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Advanced prediction of combustion phasing in methane homogeneous engines via in-cylinder ion current profiling and a novel ionic kinetics framework
Advanced prediction of combustion phasing in methane homogeneous engines via in-cylinder ion current profiling and a novel ionic kinetics framework
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Advanced prediction of combustion phasing in methane homogeneous engines via in-cylinder ion current profiling and a novel ionic kinetics framework
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Advanced prediction of combustion phasing in methane homogeneous engines via in-cylinder ion current profiling and a novel ionic kinetics framework
Advanced prediction of combustion phasing in methane homogeneous engines via in-cylinder ion current profiling and a novel ionic kinetics framework

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Advanced prediction of combustion phasing in methane homogeneous engines via in-cylinder ion current profiling and a novel ionic kinetics framework
Advanced prediction of combustion phasing in methane homogeneous engines via in-cylinder ion current profiling and a novel ionic kinetics framework
Journal Article

Advanced prediction of combustion phasing in methane homogeneous engines via in-cylinder ion current profiling and a novel ionic kinetics framework

2025
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Overview
This study presents a reduced ionic chemical kinetics mechanism for predicting combustion phasing in methane-fueled homogeneous charge compression ignition (HCCI) engines. Starting from the detailed GRI-Mech 3.0 mechanism, a reduced scheme with 22 species and 48 reactions was developed. Ionic reactions were then added, forming a comprehensive mechanism with 27 species and 54 reactions. The mechanism was integrated into a multi-zone combustion model and validated against experimental data from a CFR engine under four operating conditions. Results show that the mechanism accurately predicts the start of combustion (SOC), with a maximum error below 0.09%. In-cylinder pressure and temperature profiles closely match experimental data. The model also captures the behavior of key radicals and ions, including H₃O⁺, OH⁻, and O₂⁻. Exhaust emissions such as CO and CO₂ are predicted with relative errors under 12%, while UHC predictions show moderate discrepancies. Notably, electrons are fully consumed during combustion, while some ions remain in the exhaust. The proposed mechanism offers a reliable and computationally efficient tool for combustion diagnostics and control, with potential applications in low-temperature and fuel-flexible engine technologies.