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Numerical investigation of a dual-loop EGR split strategy using a split index and multi-objective Pareto optimization

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  • Park, Jungsoo
  • Song, Soonho
  • Lee, Kyo Seung

Abstract

A proposed dual-loop exhaust-gas recirculation (EGR) system that combines the features of high-pressure (HP) and low-pressure (LP) systems is considered a key technology for improving the combustion behavior of diesel engines. The fraction of HP and LP flows, known as the EGR split, for a given dual-loop EGR rate play an important role in determining the engine performance and emission characteristics. Therefore, identifying the proper EGR split is important for the engine optimization and calibration processes, which affect the EGR response and deNOX efficiencies. The objective of this research was to develop a dual-loop EGR split strategy using numerical analysis and one-dimensional (1D) cycle simulation. A control system was modeled by coupling the 1D cycle simulation and the control logic. An EGR split index was developed to investigate the HP/LP split effects on the engine performance and emissions. Using the model-based control system, a multi-objective Pareto (MOP) analysis was used to minimize the NOX formation and fuel consumption through optimized engine operating parameters. The MOP analysis was performed using a response surface model extracted from Latin hypercube sampling as a fractional factorial design of experiment. By using an LP rich dual-loop EGR, a high EGR rate was attained at low, medium, and high engine speeds, increasing the applicable load ranges compared to base conditions.

Suggested Citation

  • Park, Jungsoo & Song, Soonho & Lee, Kyo Seung, 2015. "Numerical investigation of a dual-loop EGR split strategy using a split index and multi-objective Pareto optimization," Applied Energy, Elsevier, vol. 142(C), pages 21-32.
  • Handle: RePEc:eee:appene:v:142:y:2015:i:c:p:21-32
    DOI: 10.1016/j.apenergy.2014.12.030
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    References listed on IDEAS

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    1. Zeng, Xiangrui & Wang, Junmin, 2014. "A physics-based time-varying transport delay oxygen concentration model for dual-loop exhaust gas recirculation (EGR) engine air-paths," Applied Energy, Elsevier, vol. 125(C), pages 300-307.
    2. Asad, Usman & Zheng, Ming, 2014. "Exhaust gas recirculation for advanced diesel combustion cycles," Applied Energy, Elsevier, vol. 123(C), pages 242-252.
    3. Zamboni, Giorgio & Capobianco, Massimo, 2012. "Experimental study on the effects of HP and LP EGR in an automotive turbocharged diesel engine," Applied Energy, Elsevier, vol. 94(C), pages 117-128.
    4. Millo, Federico & Giacominetto, Paolo Ferrero & Bernardi, Marco Gianoglio, 2012. "Analysis of different exhaust gas recirculation architectures for passenger car Diesel engines," Applied Energy, Elsevier, vol. 98(C), pages 79-91.
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    Cited by:

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    5. Zamboni, Giorgio & Moggia, Simone & Capobianco, Massimo, 2016. "Hybrid EGR and turbocharging systems control for low NOX and fuel consumption in an automotive diesel engine," Applied Energy, Elsevier, vol. 165(C), pages 839-848.
    6. Park, Jungsoo & Choi, Jungwook, 2016. "Optimization of dual-loop exhaust gas recirculation splitting for a light-duty diesel engine with model-based control," Applied Energy, Elsevier, vol. 181(C), pages 268-277.
    7. Park, Sangjun & Cho, Jungkeun & Park, Jungsoo, 2019. "Numerical methodology on virtual model extension and system-level optimization of light-duty diesel vehicle with dual-loop exhaust gas recirculation," Applied Energy, Elsevier, vol. 242(C), pages 1422-1435.
    8. Heecheong Yoo & Bum Youl Park & Honghyun Cho & Jungsoo Park, 2019. "Performance Optimization of a Diesel Engine with a Two-Stage Turbocharging System and Dual-Loop EGR Using Multi-Objective Pareto Optimization Based on Diesel Cycle Simulation," Energies, MDPI, vol. 12(22), pages 1-26, November.
    9. Giorgio Zamboni & Simone Moggia & Massimo Capobianco, 2017. "Effects of a Dual-Loop Exhaust Gas Recirculation System and Variable Nozzle Turbine Control on the Operating Parameters of an Automotive Diesel Engine," Energies, MDPI, vol. 10(1), pages 1-18, January.
    10. Jiwon Park & Jungkeun Cho & Heewon Choi & Jungsoo Park, 2020. "Prediction of Reformed Gas Composition for Diesel Engines with a Reformed EGR System Using an Artificial Neural Network," Energies, MDPI, vol. 13(22), pages 1-17, November.
    11. Yoon, Wonjun & Kim, Jonghyun & Chung, Chungsoo & Park, Jungsoo, 2022. "Numerical study on prediction of icing phenomena in intake system of diesel engine: Operating conditions with low-to-middle velocity of inlet air," Energy, Elsevier, vol. 248(C).

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