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Spray modelling plays a key role in engine simulations to understand fuel propagation and mixing, combustion, pollutant formation and energy efficiency. The grid dependency, need of calibration of several spray parameters, complexity associated with validation and high computational demand associated with Spray modelling are addressed with 1-dimentional SprayLet model. This work focuses on enhancing the SprayLet model approach with a dual emphasis on computational efficiency and grid independence for advanced engine simulations. Key spray characteristics, such as vapor and liquid penetration lengths, have been systematically evaluated as they play pivotal roles in understanding fuel evaporation, spray-wall interactions, and mixture formation within engines.

In more or less all aspects of life and in all sectors, there is a generalized global demand to reduce greenhouse gas (GHG) emissions, leading to the tightening and expansion of existing emissions regulations. Currently, non-road engines manufacturers are facing updates such as, among others, US Tier 5 (2028), European Stage V (2019/2020), and China Non-Road Stage IV (in phases between 2023 and 2026). For on-road applications, updates of Euro VII (2025), China VI (2021), and California Low NOx Program (2024) are planned. These new laws demand significant reductions in nitrogen oxides (NOx) and particulate matter (PM) emissions from heavy-duty vehicles. When equipped with an appropriate exhaust aftertreatment system, natural gas engines are a promising technology to meet the new emission standards.

In contrast to the currently primarily used liquid fuels (diesel and gasoline), methane (CH4) as a fuel offers a high potential for a significant reduction of greenhouse gas emissions (GHG). This advantage can only be used if tailpipe CH4 emissions are reduced to a minimum, since the GHG impact of CH4 in the atmosphere is higher than that of carbon dioxide (CO2). Three-way catalysts (TWC - stoichiometric combustion) and methane oxidation catalysts (MOC - lean combustion) can be used for post-engine CH4 oxidation. Both technologies allow for a nearly complete CH4 conversion to CO2 and water at sufficiently high exhaust temperatures (above the light-off temperature of the catalysts). However, CH4 combustion is facing a huge challenge with the planned introduction of Euro VII emissions standard, where stricter CH4 emission limits and a decrease of the cold start starting temperatures are discussed.

Meeting strict current and future emissions legislation necessitates development of computational tools capable of predicting the behaviour of combustion and emissions with an accuracy sufficient to make correct design decisions while keeping computational cost of the simulations amenable for large-scale design space exploration. While detailed kinetics modelling is increasingly seen as a necessity for accurate simulations, the computational cost can be often prohibitive, prompting interest in simplified approaches allowing fast simulation of reduced mechanisms at coarse grid resolutions appropriate for internal combustion engine simulations in design context. In this study we present a simplified Well-stirred Reactor (WSR) implementation coupled with 3D CFD Ricardo VECTIS solver.

The development of future gasoline engines is dominated by the study of new technologies aimed at reducing the engine negative environmental impact and increase its thermal efficiency. One common trend is to develop smaller engines able to operate in stoichiometric conditions across the whole engine map for better efficiency, lower fuel consumption, and optimal conversion rate of the three-way catalyst (TWC). Water injection is one promising technique, as it significantly reduces the engine knock tendency and avoids fuel enrichment for exhaust temperature mitigation at high power operation. With the focus on reducing the carbon footprint of the automotive sector, another vital topic of research is the investigation of new alternative CO2-neutral fuels or so-called eFuels. Several studies have already shown how these new synthetic fuels can be produced by exploiting renewable energy sources and can significantly reduce engine emissions.

Advanced combustion concepts such as reactivity controlled compression ignition (RCCI) have been proven to be capable of fundamentally improve the conventional Diesel combustion by mitigating or avoiding the soot-NOx trade-off, while delivering comparable or better thermal efficiency. To further facilitate the development of the RCCI technology, a robust and possibly computationally efficient simulation framework is needed. While many successful studies have been published using 3D-CFD coupled with detailed combustion chemistry solvers, the maturity level of the 0D/1D based software solution offerings is relatively limited. The close interaction between physical and chemical processes challenges the development of predictive numerical tools, particularly when spatial information is not available.

Water injection can be applied to spark ignited gasoline engines to increase the Knock Limit Spark Advance and improve the thermal efficiency. The Knock Limit Spark Advance potential of 6 °CA to 11 °CA is shown by many research groups for EN228 gasoline fuel using experimental and simulation methods. The influence of water is multi-layered since it reduces the in-cylinder temperature by vaporization and higher heat capacity of the fresh gas, it changes the chemical equilibrium in the end gas and increases the ignition delay and decreases the laminar flame speed. The aim of this work is to extend the analysis of water addition to different octane ratings. The simulation method used for the analysis consists of a detailed reaction scheme for gasoline fuels, the Quasi-Dimensional Stochastic Reactor Model and the Detonation Diagram. The detailed reaction scheme is used to create the dual fuel laminar flame speed and combustion chemistry look-up tables.

This study investigates particulate matter (PM) and regulated emissions from renewable rapeseed oil methyl ester (RME) biodiesel in pure and blended forms and contrasts that to conventional diesel fuel. Environmental and health concerns are the major motivation for combustion engines research, especially finding sustainable alternatives to fossil fuels and reducing diesel PM emissions. Fatty acid methyl esters (FAME), including RME, are renewable fuels commonly used from low level blends with diesel to full substitution. They strongly reduce the net carbon dioxide emissions. It is largely unknown how the emissions and characteristics of PM get altered by the combined effect of adding biodiesel to diesel and implementing modern engine concepts that reduce nitrogen oxides (NOx) emissions by exhaust gas recirculation (EGR).

The use of complex reaction schemes is accompanied by high computational cost in 3D CFD simulations but is particularly important to predict pollutant emissions in internal combustion engine simulations. One solution to tackle this problem is to solve the chemistry prior the CFD run and store the chemistry information in look-up tables. The approach presented combines pre-tabulated progress variable-based source terms for auto-ignition as well as soot and NOx source terms for emission predictions. The method is coupled to the 3D CFD code CONVERGE v2.4 via user-coding and tested over various speed and load passenger-car Diesel engine conditions. This work includes the comparison between the combustion progress variable (CPV) model and the online chemistry solver in CONVERGE 2.4. Both models are compared by means of combustion and emission parameters. A detailed n-decane/α-methyl-naphthalene mechanism, comprising 189 species, is used for both online and tabulated chemistry simulations.

A large number of measurement techniques have been developed or adapted from other fields to measure various parameters of engine particulates. With the strict limits given by regulations on pollutant emissions, many advanced combustion strategies have been developed towards cleaner combustion. Exhaust gas recirculation (EGR) is widely applied to suppress nitrogen oxide (NOx) and reduce soot emissions. On the other hand, gasoline starts to be utilized in compression ignition engines due to great potential in soot reduction and high engine efficiency. New engine trends raise the need for good sensitivity and suitable accuracy of the PM measurement techniques to detect particulates with smaller size and low particulate mass emissions. In this work, we present a comparison between different measurement techniques for particulate matter (PM) emissions in a compression ignition engine running on gasoline fuel. A wide-range of EGR was used with lambda varied from 3 down to 1.

The introduction of a physics-based zero-dimensional stochastic reactor model combined with tabulated chemistry enables the simulation-supported development of future compression-ignited engines. The stochastic reactor model mimics mixture and temperature inhomogeneities induced by turbulence, direct injection and heat transfer. Thus, it is possible to improve the prediction of NOx emissions compared to common mean-value models. To reduce the number of designs to be evaluated during the simulation-based multi-objective optimization, genetic algorithms are proven to be an effective tool. Based on an initial set of designs, the algorithm aims to evolve the designs to find the best parameters for the given constraints and objectives. The extension by response surface models improves the prediction of the best possible Pareto Front, while the time of optimization is kept low.

Partially premixed combustion (PPC) in internal combustion engine as a low temperature combustion strategy has shown great potential to achieve high thermodynamic efficiency. Methanol due to its unique properties is considered as a preferable PPC engine fuel. The injection timing to achieve methanol PPC conditions should be set very close to TDC, allowing to utilize spray-bowl interaction to further improve combustion process in terms of emissions and heat losses. In this study CFD simulations are performed to investigate spray-bowl interaction for a number of different piston designs and its impact on the heat transfer and the overall piston performance. The validation case is based on a single cylinder heavy-duty Scania D13 engine with a compression ratio 15. The operation point is set to low load 5.42 IMEPg bar with SOI -3 aTDC.

Water injection is a promising technology to improve the fuel efficiency of turbocharged gasoline engines due to the possibility to suppress engine knock. Additionally, this technology is believed to enable the efficient operation of the three-way catalyst also at high-load conditions, through limiting the exhaust temperature. In this numerical study, we investigate the effect of water on the chemical and thermodynamic processes using 3D computational fluid dynamics (CFD) Reynolds-averaged Navier–Stokes (RANS) with detailed chemistry. In the first step, the influence of different amounts of water vapor on ignition delay time, laminar flame speed, and heat capacity is investigated. In the second step, the impact of water vaporization is analyzed for port and direct injection. For this purpose, the water mass flow and the injection pressure are varied.

Heavy-duty direct injection compression ignition (DICI) engine running on methanol is studied at a high compression ratio (CR) of 27. The fuel is injected with a common-rail injector close to the top-dead-center (TDC) with two injection pressures of 800 bar and 1600 bar. Numerical simulations using Reynold Averaged Navier Stokes (RANS), Lagrangian Particle Tracking (LPT), and Well-Stirred-Reactor (WSR) models are employed to investigate local conditions of injection and combustion process to identify the mechanism behind the trend of increasing nitrogen oxides (NOx) emissions at higher injection pressures found in the experiments. It is shown that the numerical simulations successfully replicate the change of ignition delay time and capture variation of NOx emissions.

Large two-stroke marine Diesel engines have special injector geometries, which differ substantially from the configurations used in most other Diesel engine applications. One of the major differences is that injector orifices are distributed in a highly non-symmetric fashion affecting the spray characteristics. Earlier investigations demonstrated the dependency of the spray morphology on the location of the spray orifice and therefore on the resulting flow conditions at the nozzle tip. Thus, spray structure is directly influenced by the flow formation within the orifice. Following recent Large Eddy Simulation resolved spray primary breakup studies, the present paper focuses on spray secondary breakup modelling of asymmetric spray structures in Euler-Lagrangian framework based on previously obtained droplet distributions of primary breakup.

Methanol as an alternative fuel in internal combustion engines has an advantage in decreasing emissions of greenhouse gases and soot. Hence, developing of a high performance internal combustion engine operating with methanol has attracted the attention in industry and academic research community. This paper presents a numerical study of methanol combustion at different start-of-injection (SOI) in a direct injection compression ignition (DICI) engine supported by experimental studies. The aim is to investigate the combustion behavior of methanol with single and double injection at close to top-dead-center (TDC) conditions. The experimental engine is a modified version of a heavy duty D13 Scania engine. URANS simulations are performed for various injection timings with delayed SOI towards TDC, aiming at analyzing the characteristics of partially premixed combustion (PPC).

Today numerical models are a major part of the diesel engine development. They are applied during several stages of the development process to perform extensive parameter studies and to investigate flow and combustion phenomena in detail. The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. 0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models. This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry.

A novel 0-D Probability Density Function (PDF) based approach for the modelling of Diesel combustion using tabulated chemistry is presented. The Direct Injection Stochastic Reactor Model (DI-SRM) by Pasternak et al. has been extended with a progress variable based framework allowing the use of a pre-calculated auto-ignition table. Auto-ignition is tabulated through adiabatic constant pressure reactor calculations. The tabulated chemistry based implementation has been assessed against the previously presented DI-SRM version by Pasternak et al. where chemical reactions are solved online. The chemical mechanism used in this work for both, online chemistry run and table generation, is an extended version of the scheme presented by Nawdial et al. The main fuel species are n-decane, α-methylnaphthalene and methyl-decanoate giving a size of 463 species and 7600 reactions.

The three-way catalytic converter (TWC) is the most common catalyst for gasoline engine exhaust gas after treatment. The reduction of carbon monoxide (CO), nitrogen oxides (NOx) and unburned hydrocarbons (HC) is achieved via oxidation of carbon monoxide and hydrocarbons, and reduction of nitrogen oxides. These conversion effects were simulated in previous works using single-channel approaches and detailed kinetic models. In addition to the single-channel model multiple representative catalyst channels are used in this work to take heat transfer between the channels into account. Furthermore, inlet temperature distribution is considered. Each channel is split into a user given number of cells and each cell is treated like a perfectly stirred reactor (PSR). The simulation is validated against an experimental four-stroke engine setup with emission outputs fed into a TWC.

The focus has recently been directed towards the engine out soot from Diesel engines. Running an engine in PPC (Partially Premixed Combustion) mode has a proven tendency of reducing these emissions significantly. In addition to combustion strategy, several studies have suggested that using alcohol fuels aid in reducing soot emissions to ultra-low levels. This study analyzes and compares the characteristics of PM emissions from naphtha gasoline PPC, ethanol PPC, methanol PPC and methanol diffusion combustion in terms of soot mass concentration, number concentration and particle size distribution in a single cylinder Scania D13 engine, while varying the intake O2. Intake temperature and injection pressure sweeps were also conducted. The fuels emitting the highest mass concentration of particles (Micro Soot Sensor) were gasoline and methanol followed by ethanol. The two alcohols tested emitted nucleation mode particles only, whereas gasoline emitted accumulation mode particles as well.