Advancing Fuel Spray Characterization: A Machine Learning Approach for Directly Injected Gasoline Fuel Sprays

Khan, Sadique; Masood, Mudassir; Medina, Mario; Alzahrani, Fahad

doi:10.1016/j.fuel.2024.131980

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2024

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Cited by 2 publications

References 53 publications

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A Study on the Application of Data-Driven Ai-Based Methods in Ammonia Sprays Prediction

lu,

He,

Peng

et al. 2024

Preprint

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A Study on the Application of Data-Driven Ai-Based Methods in Ammonia Sprays Prediction

lu,

He,

Peng

et al. 2024

Preprint

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Injected Fuel Mass and Flow Rate Control in Internal Combustion Engines: A Systematic Literature Review

Ferrari,

Gurrì,

Vento

2024

Energies

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Advancements in fuel injection systems have dramatically improved the precision of controlling injected fuel mass or flow rate; a key factor in optimizing internal combustion engine (ICE) performance, emissions control, and fuel efficiency. This review systematically analyzes 145 scientific research papers from the last two decades, including older foundational works, tracing the evolution of injected mass control from early Bosch and Zeuch meters to advanced machine learning or physical models. This study draws upon research collected from the most reputable databases. Through both qualitative and quantitative analyses, the state-of-the-art of these systems is presented, and key innovations are highlighted regarding advanced control algorithms and real-time feedback mechanisms under various operational conditions such as high or transient loads and multi-stage injection strategies. Special attention is given to challenges in maintaining precise control with alternative fuels like biodiesel, hydrogen, or synthetic fuels, which exhibit different physical properties compared to traditional fuels. The findings emphasize the need for further research on injection control, especially in light of stringent emissions regulations. Improving these systems for next-generation ICEs is a key point for achieving cleaner, more efficient combustion and bridging the sustainability gap between traditional and future mobility solutions.

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Advancing Fuel Spray Characterization: A Machine Learning Approach for Directly Injected Gasoline Fuel Sprays

Cited by 2 publications

References 53 publications

A Study on the Application of Data-Driven Ai-Based Methods in Ammonia Sprays Prediction

A Study on the Application of Data-Driven Ai-Based Methods in Ammonia Sprays Prediction

Injected Fuel Mass and Flow Rate Control in Internal Combustion Engines: A Systematic Literature Review

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