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A RANS knock model to predict the statistical occurrence of engine knock

Author

Listed:
  • d'Adamo, Alessandro
  • Breda, Sebastiano
  • Fontanesi, Stefano
  • Irimescu, Adrian
  • Merola, Simona Silvia
  • Tornatore, Cinzia

Abstract

In the recent past engine knock emerged as one of the main limiting aspects for the achievement of higher efficiency targets in modern spark-ignition (SI) engines. To attain these requirements, engine operating points must be moved as close as possible to the onset of abnormal combustions, although the turbulent nature of flow field and SI combustion leads to possibly ample fluctuations between consecutive engine cycles. This forces engine designers to distance the target condition from its theoretical optimum in order to prevent abnormal combustion, which can potentially damage engine components because of few individual heavy-knocking cycles.

Suggested Citation

  • d'Adamo, Alessandro & Breda, Sebastiano & Fontanesi, Stefano & Irimescu, Adrian & Merola, Simona Silvia & Tornatore, Cinzia, 2017. "A RANS knock model to predict the statistical occurrence of engine knock," Applied Energy, Elsevier, vol. 191(C), pages 251-263.
    • Handle: RePEc:eee:appene:v:191:y:2017:i:c:p:251-263
    DOI: 10.1016/j.apenergy.2017.01.101
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    References listed on IDEAS

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    4. Irimescu, Adrian & Merola, Simona Silvia & Valentino, Gerardo, 2016. "Application of an entrainment turbulent combustion model with validation based on the distribution of chemical species in an optical spark ignition engine," Applied Energy, Elsevier, vol. 162(C), pages 908-923.
    5. Irimescu, Adrian & Merola, Simona Silvia & Tornatore, Cinzia & Valentino, Gerardo, 2015. "Development of a semi-empirical convective heat transfer correlation based on thermodynamic and optical measurements in a spark ignition engine," Applied Energy, Elsevier, vol. 157(C), pages 777-788.
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    1. Chen, Ceyuan & Pal, Pinaki & Ameen, Muhsin & Feng, Dengquan & Wei, Haiqiao, 2020. "Large-eddy simulation study on cycle-to-cycle variation of knocking combustion in a spark-ignition engine," Applied Energy, Elsevier, vol. 261(C).
    2. Wang, Chenyao & Zhang, Fujun & Wang, Enhua & Yu, Chuncun & Gao, Hongli & Liu, Bolan & Zhao, Zhenfeng & Zhao, Changlu, 2019. "Experimental study on knock suppression of spark-ignition engine fuelled with kerosene via water injection," Applied Energy, Elsevier, vol. 242(C), pages 248-259.
    3. Simona Silvia Merola & Adrian Irimescu & Silvana Di Iorio & Bianca Maria Vaglieco, 2017. "Effect of Fuel Injection Strategy on the Carbonaceous Structure Formation and Nanoparticle Emission in a DISI Engine Fuelled with Butanol," Energies, MDPI, vol. 10(7), pages 1-19, June.
    4. Yue, Zongyu & Som, Sibendu, 2021. "Fuel property effects on knock propensity and thermal efficiency in a direct-injection spark-ignition engine," Applied Energy, Elsevier, vol. 281(C).
    5. Engelmann, L. & Welch, C. & Schmidt, M. & Meller, D. & Wollny, P. & Böhm, B. & Dreizler, A. & Kempf, A., 2023. "A temporal fluid-parcel backwards-tracing method for Direct-Numerical and Large-Eddy Simulation employing Lagrangian particles," Applied Energy, Elsevier, vol. 342(C).
    6. 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.
    7. Lijia Zhong & Changwen Liu, 2019. "Numerical Analysis of End-Gas Autoignition and Pressure Oscillation in a Downsized SI Engine Using Large Eddy Simulation," Energies, MDPI, vol. 12(20), pages 1-20, October.
    8. Guardiola, C. & Pla, B. & Bares, P. & Barbier, A., 2018. "An analysis of the in-cylinder pressure resonance excitation in internal combustion engines," Applied Energy, Elsevier, vol. 228(C), pages 1272-1279.
    9. 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.
    10. Alessandro d’Adamo & Clara Iacovano & Stefano Fontanesi, 2021. "A Data-Driven Methodology for the Simulation of Turbulent Flame Speed across Engine-Relevant Combustion Regimes," Energies, MDPI, vol. 14(14), pages 1-17, July.
    11. Cao, Jiale & Li, Tie & Huang, Shuai & Chen, Run & Li, Shiyan & Kuang, Min & Yang, Rundai & Huang, Yating, 2023. "Co-optimization of miller degree and geometric compression ratio of a large-bore natural gas generator engine with novel Knock models and machine learning," Applied Energy, Elsevier, vol. 352(C).

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