IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i15p4008-d394007.html
   My bibliography  Save this article

Optimal Calibration Strategy of a Hybrid Electric Vehicle Equipped with an Ultra-Lean Pre-Chamber SI Engine for the Minimization of CO 2 and Pollutant Emissions

Author

Listed:
  • Fabio Bozza

    (Dipartimento di Ingegneria Industriale, Università di Napoli Federico II, 80125 Napoli, Italy)

  • Vincenzo De Bellis

    (Dipartimento di Ingegneria Industriale, Università di Napoli Federico II, 80125 Napoli, Italy)

  • Enrica Malfi

    (Dipartimento di Ingegneria Industriale, Università di Napoli Federico II, 80125 Napoli, Italy)

  • Luigi Teodosio

    (Dipartimento di Ingegneria Industriale, Università di Napoli Federico II, 80125 Napoli, Italy)

  • Daniela Tufano

    (Dipartimento di Ingegneria Industriale, Università di Napoli Federico II, 80125 Napoli, Italy)

Abstract

The complexity of modern hybrid powertrains poses new challenges for the optimal control concerning, on one hand, the thermal engine to maximize its efficiency, and, on the other hand, the vehicle to minimize the noxious emissions and CO 2 . In this context, the engine calibration has to be conducted by considering simultaneously the powertrain management, the vehicle characteristics, and the driving mission. In this work, a calibration methodology for a two-stage boosted ultra-lean pre-chamber spark ignition (SI) engine is proposed, aiming at minimizing its CO 2 and pollutant emissions. The engine features a flexible variable valve timing (VVT) control of the valves and an E-compressor, coupled in series to a turbocharger, to guarantee an adequate boost level needed for ultra-lean operation. The engine is simulated in a refined 1D model. A simplified methodology, based on a network of proportional integral derivative (PID) controllers, is presented for the calibration over the whole operating domain. Two calibration variants are proposed and compared, characterized by different fuel and electric consumptions: the first one aims to exclusively maximize the brake thermal efficiency, and the second one additionally considers the electric energy absorbed by the E-compressor and drained from the battery. After a verification against the outcomes of an automatic optimizer, the calibration strategies are assessed based on pollutant and CO 2 emissions along representative driving cycles by vehicle simulations. The results highlight slightly lower CO 2 emissions with the calibration approach that minimizes the E-compressor consumption, thus revealing the importance of considering the engine calibration phase, the powertrain management, the vehicle characteristics, and its mission.

Suggested Citation

  • Fabio Bozza & Vincenzo De Bellis & Enrica Malfi & Luigi Teodosio & Daniela Tufano, 2020. "Optimal Calibration Strategy of a Hybrid Electric Vehicle Equipped with an Ultra-Lean Pre-Chamber SI Engine for the Minimization of CO 2 and Pollutant Emissions," Energies, MDPI, vol. 13(15), pages 1-25, August.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:4008-:d:394007
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/15/4008/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/15/4008/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Millo, Federico & Rolando, Luciano & Fuso, Rocco & Zhao, Jianning, 2015. "Development of a new hybrid bus for urban public transportation," Applied Energy, Elsevier, vol. 157(C), pages 583-594.
    2. Teodosio, Luigi & Pirrello, Dino & Berni, Fabio & De Bellis, Vincenzo & Lanzafame, Rosario & D'Adamo, Alessandro, 2018. "Impact of intake valve strategies on fuel consumption and knock tendency of a spark ignition engine," Applied Energy, Elsevier, vol. 216(C), pages 91-104.
    3. Bozza, Fabio & De Bellis, Vincenzo & Teodosio, Luigi, 2016. "Potentials of cooled EGR and water injection for knock resistance and fuel consumption improvements of gasoline engines," Applied Energy, Elsevier, vol. 169(C), pages 112-125.
    4. Thiel, Christian & Perujo, Adolfo & Mercier, Arnaud, 2010. "Cost and CO2 aspects of future vehicle options in Europe under new energy policy scenarios," Energy Policy, Elsevier, vol. 38(11), pages 7142-7151, November.
    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. Viktor Dilber & Momir Sjerić & Rudolf Tomić & Josip Krajnović & Sara Ugrinić & Darko Kozarac, 2022. "Optimization of Pre-Chamber Geometry and Operating Parameters in a Turbulent Jet Ignition Engine," Energies, MDPI, vol. 15(13), pages 1-21, June.
    2. Saiteja, Pemmareddy & Ashok, B., 2022. "Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    3. Jacek Oskarbski & Krystian Birr & Karol Żarski, 2021. "Bicycle Traffic Model for Sustainable Urban Mobility Planning," Energies, MDPI, vol. 14(18), pages 1-36, September.

    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. Zhu, Zengqiang & Mu, Zhiqiang & Wei, Yanju & Du, Ruiheng & Guan, Wei & Liu, Shenghua, 2022. "Cylinder-to-cylinder variation of knock and effects of mixture formation on knock tendency for a heavy-duty spark ignition methanol engine," Energy, Elsevier, vol. 254(PA).
    2. d'Adamo, A. & Breda, S. & Berni, F. & Fontanesi, S., 2019. "The potential of statistical RANS to predict knock tendency: Comparison with LES and experiments on a spark-ignition engine," Applied Energy, Elsevier, vol. 249(C), pages 126-142.
    3. Serrano, José Ramón & Piqueras, Pedro & De la Morena, Joaquín & Gómez-Vilanova, Alejandro & Guilain, Stéphane, 2021. "Methodological analysis of variable geometry turbine technology impact on the performance of highly downsized spark-ignition engines," Energy, Elsevier, vol. 215(PB).
    4. Kley, Fabian & Lerch, Christian & Dallinger, David, 2011. "New business models for electric cars--A holistic approach," Energy Policy, Elsevier, vol. 39(6), pages 3392-3403, June.
    5. Karthic, S.V. & Senthil Kumar, M., 2021. "Experimental investigations on hydrogen biofueled reactivity controlled compression ignition engine using open ECU," Energy, Elsevier, vol. 229(C).
    6. Varga, Bogdan Ovidiu, 2013. "Electric vehicles, primary energy sources and CO2 emissions: Romanian case study," Energy, Elsevier, vol. 49(C), pages 61-70.
    7. Jacopo Zembi & Michele Battistoni & Francesco Ranuzzi & Nicolò Cavina & Matteo De Cesare, 2019. "CFD Analysis of Port Water Injection in a GDI Engine under Incipient Knock Conditions," Energies, MDPI, vol. 12(18), pages 1-22, September.
    8. Zhongqi Deng & Peng Tian, 2020. "Are China's subsidies for electric vehicles effective?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(4), pages 475-489, June.
    9. Weixing Liu & Hongtao Yi, 2020. "What Affects the Diffusion of New Energy Vehicles Financial Subsidy Policy? Evidence from Chinese Cities," IJERPH, MDPI, vol. 17(3), pages 1-15, January.
    10. Yong, Jia Ying & Ramachandaramurthy, Vigna K. & Tan, Kang Miao & Mithulananthan, N., 2015. "A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 365-385.
    11. Duan, Xiongbo & Liu, Jingping & Yao, Jun & Chen, Zheng & Wu, Cheng & Chen, Ceyuan & Dong, Hao, 2018. "Performance, combustion and knock assessment of a high compression ratio and lean-burn heavy-duty spark-ignition engine fuelled with n-butane and liquefied methane gas blend," Energy, Elsevier, vol. 158(C), pages 256-268.
    12. Gnann, Till & Plötz, Patrick & Kühn, André & Wietschel, Martin, 2015. "Modelling market diffusion of electric vehicles with real world driving data – German market and policy options," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 95-112.
    13. Ajanovic, Amela & Haas, Reinhard, 2016. "Dissemination of electric vehicles in urban areas: Major factors for success," Energy, Elsevier, vol. 115(P2), pages 1451-1458.
    14. Lin, Boqiang & Tan, Ruipeng, 2017. "Estimation of the environmental values of electric vehicles in Chinese cities," Energy Policy, Elsevier, vol. 104(C), pages 221-229.
    15. Samuel Pelletier & Ola Jabali & Gilbert Laporte, 2016. "50th Anniversary Invited Article—Goods Distribution with Electric Vehicles: Review and Research Perspectives," Transportation Science, INFORMS, vol. 50(1), pages 3-22, February.
    16. Zhao, Dan & Ji, Shou-feng & Wang, He-ping & Jiang, Li-wen, 2021. "How do government subsidies promote new energy vehicle diffusion in the complex network context? A three-stage evolutionary game model," Energy, Elsevier, vol. 230(C).
    17. Thiago Rodrigo Vieira da Silva & Nilton Antonio Diniz Netto & Jeanine Costa Santos & Augusto Cesar Teixeira Malaquias & José Guilherme Coelho Baêta, 2022. "Development Procedure for Performance Estimation and Main Dimensions Calculation of a Highly-Boosted Ethanol Engine with Water Injection," Energies, MDPI, vol. 15(13), pages 1-24, June.
    18. Wadud, Zia & Mattioli, Giulio, 2021. "Fully automated vehicles: A cost-based analysis of the share of ownership and mobility services, and its socio-economic determinants," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 228-244.
    19. Geir H. Bjertnæs, 2013. "Biofuel mandate versus favourable taxation of electric cars. The case of Norway," Discussion Papers 745, Statistics Norway, Research Department.
    20. Shafiei, Ehsan & Davidsdottir, Brynhildur & Leaver, Jonathan & Stefansson, Hlynur & Asgeirsson, Eyjolfur Ingi, 2015. "Comparative analysis of hydrogen, biofuels and electricity transitional pathways to sustainable transport in a renewable-based energy system," Energy, Elsevier, vol. 83(C), pages 614-627.

    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:13:y:2020:i:15:p:4008-:d:394007. 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.