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

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-12-24
DOI
https://doi.org/10.1038/s41598-025-28182-4
Primary Topic
Advanced Combustion Engine Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Damon Honnery, Elaheh Neshat, Amin Motevali Imami
Scientific Reports
Advanced Combustion Engine Technologies
article

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

Damon Honnery, Elaheh Neshat, Amin Motevali Imami
article en

Abstract

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.

Scientific ReportsVol. 15(1)
Sahand University of Technology (IR), Monash University (AU)
Affordable and clean energy
Openalex Percentile: Top 48%
Advanced Combustion Engine Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Advanced prediction of combustion phasing in methane homogeneous engines via in-cylinder ion current profiling and a novel ionic kinetics framework — Damon Honnery, Elaheh Neshat, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS