Development of a Riemann variables-based technique for on-line fuel injected mass evaluation in direct injection systems

On-line evaluation of injected fuel mass based on physical principles offers the potential for accurate and rapid feedback on actual injection quantities. High-accuracy pressure transducers are commonly used as primary sensors to provide inputs for model-based virtual flowmeters. While increasing the number of transducers allows for a more comprehensive analysis of elementary waves within the system, balancing measurement accuracy and economic efficiency is essential for industrial applications. In this study, a physics-based technique requiring only a single pressure sensor on the injector-feeding pipe is proposed, considering two elementary waves. The algorithm employs a predefined signal that exploits quasi-constant Riemann variables propagating from the rail to the injector, enabling accurate estimation of the flow-rate and mass entering the injector. Correlation relationships are then used to convert the entering mass into the injected mass. This approach achieves an estimation accuracy within 2 mg for single injection events. The proposed method is benchmarked against a previously developed flowmeter utilizing two pressure sensors, demonstrating that comparable accuracy can be obtained with a more economical single-sensor setup. The algorithm is applicable across a wide range of injection sizes and working conditions, offering a practical solution for real-time injected mass evaluation and control in high-pressure fuel systems.

Authors

Institutions

Publication Details

Journal
International Journal of Engine Research
Published
2025-10-18
DOI
https://doi.org/10.1177/14680874251378395
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

Development of a Riemann variables-based technique for on-line fuel injected mass evaluation in direct injection systems

Alessandro Ferrari, Oscar Vento, Tantan Zhang
International Journal of Engine Research
Advanced Combustion Engine Technologies
article

Development of a Riemann variables-based technique for on-line fuel injected mass evaluation in direct injection systems

Alessandro Ferrari, Oscar Vento, Tantan Zhang
article en

Abstract

On-line evaluation of injected fuel mass based on physical principles offers the potential for accurate and rapid feedback on actual injection quantities. High-accuracy pressure transducers are commonly used as primary sensors to provide inputs for model-based virtual flowmeters. While increasing the number of transducers allows for a more comprehensive analysis of elementary waves within the system, balancing measurement accuracy and economic efficiency is essential for industrial applications. In this study, a physics-based technique requiring only a single pressure sensor on the injector-feeding pipe is proposed, considering two elementary waves. The algorithm employs a predefined signal that exploits quasi-constant Riemann variables propagating from the rail to the injector, enabling accurate estimation of the flow-rate and mass entering the injector. Correlation relationships are then used to convert the entering mass into the injected mass. This approach achieves an estimation accuracy within 2 mg for single injection events. The proposed method is benchmarked against a previously developed flowmeter utilizing two pressure sensors, demonstrating that comparable accuracy can be obtained with a more economical single-sensor setup. The algorithm is applicable across a wide range of injection sizes and working conditions, offering a practical solution for real-time injected mass evaluation and control in high-pressure fuel systems.

International Journal of Engine Research
Hunan University (CN), Politecnico di Torino (IT)
Openalex Percentile: Top 73%
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.