[Paper Review] Detailed kinetic models for the low-temperature auto ignition of gasoline surrogates

Roda Bounaceur, Pierre‐Alexandre Glaude+3 more|ArXiv.org|Apr 20, 2009

Advanced Combustion Engine Technologies6 citations

TL;DR

This paper presents a detailed kinetic model for low-temperature autoignition of gasoline surrogates composed of n-heptane, iso-octane, hexene isomers, and toluene, using a mechanism based on existing literature and validated against rapid compression machine experiments. The model accurately predicts reactivity trends across binary, ternary, and quaternary blends, showing a retarding effect with increasing chain branching in hexene isomers, with predictions closely matching pure iso-octane behavior in quaternary mixtures.

ABSTRACT

In the context of the search for gasoline surrogates for kinetic modeling purpose, this paper describes a new model for the low-temperature auto-ignition of n-heptane/iso-octane/hexene/toluene blends for the different linear isomers of hexene. The model simulates satisfactory experimental results obtained in a rapid compression machine for temperatures ranging from 650 to 850 K in the case of binary and ternary mixtures including iso octane, 1-hexene and toluene. Predictive simulations have also been performed for the autoignition of n heptane/iso octane/hexene/toluene quaternary mixtures: the predicted reactivity is close to that of pure iso octane with a retarding effect when going from 1- to 3-alkene.

Motivation & Objective

• To develop a comprehensive kinetic mechanism for low-temperature autoignition of gasoline surrogates containing n-heptane, iso-octane, hexene isomers, and toluene.
• To accurately simulate experimental autoignition data from rapid compression machines across a range of temperatures (650–850 K).
• To investigate the reactivity trends in binary, ternary, and quaternary mixtures, particularly the influence of hexene isomer structure.
• To evaluate the predictive capability of the model for complex, real-fuel-like blends.

Proposed method

• The model integrates existing mechanisms for n-heptane, iso-octane, toluene, and 1-hexene, with additional pathways for other hexene isomers.
• Reaction pathways are derived from existing literature and validated against experimental data from rapid compression machines.
• The mechanism includes detailed elementary reactions for low-temperature oxidation, including peroxy radical isomerizations and decomposition steps.
• The model is implemented in a chemical kinetic framework and simulated using detailed numerical integration.
• Reactivity is evaluated by comparing predicted ignition delay times with experimental measurements.
• Sensitivity analysis and mechanism validation are performed across multiple blend compositions and temperatures.

Experimental results

Research questions

• RQ1 How accurately can the model predict low-temperature autoignition delays in n-heptane/iso-octane/hexene/toluene blends across 650–850 K?
• RQ2 What is the effect of hexene isomer structure (1-hexene vs. 3-hexene) on autoignition reactivity in binary and ternary mixtures?
• RQ3 How does the addition of toluene influence the ignition behavior of n-heptane/iso-octane/hexene blends?
• RQ4 To what extent does the model predict the reactivity of quaternary mixtures with respect to pure iso-octane?
• RQ5 Can the model capture the retarding effect of branched hexene isomers on autoignition timing?

Key findings

• The model successfully reproduces experimental ignition delay times in binary and ternary mixtures of iso-octane, 1-hexene, and toluene across the 650–850 K range.
• For quaternary mixtures, the predicted reactivity closely matches that of pure iso-octane, indicating a dominant influence of iso-octane on ignition behavior.
• A retarding effect on autoignition is observed when transitioning from 1-hexene to 3-hexene isomers, consistent with lower reactivity of branched alkenes.
• The model captures the complex interplay between fuel components, particularly the inhibition effect of toluene on low-temperature reactivity.
• The mechanism demonstrates predictive capability for complex, real-fuel-like blends, supporting its use in advanced combustion modeling.