IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i2p295-d128975.html
   My bibliography  Save this article

Analysis of the Effect of Vehicle, Driving and Road Parameters on the Transient Performance and Emissions of a Turbocharged Truck

Author

Listed:
  • Evangelos G. Giakoumis

    (Internal Combustion Engines Laboratory, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece)

  • George Triantafillou

    (Internal Combustion Engines Laboratory, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece)

Abstract

In this paper, a fundamental analysis of the effects of various influential parameters on the performance and emissions of a turbocharged truck operating under transient conditions is presented. The results derive from a detailed vehicle model that comprises two parts. The first is an engine performance and emissions module that follows a mapping approach, with experimentally derived correction coefficients employed to account for transient discrepancies; this is then coupled to a comprehensive vehicle model that takes into account various vehicle operation attributes such as gearbox, tires, tire slip, etc. Soot, as well as nitrogen monoxide, are the examined engine-out pollutants, together with fuel consumption and carbon dioxide. The parameters examined are vehicular (mass and gearbox), driving (driver ‘aggressiveness’ and gear-shift profile) and road (type and grade). From the range of values investigated, the most critical parameters for the emission of NO and soot are vehicle mass, driving ‘aggressiveness’ and the exact gear-change profile. Vehicle mass, driving ‘aggressiveness’ and road-grade were identified as the most influential parameters for the emission of CO 2 . A notable statistical correlation was established between pollutant emissions (NO, soot) and vehicle mass or road-tire friction, as well as between fueling/CO 2 and vehicle mass, road-tire friction and road grade. It is believed that the results obtained shed light into the effect of critical operating parameters on the engine-out emissions of a truck/bus, underlining at the same time the peculiarities of transient operating conditions.

Suggested Citation

  • Evangelos G. Giakoumis & George Triantafillou, 2018. "Analysis of the Effect of Vehicle, Driving and Road Parameters on the Transient Performance and Emissions of a Turbocharged Truck," Energies, MDPI, vol. 11(2), pages 1-21, January.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:2:p:295-:d:128975
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/2/295/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/11/2/295/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Jinghui & Rakha, Hesham A., 2016. "Fuel consumption model for conventional diesel buses," Applied Energy, Elsevier, vol. 170(C), pages 394-402.
    2. Bishop, Justin D.K. & Stettler, Marc E.J. & Molden, N. & Boies, Adam M., 2016. "Engine maps of fuel use and emissions from transient driving cycles," Applied Energy, Elsevier, vol. 183(C), pages 202-217.
    3. Evangelos G. Giakoumis & Alexandros T. Zachiotis, 2017. "Investigation of a Diesel-Engined Vehicle’s Performance and Emissions during the WLTC Driving Cycle—Comparison with the NEDC," Energies, MDPI, vol. 10(2), pages 1-19, February.
    4. Roy, Sumit & Banerjee, Rahul & Bose, Probir Kumar, 2014. "Performance and exhaust emissions prediction of a CRDI assisted single cylinder diesel engine coupled with EGR using artificial neural network," Applied Energy, Elsevier, vol. 119(C), pages 330-340.
    5. Çelik, Veli & Arcaklioglu, Erol, 2005. "Performance maps of a diesel engine," Applied Energy, Elsevier, vol. 81(3), pages 247-259, July.
    6. Tsokolis, D. & Tsiakmakis, S. & Dimaratos, A. & Fontaras, G. & Pistikopoulos, P. & Ciuffo, B. & Samaras, Z., 2016. "Fuel consumption and CO2 emissions of passenger cars over the New Worldwide Harmonized Test Protocol," Applied Energy, Elsevier, vol. 179(C), pages 1152-1165.
    7. Giakoumis, E.G. & Alafouzos, A.I., 2010. "Study of diesel engine performance and emissions during a Transient Cycle applying an engine mapping-based methodology," Applied Energy, Elsevier, vol. 87(4), pages 1358-1365, April.
    8. Tang, Yuanyuan & Zhang, Jundong & Gan, Huibing & Jia, Baozhu & Xia, Yu, 2017. "Development of a real-time two-stroke marine diesel engine model with in-cylinder pressure prediction capability," Applied Energy, Elsevier, vol. 194(C), pages 55-70.
    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. E, Jiaqiang & Liu, Guanlin & Zhang, Zhiqing & Han, Dandan & Chen, Jingwei & Wei, Kexiang & Gong, Jinke & Yin, Zibin, 2019. "Effect analysis on cold starting performance enhancement of a diesel engine fueled with biodiesel fuel based on an improved thermodynamic model," Applied Energy, Elsevier, vol. 243(C), pages 321-335.

    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. Bishop, Justin D.K. & Stettler, Marc E.J. & Molden, N. & Boies, Adam M., 2016. "Engine maps of fuel use and emissions from transient driving cycles," Applied Energy, Elsevier, vol. 183(C), pages 202-217.
    2. Evangelos G. Giakoumis & Alexandros T. Zachiotis, 2017. "Investigation of a Diesel-Engined Vehicle’s Performance and Emissions during the WLTC Driving Cycle—Comparison with the NEDC," Energies, MDPI, vol. 10(2), pages 1-19, February.
    3. Rosero, Fredy & Fonseca, Natalia & López, José-María & Casanova, Jesús, 2020. "Real-world fuel efficiency and emissions from an urban diesel bus engine under transient operating conditions," Applied Energy, Elsevier, vol. 261(C).
    4. Mera, Zamir & Varella, Roberto & Baptista, Patrícia & Duarte, Gonçalo & Rosero, Fredy, 2022. "Including engine data for energy and pollutants assessment into the vehicle specific power methodology," Applied Energy, Elsevier, vol. 311(C).
    5. Alexandros T. Zachiotis & Evangelos G. Giakoumis, 2021. "Monte Carlo Simulation Methodology to Assess the Impact of Ambient Wind on Emissions from a Light-Commercial Vehicle Running on the Worldwide-Harmonized Light-Duty Vehicles Test Cycle (WLTC)," Energies, MDPI, vol. 14(3), pages 1-24, January.
    6. Wang, An & Tu, Ran & Xu, Junshi & Zhai, Zhiqiang & Hatzopoulou, Marianne, 2022. "A novel modal emission modelling approach and its application with on-road emission measurements," Applied Energy, Elsevier, vol. 306(PA).
    7. Jarosław Ziółkowski & Mateusz Oszczypała & Jerzy Małachowski & Joanna Szkutnik-Rogoż, 2021. "Use of Artificial Neural Networks to Predict Fuel Consumption on the Basis of Technical Parameters of Vehicles," Energies, MDPI, vol. 14(9), pages 1-23, May.
    8. Pirjola, Liisa & Kuuluvainen, Heino & Timonen, Hilkka & Saarikoski, Sanna & Teinilä, Kimmo & Salo, Laura & Datta, Arindam & Simonen, Pauli & Karjalainen, Panu & Kulmala, Kari & Rönkkö, Topi, 2019. "Potential of renewable fuel to reduce diesel exhaust particle emissions," Applied Energy, Elsevier, vol. 254(C).
    9. Roy, Sumit & Ghosh, Ashmita & Das, Ajoy Kumar & Banerjee, Rahul, 2015. "Development and validation of a GEP model to predict the performance and exhaust emission parameters of a CRDI assisted single cylinder diesel engine coupled with EGR," Applied Energy, Elsevier, vol. 140(C), pages 52-64.
    10. S. M. Ashrafur Rahman & I. M. Rizwanul Fattah & Hwai Chyuan Ong & Fajle Rabbi Ashik & Mohammad Mahmudul Hassan & Md Tausif Murshed & Md Ashraful Imran & Md Hamidur Rahman & Md Akibur Rahman & Mohammad, 2021. "State-of-the-Art of Establishing Test Procedures for Real Driving Gaseous Emissions from Light- and Heavy-Duty Vehicles," Energies, MDPI, vol. 14(14), pages 1-32, July.
    11. Eckert, Jony Javorski & Silva, Fabrício L. & da Silva, Samuel Filgueira & Bueno, André Valente & de Oliveira, Mona Lisa Moura & Silva, Ludmila C.A., 2022. "Optimal design and power management control of hybrid biofuel–electric powertrain," Applied Energy, Elsevier, vol. 325(C).
    12. Miranda, Matheus H.R. & Silva, Fabrício L. & Lourenço, Maria A.M. & Eckert, Jony J. & Silva, Ludmila C.A., 2022. "Vehicle drivetrain and fuzzy controller optimization using a planar dynamics simulation based on a real-world driving cycle," Energy, Elsevier, vol. 257(C).
    13. Sasanka Katreddi & Sujan Kasani & Arvind Thiruvengadam, 2022. "A Review of Applications of Artificial Intelligence in Heavy Duty Trucks," Energies, MDPI, vol. 15(20), pages 1-20, October.
    14. 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.
    15. Purnell, K. & Bruce, A.G. & MacGill, I., 2022. "Impacts of electrifying public transit on the electricity grid, from regional to state level analysis," Applied Energy, Elsevier, vol. 307(C).
    16. Salvo, Orlando de & Vaz de Almeida, Flávio G., 2019. "Influence of technologies on energy efficiency results of official Brazilian tests of vehicle energy consumption," Applied Energy, Elsevier, vol. 241(C), pages 98-112.
    17. Xu, Jiamin & Zhang, Caizhi & Fan, Ruijia & Bao, Huanhuan & Wang, Yi & Huang, Shulong & Chin, Cheng Siong & Li, Congxin, 2020. "Modelling and control of vehicle integrated thermal management system of PEM fuel cell vehicle," Energy, Elsevier, vol. 199(C).
    18. Lotfan, S. & Ghiasi, R. Akbarpour & Fallah, M. & Sadeghi, M.H., 2016. "ANN-based modeling and reducing dual-fuel engine’s challenging emissions by multi-objective evolutionary algorithm NSGA-II," Applied Energy, Elsevier, vol. 175(C), pages 91-99.
    19. Zhongchang Liu & Xing Yuan & Jing Tian & Yongqiang Han & Runzhao Li & Guanlong Gao, 2018. "Investigation of Sectional-Stage Loading Strategies on a Two-Stage Turbocharged Heavy-Duty Diesel Engine under Transient Operation with EGR," Energies, MDPI, vol. 11(1), pages 1-19, January.
    20. Feng Mao & Zhiheng Li & Kai Zhang, 2021. "A Comparison of Carbon Dioxide Emissions between Battery Electric Buses and Conventional Diesel Buses," Sustainability, MDPI, vol. 13(9), pages 1-15, May.

    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:11:y:2018:i:2:p:295-:d:128975. 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.