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The accurate prediction of engine performance maps can guide data-driven optimization of engine technologies to control fuel use and associated emissions. However, engine operational maps are scarcely reported in literature and often have missing data. Assessment of missing-data resilient algorithms in the context of engine data prediction could enable better processing of real-world driving cycles, where missing data is a more pervasive phenomenon. The goal of this study is, therefore, to determine the most effective technique to deal with missing data and employ it in prediction of engine performance characteristics. We assess the performance of two machine learning approaches, namely Artificial Neural Networks (ANNs) and the extreme tree boosting algorithm (XGBoost), in handling missing data.

Lean combustion technologies show promise for improving engine efficiency and reducing emissions. Among these technologies, prechamber-assisted combustion (PCC) is established as a reliable option for achieving lean or ultra-lean combustion. In this study, the effect of engine speed on PCC was investigated in a naturally aspirated heavy-duty optical engine: a comparison has been made between analytical performances and optical flame behavior. Bottom view natural flame luminosity (NFL) imaging was used to observe the combustion process. The prechamber was fueled with methane, while the main chamber was fueled with methanol. The engine speed was varied at 1000, 1100, and 1200 revolutions per minute (rpm). The combustion in the prechamber is not affected by changes in engine speed. However, the heat release rate (HRR) in the main chamber changed from two distinct stages with a faster first stage to more gradual and merged stages as the engine speed increased.

To understand key practical aspects of ammonia as a fuel for internal combustion engines, three-dimensional computational fluid dynamics (CFD) simulations were performed using CONVERGETM. A light-duty single-cylinder research engine with a geometrical compression ratio of 11.5 and a conventional pentroof combustion chamber was experimentally operated at stoichiometry. The fumigated ammonia was introduced at the intake plenum. Upon model validation, additional sensitivity analysis was performed. The combustion was modeled using a detailed chemistry solver (SAGE), and the ammonia oxidation was computed from a 38-specie and 262-reaction chemical reaction mechanism. Three different piston shapes were assessed, and it was found that the near-spark flow field associated with the piston design in combination with the tumble motion promotes faster combustion and yields enhanced engine performance.

The combustion instability at low loads is one of the key technology risks that needs to be addressed with the development of gasoline compression ignition (GCI) engine. The misfires and partial burns due to combustion instability leads to excessive hydrocarbon (HC) and carbon monoxide (CO) emissions. This study aims to improve the combustion robustness and reduce the emissions at low loads. The GCI engine used in this study has unique hardware features of a spark plug placed adjacent to the centrally mounted gasoline direct injector and a shallow pent roof combustion chamber coupled with a bowl in piston geometry. The engine experiments were performed in a single cylinder GCI engine at 3 bar indicated mean effective pressure (IMEP) and 1500 rpm for certified gasoline with research octane number (RON) = 91.

The global need for de-carbonization and stringent emission regulations are pushing the current engine research toward alternative fuels. Previous studies have shown that the uHC, CO, and CO2 emissions are greatly reduced and brake thermal efficiency increases with an increase in hydrogen concentration in methane-hydrogen blends for the richer mixture compositions. However, the combustion suffers from high NOx emissions. While these trends are well established, there is limited information on a detailed optical study on the effect of air-excess ratio for different methane-hydrogen mixtures. In the present study, experimental investigations of different methane-hydrogen blends between 0 and 100% hydrogen concentration by volume for the air-excess ratio of 1, 1.4, 1.8, and 2.2 were conducted in a heavy-duty optical diesel engine converted to spark-ignition operation. The engine was equipped with a flat-shaped optical piston to allow bottom-view imaging of the combustion chamber.

In passenger car development, extreme ICE downsizing trends have been observed over the past decade. While this comes with fuel economy benefits, they are often obtained at the expense of Brake Mean Effective Pressure (BMEP) rise time in transient engine response. Through advanced control strategies, the use of Fully Variable Valvetrain (FVVT) technologies has the potential to completely mitigate the associated drivability-penalizing constraints. Adopting a statistical approach, key part load performance engine parameters are analyzed. Design-of-Experiment data is generated using a validated GT-Power model for a Freevalve-converted turbocharged Ultraboost engine. Subsequently, MathWorks' Model Based Calibration (MBC) toolbox is utilized to interpret the data through model fitments using neural network models of optimized architectures.

The pre-chamber combustion (PCC) concept is a proven lean or diluted combustion technique for internal combustion engines with benefits in engine efficiency and reduced NOx emissions. The engine lean operation limit can be extended by supplying auxiliary fuel into the pre-chamber and thereby, achieving mixture stratification inside the pre-chamber over the main chamber. Introducing liquid fuels into the pre-chambers is challenging owing to the small form factor of the pre-chamber. With a conventional injector, the fuel penetrates in liquid form and impinges on the pre-chamber walls, which leads to increased unburned hydrocarbon emissions from the pre-chamber. In this study, a prototype liquid fuel injector is introduced which preheats the fuel within a heated chamber fitted with an electrical heating element before injecting an effervescently atomized spray into the pre-chamber.

Throughout its history, the internal combustion engine has been continuously scrutinized to achieve strict legislative emission targets. With the dawn of renewable fuels fast approaching, most Internal Combustion Engine (ICE) equipped hybrid electric vehicles (HEVs) face difficulty in adjusting their precise control strategies to new fuels. This is partly due to constrained limitations associated with camshaft-induced design-point air induction limitations. Freevalve is a fully variable valvetrain technology enabling independent control of valve lifts, durations, and timings. Additionally, the added degrees-of-freedom enable the capability to shut-off individual engine valves, optimizing combustion performance and stability through specific speed ranges. By design, it minimizes the existing breathing-related constraints that are currently hindering the extraction of the higher efficiency potential of ICEs.

Typical automotive emission testing systems usually employ Flame Ionization Detection (FID) analyzers to measure unburned fuel species in the exhaust, but the technique is not suitable for engines operating on alcohol fuels. The FID method is not sensitive to measuring unburned alcohol fuels due to the presence of oxygen bonds in the fuel molecule. Other techniques, such as Fourier Transform Infrared (FTIR), can provide accurate unburned fuel measurements with alcohol fuel. However, these techniques are expensive and are less accessible compared to FID analyzers. In this study, the unburned fuel emissions from the engine exhaust were measured simultaneously with FID and FTIR analyzers, with the engine operating on pure alcohols, which are methanol, ethanol, and n-butanol. While most previous work focuses on stoichiometric air-fuel mixtures, a wide range of lean operating conditions between global-λ 1.6 to 2.8 will be tested in this study.

The current work utilizes computational fluid dynamics (CFD) simulations to assess the effects of different piston geometries in an active-type pre-chamber combustion engine fueled with methane. Previous works identified that the interaction of the jets with the main chamber flow and piston wall are key aspects for the local turbulent flame speed and overall burning duration. The combustion process is simulated with the G-equation model for flame propagation combined with the MZ-WSR model to determine the post-flame composition and to predict possible auto-ignition of the reactant mixture. Four setups were considered: two bowl-shaped and one flat piston, and one additional case of the flat piston with jets at wider jet angles to the cylinder axis. The results show that premature jet-wall interaction impacts the main chamber pressure build-up, turbulence, and burn rate.

The pre-chamber combustion can extend the lean limit of internal combustion engines (ICE) and hence increase their overall efficiency. Compared to active pre-chambers equipped with an auxiliary fuel supply system, passive pre-chambers have lower manufacturing costs and require minimal or no design modifications to the conventional spark plug engines. The major challenge of the passive pre-chamber is to extend the lean limit as much as the active pre-chamber. Computational fluid dynamics (CFD) simulations were conducted on a light-duty single-cylinder engine geometry fitted with a passive pre-chamber and using iso-octane as fuel to investigate and optimize the passive pre-chamber fuel enrichment through the pre-chamber nozzles. The non-reacting flow simulations were performed from the intake valve open (IVO) to spark timing.

In recent years lean-burn technologies have acquired center stage in engine research due to stringent emission norms. Among such technologies, pre-chamber assisted combustion (PCC) has gained much attention for its ability to allow ultra-lean engine operation (λ > 2). The spark-ignited pre-chambers engines allow such lean operation by inducing a strong charge stratification, enhancing turbulence generation, and multipoint ignition. Adding a pre-chamber igniter to the engine alters the in-cylinder flow fields as mass is exchanged between the pre-chamber and the main chamber. This study reports the main chamber flow fields of methane fuelled heavy-duty optical engine fitted with a narrow throat active prechamber. Particle image velocimetry (PIV) at 10 Hz is performed from the side view using TiO2 particle seeding.

Lean combustion is one of the most applied methods to increase engine efficiency and maintain a good trade-off with engine emissions. The pre-chamber combustion (PCC) is one of the most promising combustion concepts to extend the lean operating limits of the engine. The Narrow throat pre-chamber has shown better lean limit extension compared to other ignition sources. The pre-chamber jets and the main-chamber combustion were studied in a Heavy-Duty optical engine using methane fuel. The tested conditions covered global excess air ratios (λ), between 1.9 to 2.3. The combustion process was recorded using three collection systems: (a) Natural Flame Luminosity (NFL) with a temporal resolution of 0.1 CAD; (b) OH* Chemiluminescence, and (c) CH* Chemiluminescence with a temporal resolution of 0.2 CAD for both. The propagating velocity of the reacting jets was studied using Combustion Image Velocimetry (CIV) based on bottom view images of the main chamber.

Compared to conventional diesel combustion (CDC), isobaric combustion can achieve higher thermal efficiency while lowering heat transfer losses and nitrogen oxides (NOx). However, isobaric combustion suffers from higher soot emissions. While the aforementioned trends are well established, there is limited literature about the high-temperature reaction zones, the liquid-phase penetration distance, and the flame tip propagation velocity of isobaric combustion. In the present study, the line-of-sight integrated imaging of Mie-scattering, combustion luminosity, and CH* chemiluminescence were conducted in an optically accessible single-cylinder heavy-duty diesel engine. The engine was equipped with a flat-bowl-shaped optical piston to allow bottom-view imaging of the combustion chamber. The experiments were conducted using n-heptane fuel for CDC and isobaric combustion modes.

Investigating combustion characteristics of oxygenated gasoline and gasoline blended ethanol is a subject of recent interest. The non-linearity in the interaction of fuel components in the oxygenated gasoline can be studied by developing chemical kinetics of relevant surrogate of fewer components. This work proposes a new reduced four-component (isooctane, heptane, toluene, and ethanol) oxygenated gasoline surrogate mechanism consisting of 67 species and 325 reactions, applicable for dynamic CFD applications in engine combustion and sprays. The model introduces the addition of eight C1-C3 species into the previous model (Li et al; 2019) followed by extensive tuning of reaction rate constants of C7 - C8 chemistry. The current mechanism delivers excellent prediction capabilities in comprehensive combustion applications with an improved performance in lean conditions.

To elucidate the complex characteristics of pre-chamber combustion engines, the interaction of the hot gas jets initiated by an active narrow throated pre-chamber with lean premixed CH4/air in a heavy-duty engine was studied computationally. A twelve-hole KAUST proprietary pre-chamber geometry was investigated using CONVERGE software. The KAUST pre-chamber has an upper conical part with the spark plug, and fuel injector, followed by a straight narrow region called the throat and nozzles connecting the chambers. The simulations were run for an entire cycle, starting at the previous cycle's exhaust valve opening (EVO). The SAGE combustion model was used with the chemistry modeled using a reduced methane oxidation mechanism based on GRI Mech 3.0, which was validated against in-house OH chemiluminescence data from the optical engine experiments.

Flame lift-off length (FLOL), ignition delay time (IDT), liquid length (LL), and Soot are essential parameters defining spray combustion characteristics. They help understand the combustion dynamics and validate the spray and combustion models for numerical simulations. However, obtaining extensive data from experiments is costlier and time-consuming. Machine learning (ML) models have advanced to the point where they could create efficient models that could be used as surrogates for experiments. In this study, five different ML algorithms have been trained using the experimental dataset available through the engine combustion network (ECN) community. A novel genetic algorithm-based hyperparameter optimization code has been used to optimize the models to improve prediction accuracy. The model performances were compared, and the better model was chosen as an experimental surrogate to predict FLOL, IDT, LL, and Soot.

The present work represents the continuation of the introductory study presented in part I [11] where the experimental plan, the measurement system and the tools developed for the testing of a modern Wankel engine were illustrated. In this paper the motored data coming from the subsequent stage of the testing are presented. The AIE 225CS Wankel rotary engine produced by Advanced Innovative Engineering UK, installed in the test cell of the University of Bath and equipped with pressure transducers selected for the particular application, has been preliminarily tested under motored conditions in order to validate the data acquisition software on the real application and the correct determination of the Top Dead Centre (TDC) location which is of foremost importance in the computation of parameters such as the indicated work and the combustion heat release when the engine is tested later under fired conditions.

This work represents a further contribution to reporting experimental activities carried out on a modern Wankel rotary engine. Specifically, in this study, the firing performance of the Advanced Innovative Engineering 225CS engine is analysed. Preliminary presentations of the experimental and measurement setup and a motoring analysis were extensively covered in Part I and II of this suite of papers while the current work presents the combustion analysis of the firing indicated pressure cycles collected through the bespoke combustion analyser software developed within the project. With the Wankel rotary engine gaining popularity again due to its potential as a range extender for battery electric vehicles, the aim of this work was mainly to analyse the fuel consumption together with the overall efficiency and the emissions at different engine speeds and loads as per classic steady-state engine testing.

The increasing demand for high-octane fuels is pushing the combustion research towards investigating new potential fuels and octane boosters. In addition to their high-octane, those additives should be environmentally friendly. In this study, the anti-knock properties of Dicyclopentadiene (DCPD) as an additive to primary reference fuels (PRF) and toluene primary reference fuels (TPRF) have been investigated. The Research octane number (RON) and Motor octane number (MON) were measured using Cooperative Fuels Research (CFR) engine for four different fuel blends; PRF 60 + 10% DCPD, PRF 60 + 20% DCPD, PRF 70 + 10% DCPD and TPRF 70 + 10% DCPD. In addition, homogenous charge compression ignition (HCCI) was also performed using the CFR engine to show the effect of DCPD on suppressing low temperature chemistry of reference fuels.