Evaluation of a dual-pulse smart ignition coil diagnostic strategy for real-time combustion monitoring and anomaly detection

Reliable combustion monitoring is essential for advanced control of spark-ignition engines, particularly when combustion anomalies and ignition-system degradation affect performance and stability. This study experimentally evaluates a smart ignition coil developed by Champion Ignition for real-time detection of combustion anomalies in a conventional gasoline spark-ignition engine. The diagnostic approach relies on time-resolved electrical signals generated during spark discharge and subsequent diagnostic events, which reflect in-cylinder combustion conditions. Experiments were performed on a production-derived, turbocharged three-cylinder SMART W451T engine (999 cc, compression ratio 10:1, port fuel injection) fueled with E5 gasoline. The methodology was assessed by detecting abnormal combustion events and by quantitatively evaluating its sensitivity to representative spark plug aging and fouling conditions while systematically varying key parameters, including coil dwell time and diagnostic timing. The results show that the smart coil's integrated diagnostic signals correlate strongly with combustion state, enabling effective detection of abnormal combustion events and providing distinct quantitative dual-pulse signatures for representative spark plug aging and fouling conditions without complex signal processing or additional sensors. These findings demonstrate the potential of ignition-coil-based diagnostics as a complementary approach to established combustion-monitoring techniques in conventional spark-ignition engines.

Authors

Institutions

Publication Details

Journal
Fuel Processing Technology
Published
2026-09-15
DOI
https://doi.org/10.1016/j.fuproc.2026.108586
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
article

Evaluation of a dual-pulse smart ignition coil diagnostic strategy for real-time combustion monitoring and anomaly detection

Michele Battistoni, Jacopo Zembi, Carlo N. Grimaldi, Stefano Papi et al.
Fuel Processing Technology
Advanced Combustion Engine Technologies
article

Evaluation of a dual-pulse smart ignition coil diagnostic strategy for real-time combustion monitoring and anomaly detection

Michele Battistoni, Jacopo Zembi, Carlo N. Grimaldi, Stefano Papi, Federico Ricci, Massimiliano Avana, Massimo Dal Re
article en

Abstract

Reliable combustion monitoring is essential for advanced control of spark-ignition engines, particularly when combustion anomalies and ignition-system degradation affect performance and stability. This study experimentally evaluates a smart ignition coil developed by Champion Ignition for real-time detection of combustion anomalies in a conventional gasoline spark-ignition engine. The diagnostic approach relies on time-resolved electrical signals generated during spark discharge and subsequent diagnostic events, which reflect in-cylinder combustion conditions. Experiments were performed on a production-derived, turbocharged three-cylinder SMART W451T engine (999 cc, compression ratio 10:1, port fuel injection) fueled with E5 gasoline. The methodology was assessed by detecting abnormal combustion events and by quantitatively evaluating its sensitivity to representative spark plug aging and fouling conditions while systematically varying key parameters, including coil dwell time and diagnostic timing. The results show that the smart coil's integrated diagnostic signals correlate strongly with combustion state, enabling effective detection of abnormal combustion events and providing distinct quantitative dual-pulse signatures for representative spark plug aging and fouling conditions without complex signal processing or additional sensors. These findings demonstrate the potential of ignition-coil-based diagnostics as a complementary approach to established combustion-monitoring techniques in conventional spark-ignition engines.

Fuel Processing TechnologyVol. 292
University of Perugia (IT), Tenneco (United States) (US)
Affordable and clean energy
Openalex Percentile: Top 20%
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.