A

Development of a Comprehensive Predictive QD Knock Simulation Model for Hydrogen, Methanol, and an Ammonia–Hydrogen Blend

SAE International Journal of Advances and Current Practices in Mobility, vol. 08, pp. 1023–1034

Abstract

To support the transition toward climate-neutral mobility and power generation, internal combustion engines (ICEs) must operate efficiently on renewable, carbon-neutral fuels. Hydrogen, methanol, and ammonia-hydrogen blends are promising candidates due to their favorable production pathways and combustion properties. However, their knock behavior differs significantly from conventional fuels, requiring dedicated simulation tools. This work presents a modeling framework based on quasi-dimensional (QD) engine simulation, including two separate knock prediction models. The first model predicts the knock boundary of a given operating point and combines an auto-ignition model with a knock criterion. The overall methodology was originally developed for gasoline and is here adapted to hydrogen, methanol, and ammonia-hydrogen blends. For this purpose, the relevant fuel properties were incorporated into the auto-ignition model, and a suitable knock criterion was identified that applies to all investigated fuels. The model was validated using experimental data from single-cylinder engine tests. In addition, two entirely new modeling approaches were developed to predict statistical knock values, specifically knock frequency and knock intensity. Each model was calibrated once per fuel and subsequently validated across a wide range of conditions. The results show that the adapted knock boundary model and the new statistical model accurately capture the knock behavior of hydrogen, methanol, and ammonia-hydrogen blends. The methodology enables predictive knock analysis using QD simulation and supports the development of robust, high-efficiency ICEs for future carbon-neutral applications.

Authors 11

  1. University of Stuttgart

    Affiliation as printed

    University of Stuttgart

  2. Research Institute of Automotive Engineering and Vehicle Engines Stuttgart

    Affiliation as printed

    FKFS

  3. Research Institute of Automotive Engineering and Vehicle Engines Stuttgart

    Affiliation as printed

    FKFS

  4. University of Stuttgart

    Affiliation as printed

    University of Stuttgart

  5. Lukas Plum Aachen

    RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University

  6. RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University

  7. RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University

  8. RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University

  9. Université d'Orléans

    Affiliation as printed

    University of Orleans

  10. Université d'Orléans

    Affiliation as printed

    University of Orleans

  11. Université d'Orléans

    Affiliation as printed

    University of Orleans

Cited by 1 stored of 1

1 result

No patents citing this paper on Lens.org (checked 2026-10-06).

References 9

9 results