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The Synergy between Methanol M100 and Plasma-Assisted Ignition System PAI to Achieve Increasingly Leaner Mixtures in a Single-Cylinder Engine

Author

Listed:
  • Federico Ricci

    (Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, PG, Italy)

  • Francesco Mariani

    (Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, PG, Italy)

  • Stefano Papi

    (Federal-Mogul Powertrain Italy, Via della Scienza, 6/8, 41012 Carpi, MO, Italy)

  • Jacopo Zembi

    (Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, PG, Italy)

  • Michele Battistoni

    (Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, PG, Italy)

  • Carlo Nazareno Grimaldi

    (Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, PG, Italy)

Abstract

Currently, conventional spark–ignition engines face challenges in meeting the ever-growing demands of customers and increasingly stringent regulations regarding pollutant emissions. A combination of innovative strategies and carbon-neutral fuels is deemed necessary in order to further reduce fuel consumption and minimize engine emissions. The present work aims to assess the performance of combustion strategies using low-carbon-content fuel, such as methanol M100, ignited by a plasma-assisted igniter (PAI) under ultra-lean conditions. The experimental campaign is conducted on a single-cylinder research engine at 1000 rpm and low loads, moving up to the engine lean stable limits. The specific purpose of this work is to determine the benefits brought by the proposed strategy, referred to as M100–PAI, which compared market gasoline E5 ignited by the PAI system and conventional spark. The synergy between M100 (methanol) and Plasma-Assisted Ignition (PAI) in internal combustion engines yielded notable benefits. This combination significantly improved combustion stability if compared to the other combinations tested, by extending the lean stable limit to λ = 2.0, reducing cycle-to-cycle variability, and facilitating faster flame front acceleration, resulting in enhanced homogeneity. These enhancements, obtained with the combination M100–PAI, contributed to higher fuel efficiency, showing a 10% efficiency gain over the combination E5–gasoline spark ignition. The findings highlight the potential of innovative combustion strategies using low-carbon fuels and advanced ignition systems to meet stringent emissions regulations while improving engine performance.

Suggested Citation

  • Federico Ricci & Francesco Mariani & Stefano Papi & Jacopo Zembi & Michele Battistoni & Carlo Nazareno Grimaldi, 2024. "The Synergy between Methanol M100 and Plasma-Assisted Ignition System PAI to Achieve Increasingly Leaner Mixtures in a Single-Cylinder Engine," Energies, MDPI, vol. 17(7), pages 1-14, March.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:7:p:1659-:d:1367373
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    References listed on IDEAS

    as
    1. Discepoli, G. & Cruccolini, V. & Ricci, F. & Di Giuseppe, A. & Papi, S. & Grimaldi, C.N., 2020. "Experimental characterisation of the thermal energy released by a Radio-Frequency Corona Igniter in nitrogen and air," Applied Energy, Elsevier, vol. 263(C).
    2. Masurier, J.-B. & Foucher, F. & Dayma, G. & Dagaut, P., 2015. "Ozone applied to the homogeneous charge compression ignition engine to control alcohol fuels combustion," Applied Energy, Elsevier, vol. 160(C), pages 566-580.
    3. Jung, Dongwon & Sasaki, Kosaku & Iida, Norimasa, 2017. "Effects of increased spark discharge energy and enhanced in-cylinder turbulence level on lean limits and cycle-to-cycle variations of combustion for SI engine operation," Applied Energy, Elsevier, vol. 205(C), pages 1467-1477.
    4. Jung, Dongwon & Iida, Norimasa, 2018. "An investigation of multiple spark discharge using multi-coil ignition system for improving thermal efficiency of lean SI engine operation," Applied Energy, Elsevier, vol. 212(C), pages 322-332.
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    Cited by:

    1. Federico Ricci & Massimiliano Avana & Francesco Mariani, 2025. "Artificial Neural Networks as a Tool for High-Accuracy Prediction of In-Cylinder Pressure and Equivalent Flame Radius in Hydrogen-Fueled Internal Combustion Engines," Energies, MDPI, vol. 18(2), pages 1-23, January.
    2. Yongzhi Li & Zhi Zhang & Haifeng Liu & Weide Chang & Zanqiao Shu & Hu Wang & Zunqing Zheng & Hua Zhao & Xinyan Wang & Mingfa Yao, 2025. "Experimental and Simulation Study on Reducing the Liquid Film and Improving the Performance of a Carbon-Neutral Methanol Engine," Energies, MDPI, vol. 18(2), pages 1-23, January.

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