Energy, Elsevier, vol. 262(PB).
    9. Tadros, M. & Ventura, M. & Guedes Soares, C., 2019. "Optimization procedure to minimize fuel consumption of a four-stroke marine turbocharged diesel engine," Energy, Elsevier, vol. 168(C), pages 897-908.
    10. John Jairo Ceballos & Andrés Melgar & Francisco V. Tinaut, 2021. "Influence of Environmental Changes Due to Altitude on Performance, Fuel Consumption and Emissions of a Naturally Aspirated Diesel Engine," Energies, MDPI, vol. 14(17), pages 1-41, August.
    11. 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).
    12. Meng Xia & Changlu Zhao & Fujun Zhang & Ying Huang, 2017. "Modeling the Performance of a New Speed Adjustable Compound Supercharging Diesel Engine Working under Plateau Conditions," Energies, MDPI, vol. 10(5), pages 1-14, May.
    13. Meng Xia & Fujun Zhang, 2020. "Application of Multi-Parameter Fuzzy Optimization to Enhance Performance of a Regulated Two-Stage Turbocharged Diesel Engine Operating at High Altitude," Energies, MDPI, vol. 13(17), pages 1-12, August.
    14. Jafari, M. & Parhizkar, M.J. & Amani, E. & Naderan, H., 2016. "Inclusion of entropy generation minimization in multi-objective CFD optimization of diesel engines," Energy, Elsevier, vol. 114(C), pages 526-541.

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