IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i24p4704-d296269.html
   My bibliography  Save this article

Implementation and Assessment of a Model-Based Controller of Torque and Nitrogen Oxide Emissions in an 11 L Heavy-Duty Diesel Engine

Author

Listed:
  • Fabio Cococcetta

    (FPT Motorenforschung AG, Schlossgasse 2, 9320 Arbon, Switzerland)

  • Roberto Finesso

    (Department of Energy, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Gilles Hardy

    (FPT Motorenforschung AG, Schlossgasse 2, 9320 Arbon, Switzerland)

  • Omar Marello

    (Department of Energy, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Ezio Spessa

    (Department of Energy, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

Abstract

A previously developed model-based controller of torque and nitrogen oxides emissions has been implemented and assessed on a heavy-duty 11 L FPT prototype Cursor 11 diesel engine. The implementation has been realized by means of a rapid prototyping device, which has allowed the standard functions of the engine control unit to be by-passed. The activity was carried out within the IMPERIUM H2020 EU Project, which is aimed at reducing the consumption of fuel and urea in heavy-duty trucks up to 20%, while maintaining the compliance with the legal emission limits. In particular, the developed controller is able to achieve desired targets of brake mean effective pressure (BMEP) (or brake torque) and engine-out nitrogen oxides emissions. To this aim, the controller adjusts the fuel quantity and the start of injection of the main pulse in real-time. The controller is based on a previously developed low-throughput combustion model, which estimates the heat release rate, the in-cylinder pressure, the BMEP (or torque) and the engine-out nitrogen oxide emissions. The controller has been assessed at both steady-state and transient operations, through rapid prototyping tests at the engine test bench and on the road.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4704-:d:296269
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/24/4704/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/24/4704/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Song Hu & Stefano d’Ambrosio & Roberto Finesso & Andrea Manelli & Mario Rocco Marzano & Antonio Mittica & Loris Ventura & Hechun Wang & Yinyan Wang, 2019. "Comparison of Physics-Based, Semi-Empirical and Neural Network-Based Models for Model-Based Combustion Control in a 3.0 L Diesel Engine," Energies, MDPI, vol. 12(18), pages 1-41, September.
    2. Edgar Talavera & Alberto Díaz-Álvarez & Felipe Jiménez & José E. Naranjo, 2018. "Impact on Congestion and Fuel Consumption of a Cooperative Adaptive Cruise Control System with Lane-Level Position Estimation," Energies, MDPI, vol. 11(1), pages 1-17, January.
    3. Roberto Finesso & Daniela Misul & Ezio Spessa & Mattia Venditti, 2018. "Optimal Design of Power-Split HEVs Based on Total Cost of Ownership and CO 2 Emission Minimization," Energies, MDPI, vol. 11(7), pages 1-28, July.
    4. Roberto Finesso & Gilles Hardy & Alessandro Mancarella & Omar Marello & Antonio Mittica & Ezio Spessa, 2019. "Real-Time Simulation of Torque and Nitrogen Oxide Emissions in an 11.0 L Heavy-Duty Diesel Engine for Model-Based Combustion Control," Energies, MDPI, vol. 12(3), pages 1-32, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. Alessandro Mancarella & Omar Marello, 2022. "Effect of Coolant Temperature on Performance and Emissions of a Compression Ignition Engine Running on Conventional Diesel and Hydrotreated Vegetable Oil (HVO)," Energies, MDPI, vol. 16(1), pages 1-27, December.
    4. Stefano d’Ambrosio & Roberto Finesso & Gilles Hardy & Andrea Manelli & Alessandro Mancarella & Omar Marello & Antonio Mittica, 2021. "Model-Based Control of Torque and Nitrogen Oxide Emissions in a Euro VI 3.0 L Diesel Engine through Rapid Prototyping," Energies, MDPI, vol. 14(4), pages 1-25, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Can, Özer & Baklacioglu, Tolga & Özturk, Erkan & Turan, Onder, 2022. "Artificial neural networks modeling of combustion parameters for a diesel engine fueled with biodiesel fuel," Energy, Elsevier, vol. 247(C).
    2. Massimiliano Passalacqua & Mauro Carpita & Serge Gavin & Mario Marchesoni & Matteo Repetto & Luis Vaccaro & Sébastien Wasterlain, 2019. "Supercapacitor Storage Sizing Analysis for a Series Hybrid Vehicle," Energies, MDPI, vol. 12(9), pages 1-15, May.
    3. Stefano d’Ambrosio & Alessandro Ferrari & Alessandro Mancarella & Salvatore Mancò & Antonio Mittica, 2019. "Comparison of the Emissions, Noise, and Fuel Consumption Comparison of Direct and Indirect Piezoelectric and Solenoid Injectors in a Low-Compression-Ratio Diesel Engine," Energies, MDPI, vol. 12(21), pages 1-16, October.
    4. Changyin Dong & Hao Wang & Quan Chen & Daiheng Ni & Ye Li, 2019. "Simulation-Based Assessment of Multilane Separate Freeways at Toll Station Area: A Case Study from Huludao Toll Station on Shenshan Freeway," Sustainability, MDPI, vol. 11(11), pages 1-22, May.
    5. Maino, Claudio & Misul, Daniela & Musa, Alessia & Spessa, Ezio, 2021. "Optimal mesh discretization of the dynamic programming for hybrid electric vehicles," Applied Energy, Elsevier, vol. 292(C).
    6. Andrzej Łebkowski, 2018. "Reduction of Fuel Consumption and Pollution Emissions in Inland Water Transport by Application of Hybrid Powertrain," Energies, MDPI, vol. 11(8), pages 1-16, July.
    7. Stefano d’Ambrosio & Roberto Finesso & Gilles Hardy & Andrea Manelli & Alessandro Mancarella & Omar Marello & Antonio Mittica, 2021. "Model-Based Control of Torque and Nitrogen Oxide Emissions in a Euro VI 3.0 L Diesel Engine through Rapid Prototyping," Energies, MDPI, vol. 14(4), pages 1-25, February.
    8. Li, Haijian & Zhang, Junjie & Sun, Xiaoliang & Niu, Jun & Zhao, Xiaohua, 2022. "A survey of vehicle group behaviors simulation under a connected vehicle environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    9. Bao, Shuyue & Sun, Ping & Zhu, Jianxin & Ji, Qian & Liu, Junheng, 2022. "Improved multi-dimensional dynamic programming energy management strategy for a vehicle power-split hybrid powertrain," Energy, Elsevier, vol. 256(C).
    10. Anselma, Pier Giuseppe, 2022. "Electrified powertrain sizing for vehicle fleets of car makers considering total ownership costs and CO2 emission legislation scenarios," Applied Energy, Elsevier, vol. 314(C).
    11. Hu, Song & Guo, Bin & Ding, Shunliang & Yang, Fuyuan & Dang, Jian & Liu, Biao & Gu, Junjie & Ma, Jugang & Ouyang, Minggao, 2022. "A comprehensive review of alkaline water electrolysis mathematical modeling," Applied Energy, Elsevier, vol. 327(C).
    12. Roberto Finesso & Gilles Hardy & Alessandro Mancarella & Omar Marello & Antonio Mittica & Ezio Spessa, 2019. "Real-Time Simulation of Torque and Nitrogen Oxide Emissions in an 11.0 L Heavy-Duty Diesel Engine for Model-Based Combustion Control," Energies, MDPI, vol. 12(3), pages 1-32, January.
    13. Ma, Fangwu & Yang, Yu & Wang, Jiawei & Liu, Zhenze & Li, Jinhang & Nie, Jiahong & Shen, Yucheng & Wu, Liang, 2019. "Predictive energy-saving optimization based on nonlinear model predictive control for cooperative connected vehicles platoon with V2V communication," Energy, Elsevier, vol. 189(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4704-:d:296269. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.