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Development of a Model-Based Coordinated Air-Fuel Controller for a 3.0 dm 3 Diesel Engine and Its Assessment through Model-in-the-Loop

Author

Listed:
  • Loris Ventura

    (Energy Department, Politecnico di Torino, 10129 Torino, Italy)

  • Roberto Finesso

    (Energy Department, Politecnico di Torino, 10129 Torino, Italy)

  • Stefano A. Malan

    (Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy)

Abstract

The tightening of diesel pollutant emission regulations has made Internal Combustion Engine (ICE) management through steady-state maps obsolete. To overcome the map’s scarce performance and efficiently manage the engine, control systems must cope with ICE transient operations, the coupling between its subsystem dynamics, and the tradeoff between different requirements. The work demonstrates the effectiveness of a reference generator that coordinates the air path and combustion control systems of a turbocharged heavy-duty diesel engine. The control system coordinator is based on neural networks and allows for following different engine-out Nitrogen Oxide (NOx) targets while satisfying the load request. The air path control system provides the global conditions for the correct functioning of the engine, targeting O 2 concentration and pressure in the intake manifold. Through cooperation, the combustion control targets Brake Mean Effective Pressure (BMEP) and NOx to react to rapid changes in the engine operating state and compensates for the remaining deviations with respect to load and NOx targets. The reference generator and the two controller algorithms are suitable for real-time implementation on rapid-prototyping hardware. The performance overall was good, allowing the engine to follow different NOx targets with 150 ppm of deviation and to achieve an average BMEP error of 0.3 bar.

Suggested Citation

  • Loris Ventura & Roberto Finesso & Stefano A. Malan, 2023. "Development of a Model-Based Coordinated Air-Fuel Controller for a 3.0 dm 3 Diesel Engine and Its Assessment through Model-in-the-Loop," Energies, MDPI, vol. 16(2), pages 1-23, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:907-:d:1034478
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    References listed on IDEAS

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    1. Stefano d’Ambrosio & Alessandro Mancarella & Andrea Manelli, 2022. "Utilization of Hydrotreated Vegetable Oil (HVO) in a Euro 6 Dual-Loop EGR Diesel Engine: Behavior as a Drop-In Fuel and Potentialities along Calibration Parameter Sweeps," Energies, MDPI, vol. 15(19), pages 1-17, September.
    2. Fabio Cococcetta & Roberto Finesso & Gilles Hardy & Omar Marello & Ezio Spessa, 2019. "Implementation and Assessment of a Model-Based Controller of Torque and Nitrogen Oxide Emissions in an 11 L Heavy-Duty Diesel Engine," Energies, MDPI, vol. 12(24), pages 1-19, December.
    3. Kalghatgi, Gautam, 2018. "Is it really the end of internal combustion engines and petroleum in transport?," Applied Energy, Elsevier, vol. 225(C), pages 965-974.
    4. Armin Norouzi & Hamed Heidarifar & Mahdi Shahbakhti & Charles Robert Koch & Hoseinali Borhan, 2021. "Model Predictive Control of Internal Combustion Engines: A Review and Future Directions," Energies, MDPI, vol. 14(19), pages 1-40, October.
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