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Internal Combustion Engines in the Energy Transition: Efficiency, Control, and Sustainable Fuels

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "I2: Energy and Combustion Science".

Deadline for manuscript submissions: 10 July 2026 | Viewed by 2281

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Special Issue Editors

Dr. Oscar Vento

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Guest Editor

Energy Department, Politecnico di Torino, Corso Duca degli Abruzzi, 29, 10129 Torino, Italy
Interests: internal combustion engines; fuel injection systems; computational fluid dynamics; compressible fluid flows; fluid power systems
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Alessandro Ferrari

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Guest Editor

Energy Department, Politecnico di Torino, Corso Duca degli Abruzzi, 29, 10129 Torino, Italy
Interests: internal combustion engines; combustion; fuel injection systems; computational fluid dynamics; compressible fluid flows; fluid power systems; cavitation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Internal combustion engines (ICEs) remain a key technology in transportation and power generation, despite the ongoing energy transition. In fact, ICEs will continue to play an important role in applications where electrification is not suitable, such as long-haul road transportation and marine propulsion. In these contexts, it is still required to further improve the efficiency and environmental impact of ICEs, particularly by reducing their carbon footprint. These goals can be achieved with extensive experimental or numerical studies, as well as with the implementation of new techniques for monitoring engines in real-time. In parallel, the usage of new fuels such as ammonia, hydrogen, methanol, or e-fuels offers a promising pathway to reduce carbon emissions, albeit introducing new challenges.

The aim of this Special Issue is to collect and disseminate analyses (by means of experimental or numerical approaches) of internal combustion engines, applications of sustainable fuels, and developments of new control strategies for efficient management.

Topics of interest include, but are not limited to, the following:

Strategies for monitoring and controlling injection and combustion events;
Real-time and off-line modeling;
Applications of sustainable fuels;
Combustion performance of green fuels and their blends;
Spray technologies;
Numerical and experimental analyses;
Innovative techniques for emissions reduction;
Advanced approaches to improve engine efficiency.

Dr. Oscar Vento
Prof. Dr. Alessandro Ferrari
Guest Editors

Manuscript Submission Information

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Keywords

internal combustion engines
injection systems
combustion
sustainable fuels
ammonia
hydrogen
combustion control
combustion modeling
innovative control strategy

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Published Papers (5 papers)

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Research

25 pages, 6981 KB

Open AccessArticle

Chemiluminescence-Based Analysis of Syngas/Diesel Dual-Fuel Combustion in an Optically Accessible Engine

by Ricardo Rabello de Castro, Pierre Brequigny and Christine Mounaïm-Rousselle

Energies 2026, 19(9), 2042; https://doi.org/10.3390/en19092042 - 23 Apr 2026

Viewed by 290

Abstract

Syngas (synthesis gas) is a promising gaseous biofuel for small-scale power generation, but its highly variable composition, which depends on the biomass source and gasification process, poses challenges for engine optimization. This study investigates syngas–diesel dual-fuel combustion in an optically accessible engine using chemiluminescence imaging of OH*, CH*, and CH₂O* to characterize ignition and flame development. Three representative syngas compositions—Downdraft, Updraft, and Fluidbed—were examined. The Fluidbed composition exhibited the weakest OH* signal, approximately one-third of that observed for the other two, primarily due to its higher CO₂ dilution and lower H₂ content. Ignition delay trends were strongly correlated with dilution level: Downdraft and Updraft showed similar delays despite different H₂/CO ratios, while larger CO₂ shares led to longer delays and flattened heat-release rates. CH* and CH₂O* chemiluminescence showed better agreement with combustion timing than OH*. Methane enrichment enhanced flame propagation and reduced ignition delay, partially offsetting CO₂ dilution effects. Full article

(This article belongs to the Special Issue Internal Combustion Engines in the Energy Transition: Efficiency, Control, and Sustainable Fuels)

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19 pages, 3235 KB

Open AccessArticle

ML-Assisted Prediction of In-Cylinder Pressures of Spark-Ignition Engines

by Yu Zhang, Qianbing Xu and Xinfeng Zhang

Energies 2026, 19(8), 1969; https://doi.org/10.3390/en19081969 - 18 Apr 2026

Viewed by 243

Abstract

In-cylinder pressure is a key parameter for evaluating combustion processes and engine performance in spark-ignition engines. However, acquiring high-resolution pressure data over a wide range of operating conditions, particularly under varying spark advance (SA), is costly and technically challenging, which limits its practical application. To address this issue, this study proposes two artificial neural network (ANN)-based methods for in-cylinder pressure reconstruction using data from a three-cylinder gasoline engine under different spark advance conditions. Both methods employ crank angle and spark advance as input features. The first method (ANN-P) directly predicts the in-cylinder pressure profile, achieving a coefficient of determination (R²) exceeding 0.99 on both training and validation datasets, with a root mean square error (RMSE) below 0.13 bar. The model accurately reproduces the pressure evolution throughout the compression, combustion, and expansion processes and enables reliable estimation of indicated mean effective pressure (IMEP). The second method (ANN-HRR) adopts an indirect strategy by first predicting the heat release rate (HRR) and subsequently reconstructing the pressure trace through thermodynamic integration based on a single-zone model. This approach avoids error amplification associated with numerical differentiation and demonstrates improved accuracy in predicting combustion phasing metrics, such as CA10 and CA50. The results indicate that both methods effectively capture the influence of spark timing on combustion characteristics and peak pressure. While ANN-P provides higher accuracy in pressure reconstruction, ANN-HRR offers superior performance in characterizing combustion features. Overall, this study presents a cost-effective and accurate framework for combustion diagnostics, performance calibration, and control optimization of gasoline engines. Full article

(This article belongs to the Special Issue Internal Combustion Engines in the Energy Transition: Efficiency, Control, and Sustainable Fuels)

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15 pages, 5305 KB

Open AccessArticle

Assessment of the AUSM Scheme for Near-Nozzle Flow Field Characterization of Under-Expanded Hydrogen Jets

by Oscar Vento, Carmelo Baronetto and Alessandro Ferrari

Energies 2026, 19(8), 1871; https://doi.org/10.3390/en19081871 - 11 Apr 2026

Viewed by 467

Abstract

Hydrogen is a carbon-free energy carrier that can support decarbonization of the energy and transport systems. Its usage as a fuel in internal combustion engines can abate the pollutants and CO₂ emissions but also presents various challenges. Among these, the formation of under-expanded jets requires proper injector design and accurate control of the injection process. CFD can accelerate the development of hydrogen engine technologies towards market readiness. Low-dissipative density-based schemes are essential to accurately describe the complex flow structures, that affect mixture formation in under-expanded injections. In the present work, the AUSM scheme was implemented in the OpenFOAM library, and successfully used to simulate an experimental hydrogen-into-nitrogen injection. The numerical method, validated against experimental Schlieren images, was compared with the Kurganov–Noelle–Petrova scheme implemented in the current density-based OpenFOAM solver. The numerical results highlighted the reduced dissipation of the AUSM scheme, leading to improved jet penetration and gas mixing. The investigation demonstrated the superior performance of the AUSM scheme, suggesting it as an alternative OpenFOAM solver. Nevertheless, the study identified areas for improvement and critical issues associated with this type of simulations. Full article

(This article belongs to the Special Issue Internal Combustion Engines in the Energy Transition: Efficiency, Control, and Sustainable Fuels)

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15 pages, 1555 KB

Open AccessArticle

Optimization of Cu₂O Nano-Additive-Doped Diesel Engine Performance via Physics-Informed Hybrid GPR Framework

by Recep Cagri Orman

Energies 2026, 19(7), 1603; https://doi.org/10.3390/en19071603 - 25 Mar 2026

Cited by 1 | Viewed by 446

Abstract

In this study, a novel “Physics-Informed Hybrid Machine Learning” framework was developed to model and optimize the complex combustion and carbon-based emission characteristics of Cu₂O nano-additive doped diesel fuel. To reduce reliance on purely empirical correlations, the proposed framework integrates alterations in fuel physical properties into the prediction loop, thereby enhancing physical consistency and model generalizability. The methodology comprises data pre-processing, modeling via Gaussian Process Regression (GPR) with an Automatic Relevance Determination (ARD) kernel, and multi-objective optimization using NSGA-II. Experimental tests were conducted at a constant engine speed of 2000 rpm under varying load conditions. The developed hybrid model exhibited high predictive accuracy, particularly for performance metrics and gaseous emissions (e.g., R² > 0.95 for BSFC and CO). ARD-based feature importance analysis confirmed that nano-additive dosage plays a critical role in the fine-tuning of emissions. Crucially, the optimization algorithm identified a nano-additive dosage of ~29 ppm and an engine load of 15.5 Nm as the optimal operating point for the simultaneous improvement of performance and carbonaceous emissions. This finding, exploring the unmeasured design space, demonstrates the framework’s capability to discover optimal conditions beyond discrete experimental points. Full article

(This article belongs to the Special Issue Internal Combustion Engines in the Energy Transition: Efficiency, Control, and Sustainable Fuels)

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29 pages, 8590 KB

Open AccessArticle

AdBlue Port Injection for Dual-Fuel Compression-Ignition Engine Knock Suppression

by Thor Scicluna and Mario Farrugia

Energies 2026, 19(5), 1242; https://doi.org/10.3390/en19051242 - 2 Mar 2026

Viewed by 499

Abstract

Dual-fuel, diesel–LPG (LPG being Liquified Petroleum Gas, e.g., propane) compression-ignition engines reduce CO₂ and particulate emissions compared to diesel-only operation but are prone to knock at high load due to charge homogeneity and increased ignition delay. AdBlue port injection (API) was evaluated as a combustion stabilisation strategy for a diesel–LPG engine and compared with water port injection (WPI). Experiments were performed on a 2.0 L diesel–LPG engine operated at 2000 RPM, BMEP ≈ 9 bar, λ ≈ 1.27 and LPG substitution of 72%. Knock intensity was quantified using knock-induced signal energy (KISE) derived from the oscillatory component of the in-cylinder pressure over a knock-sensitive crank angle window. Characterisation of combustion was done through HRR analyses, MFB analyses and FFT-based frequency characterisation. Baseline operation exhibited severe knock with a peak HRR ≈ 200 J/°CA and mean KISE of 307.2 bar². WPI at a water mass ratio WMR of 130% reduced the peak HRR by 56% and mean KISE by 88%, but decreased the peak pressure, BMEP and BTE. API at an AdBlue mass ratio AMR of 130% reduced the peak HRR by 37% and KISE by 82.6% while maintaining BMEP and BTE within baseline variability. Both strategies attenuated the dominant ~19.8 kHz (1,2) mode. NOx emissions decreased with WPI but increased at a high AMR. Full article

(This article belongs to the Special Issue Internal Combustion Engines in the Energy Transition: Efficiency, Control, and Sustainable Fuels)

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