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Application of Multi-Parameter Fuzzy Optimization to Enhance Performance of a Regulated Two-Stage Turbocharged Diesel Engine Operating at High Altitude

Author

Listed:
  • Meng Xia

    (School of Transportation Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China)

  • Fujun Zhang

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

Abstract

Air intake and fuel supply conditions are the major factors that affect diesel engine performance at plateau. In a regulated two-stage turbocharged diesel engine, these parameters are reflected as the adjustment of fuel injection mass ( m fuel ), fuel injection advance angle, and bypass valve opening of a high-pressure stage (HP) turbine. Due to the strongly nonlinear nature and complexity of the diesel engine, it is difficult to find the proper parameter combinations. That is why a model-based optimization method is adopted in this paper. The simulation model of a six-cylinder two-stage turbocharged diesel engine is built on the GT-SUITE platform. According to the analysis of diesel engine operation characteristics at high altitude, a fuzzy optimization algorithm is proposed based on a fuzzy logic controller and is realized in a MATLAB/simulink (MATLAB 2014, Mathworks, Natick, MA, USA) environment. Joint optimization of air intake and fuel supply parameters is then performed on the GT-MATLAB co-simulation platform. Results show that engine torque at full load is significantly increased. At the full load point of 2100 r/min, engine power is increased from 256.5 to 319.6 kW, and brake specific fuel consumption (BSFC) is reduced from 243.1 to 222.3 g/(kW·h). Peak torque is increased from 1944.8 to 2173.2 N·m.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4278-:d:400721
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    References listed on IDEAS

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    1. Mariani, F. & Grimaldi, C.N. & Battistoni, M., 2014. "Diesel engine NOx emissions control: An advanced method for the O2 evaluation in the intake flow," Applied Energy, Elsevier, vol. 113(C), pages 576-588.
    2. Zhao, Jinxing & Xu, Min, 2013. "Fuel economy optimization of an Atkinson cycle engine using genetic algorithm," Applied Energy, Elsevier, vol. 105(C), pages 335-348.
    3. Al-Hinti, I. & Samhouri, M. & Al-Ghandoor, A. & Sakhrieh, A., 2009. "The effect of boost pressure on the performance characteristics of a diesel engine: A neuro-fuzzy approach," Applied Energy, Elsevier, vol. 86(1), pages 113-121, January.
    4. 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.
    5. Ganapathy, T. & Murugesan, K. & Gakkhar, R.P., 2009. "Performance optimization of Jatropha biodiesel engine model using Taguchi approach," Applied Energy, Elsevier, vol. 86(11), pages 2476-2486, November.
    6. Ogaji, S.O.T. & Marinai, L. & Sampath, S. & Singh, R. & Prober, S.D., 2005. "Gas-turbine fault diagnostics: a fuzzy-logic approach," Applied Energy, Elsevier, vol. 82(1), pages 81-89, September.
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    2. Batyr Orazbayev & Ainur Zhumadillayeva & Kulman Orazbayeva & Sandugash Iskakova & Balbupe Utenova & Farit Gazizov & Svetlana Ilyashenko & Olga Afanaseva, 2022. "The System of Models and Optimization of Operating Modes of a Catalytic Reforming Unit Using Initial Fuzzy Information," Energies, MDPI, vol. 15(4), pages 1-25, February.

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