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Ducted Fuel Injection (DFI) has the potential to reduce soot emissions in Diesel engines thanks to the enhanced mixing rate resulting from the liquid fuel flow through a small cylindrical pipe located at a certain distance from the nozzle injector hole. A consolidated set of experiments in constant-volume vessel and engine allowed to understand the effects of ambient conditions, duct geometry and shape on fuel-air mixing, combustion and soot formation. However, implementation of this promising technology in compression-ignition engines requires predictive numerical models that can properly support the design of combustion systems in a wide range of operating conditions. This work presents a computational methodology to predict fuel-air mixing and combustion with ducted fuel injection. Attention is mainly focused on turbulence and combustion modelling.

A test sample configuration with a circular cross-section has been conceptualized to reproduce all geometrically relevant flow-guided elements - straight segments, deflections, bifurcations, impingement regions, confluence - as they can also be found in the cooling systems of realistic Internal Combustion (IC) engines. This newly-designed reference test sample is termed as Water Spider Geometry (WSG), with the shape inspired by the flow guidance around an IC engine cylinder head. Computational investigations are carried out within the framework of a BMWi (German Federal Ministry for Economic Affairs and Energy) project by applying a well-resolved, highly comprehensive Large Eddy Simulation aiming at providing a meaningful assessment of the isothermal flow topology within the WSG. The basis forms a fully-hexahedral, block-structured grid arrangement comprising 290 million cells with the results considered to be a reference solution for further investigations.

Diesel engines are one of the most popular combustion systems used in different types of heavy-duty applications because of higher efficiencies compared to the spark ignition engines. Combustion phasing and the rate of heat release in diesel engines are controlled by the rate at which the fuel is injected into the combustion chamber near top dead center. In this work, computational fluid dynamics (CFD) was employed to simulate the combustion behavior of a heavy-duty diesel engine equipped with a 16-hole injector, in which the nozzles were arranged in two individual rows. The two rows of nozzles have differential flow rate due to the geometrical construction of the injector. Combustion and performance characteristics of the engine were compared with and without considering the differential flow rate of the nozzle rows at a range of injection timing values.

G-Equation models represent propagating flame fronts with an implicit two-dimensional surface representation (level-set). Level-set methods are fast, as transport source terms for the implicit surface can be solved with finite-volume operators on the finite-volume domain, without having to build the actual surface. However, they include approximations whose practical effects are not properly understood. In this study, we improved the numerics of the FRESCO CFD code’s G-Equation solver and developed a new method to simulate kernel growth using signed distance functions and the analytical sphere-mesh overlap. We analyzed their role for simulating propane/air flames, using three well-established constant-volume configurations: a one-dimensional, freely propagating laminar flame; a disc-shaped, constant-volume swirl combustor; and torch-jet flame development through an orifice from a two-chamber device.

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.

Liquefied petroleum gas (LPG), whose primary composition is propane, is a promising candidate for heavy-duty vehicle applications as a diesel fuel alternative due to its CO2 reduction potential and high knock resistance. To realize diesel-like efficiencies, spark-ignited LPG engines are proposed to operate near knock-limit over a wide range of operating conditions, which necessitates an investigation of fuel-engine interactions that leads to end-gas autoignition with propane combustion. This work presents both experimental and numerical studies of stoichiometric propane combustion in a spark-ignited (SI) cooperative fuel research (CFR) engine. Engine experiments are initially conducted at different compression ratio (CR) values, and the effects of CR on engine combustion are characterized.

A one-dimensional, non-equilibrium, compressible law of the wall model is proposed to increase the accuracy of heat transfer predictions from computational fluid dynamics (CFD) simulations of internal combustion engine flows on engineering grids. Our 1D model solves the transient turbulent Navier-Stokes equations for mass, momentum, energy and turbulence under the thin-layer assumption, using a finite-difference spatial scheme and a high-order implicit time integration method. A new algebraic eddy-viscosity closure, derived from the Han-Reitz equilibrium law of the wall, with enhanced Prandtl number sensitivity and compressibility effects, was developed for optimal performance. Several eddy viscosity sub-models were tested for turbulence closure, including the two-equation k-epsilon and k-omega, which gave insufficient performance.

This study examines the cycle-to-cycle variations (combustion instability) in the dual-fuel stationary compression ignition engine. The variations in the consecutive engine cycles are characterized under different load, gasoline/methanol-diesel premixing ratio (rp) and diesel injection timing (SOI). To investigate the combustion instability in dual-fuel CI-engine, gasoline and methanol are used as a low reactivity fuel (LRF) and is fed in the modified intake manifold during the suction stroke. The tests are performed for different fuel rp using developed port-fuel injector controller in the laboratory. The combustion instability is analyzed using the statistical method and Wavelet Transform (WT). Results indicate that combustion instability is more prone to lower and medium engine load, and variations are significantly higher for the high substitution fraction of LRF. The upper limit of fuel rp is restricted by higher variations in the combustion parameters.

This paper investigates how particulates number PN is influenced by fuel wall-film, liner wetting, and the mixing quality for different start of injection timings (SOI). Both experimental data with PN measurements, endoscope images from a high-speed camera from a single-cylinder engine, and CFD simulations were used for the analysis. Engine geometry was a spray-guided system with 300 bar fuel pressure and with single injections. Data was captured for 2000 rpm / 9 bar IMEPn. The results show that fuel film on the piston was only found to significantly increase PN for over-advanced SOI (in our engine geometry, earlier than -310 CAD). This results in luminescence from diffusion burn on the piston surface, which strongly contributes to PN. For an SOI timing of -310 CAD, fuel film on piston reaches a maximum of 3% of the injected fuel, vaporizes, and no remaining fuel film is found at the time of ignition. Approximately 0.5-1% of the fuel ends up on the liner.

Among the new low temperature combustion modes, Reactivity-Controlled Compression Ignition (RCCI) offers a low NOx-soot trade off (keeping a relatively high engine efficiency). Also, RCCI permits the introduction of a renewable fuel with a lower CO2 direct emission such as short-chains alcohols. For this work, methanol and diesel fuel were used as low and high reactivity fuels, respectively. A 1.3 L single-cylinder engine, with a cylinder volume usual in medium- and heavy-duty truck and bus engines, was used in this work. The engine was operated at an engine speed of 1600 rpm and 25% load (representing one of the 13-mode test on medium duty trucks), which results in an indicated mean effective pressure of 5.2 bar. The effects of methanol substitution ratio (MSR) at 20 and 35% on performance and pollutant emissions was investigated and compared to conventional diesel combustion (CDC).

Reactivity Controlled Compression Ignition (RCCI) is a low temperature combustion regime that has demonstrated ultra-low NOx and soot while achieving high thermal efficiency. RCCI uses a low reactivity premixed charge which is ignited via direct injection of a high reactivity fuel. The aim is to create a nearly homogeneous charge but maintain control over the combustion timing via the ratio between the premixed and direct injected fuel, hence controlling global reactivity via reactivity gradients in-cylinder. RCCI combustion with gasoline as the premixed fuel and diesel as the high reactivity fuel has shown good combustion timing controllability. However, RCCI with alcohol fuels, in which pure alcohol is the low reactivity premixed fuel and the alcohol doped with a reactivity enhancer is the direct injected high reactivity fuel, has shown a lack of control over the combustion timing, which is undesirable.

A diesel piloted natural gas engine's performance varies depending on operating conditions and has performed best under medium to high loads. It can often equal or better the fuel conversion efficiency of a diesel-only engine in this operating range. This paper presents a study performed on a multi-cylinder Cummins ISB 6.7L diesel engine converted to run stoichiometric natural gas/diesel micro-pilot combustion with a maximum diesel contribution of 10%. This study systematically quantifies and ranks the sensitivity of control factors on combustion and performance while operating at medium loads. The effects of combustion control parameters, including the pilot start of injection, pilot injection pressure, pilot injection quantity, exhaust gas recirculation, and global equivalence ratio, were tested using a design of experiments orthogonal matrix approach.

Active prechamber combustion systems for SI engines represent a feasible and effective solution in reducing fuel consumption and pollutant emissions for both marine and ground heavy-duty engines. However, reliable and low-cost numerical approaches need to be developed to support and speed-up their industrial design considering their geometry complexity and the involved multiple flow length scales. This work presents a CFD methodology based on the RANS approach for the simulation of active prechamber spark-ignition engines. To reduce the computational time, the gas exchange process is computed only in the prechamber region to correctly describe the flow and mixture distributions, while the whole cylinder geometry is considered only for the power-cycle (compression, combustion and expansion). Outside the prechamber the in-cylinder flow field at IVC is estimated from the measured swirl ratio.

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.

In the challenge to reduce CO2, NOx and PM emissions, the application of natural gas or biogas in engines is a viable approach. In heavy duty and marine, either a conventional dual fuel (CDF), or a reactivity-controlled compression ignition (RCCI) approach is feasible on existing diesel engines. In both technologies a pilot diesel injection is used to ignite the premixed natural gas. However, the influence of injection-timing and -pressure on the start of combustion timing (SOC) is opposite between both modes. For a single operating point these relations can be explained by a detailed CFD simulation, but an intuitive overall explanation is lacking. This makes it difficult to incorporate both modes into one engine application, using a single controller. In an experimental campaign by the authors, on a medium speed engine, the lowest emissions were found to be very close to the SOC corresponding to the transition from RCCI to CDF.

Natural Gas used in high-efficiency engines holds promise as a low-cost intermediate solution to reduce Greenhouse Gases and particulate matter. However, to achieve high engine efficiencies, engines need to be operated at increased Brake Mean Effective Pressures (BMEP), which is limited by destructive, engine damaging knock. Alternatively, if controlled, the same End-Gas Autoignition (EGAI) process responsible for knock can boost efficiencies and consume unburned methane while leveraging low-cost traditional exhaust aftertreatment technologies, such as a three-way catalyst, to minimize environmental impact. For this reason, this work has developed a method to detect the presence of EGAI and to determine its onset location (or crank angle).

Machine learning algorithms are effective tools to reduce the number of engine dynamometer tests during internal combustion engine development and/or optimization. This paper provides a case study of using such a statistical algorithm to characterize the heat transfer from the combustion chamber to the environment during combustion and during the entire engine cycle. The data for building the machine learning model came from a single cylinder compression ignition engine (13.3 compression ratio) that was converted to natural-gas port fuel injection spark-ignition operation. Engine dynamometer tests investigated several spark timings, equivalence ratios, and engine speeds, which were also used as model inputs. While building the model it was found that adding the intake pressure as another model input improved model efficiency.

Economy decarbonization will be one of the main goals for the following years. Research efforts are being focused on reducing carbon-based emissions, by increasing the efficiency of the transport power plants while developing new fuel production methods that reduce the environmental footprint of the refinement process. Consequently, the depletion of conventional fuels derived from petroleum with high carbon content, such as gasoline and diesel, motivated the development of propulsive alternatives for the transportation sector. In this paradigm, methane (CH4) fuel appears as a mid-term solution due to its low carbon content, if compared with traditional fuels, and the low CO2 emissions during its production from renewable sources. However, the intrinsic properties of methane compromise the combustion process, subsequently increasing the emission of CO2.

Stringent emission legislations have pushed engine operation to borderline knock. Knocking combustion limits engine efficiency, putting a threshold in carbon emission reduction that impairs further decarbonization of the transport sector. In this way, online knock monitoring is very important during engine development and calibration to allow operation with higher efficiency levels. Commonly, knock detection methods require complex calculations with high computational cost. Furthermore, these methods normally need previous calibration of a threshold value for each specific engine to indicate the knock limit, requiring important engineering resources and time. Hence, this paper proposes a novel methodology for knock detection that is simple, does not require prior calibration and can be used for sensorless knock detection. The method is applied by relating the crank angle of maximum pressure rise rate (AMPRR) with the angle of 50% of fuel mass burned (CA50), the so-called G Index (GI).

A model-based control approach is proposed to give proper reference for the feed-forward combustion control of Partially Pre-mixed Combustion (PPC) engines. The current study presents a simplified first principal model, which has been developed to provide a base estimation of the ignition properties. This model is used to describe the behavior of a single-cylinder heavy-duty diesel engine fueled with a mix of bio-butanol and n-heptane (80vol% bio-butanol and 20 vol% n-heptane). The model has been validated at 8 bar gross Indicated Mean Effective Pressure (gIMEP) in PPC mode. Inlet temperature and pressure have been varied to test the model capabilities. First the experiments were conducted to generate reference points with BH80 under PPC conditions. And then CFD simulations were conducted to give initial parameter set up, e.g. fuel distribution, zone dividing, for the multi-zone model.