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The continuous pursuit of higher combustion efficiencies, as well as the possible usage of synthetic fuels with different properties than fossil-ones, require reliable and low-cost numerical approaches to support and speed-up engines industrial design. In this context, SI engines operated with homogeneous ultra-lean mixtures both characterized by a classical ignition configuration or equipped with an active prechamber represent the most promising solutions. In this work, for the classical ignition arrangement, a 3DCFD strategy to model the impact of the ignition system type on the CCV is developed using the RANS approach for turbulence modelling. The spark-discharge is modelled through a set of Lagrangian particles, whose velocity is modified with a zero-divergence perturbation at each discharge event, then evolved according to the Simplified Langevin Model (SLM) to simulate stochastic interactions with the surrounding gas flow.

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.

A correct prediction of the initial stages of the combustion process in SI engines is of great importance to understand how local flow conditions, fuel properties, mixture stratification and ignition affect the in-cylinder pressure development and pollutant formation. However, flame kernel growth is governed by many interacting processes including energy transfer from the electrical circuit to the gas phase, interaction between the plasma channel and the flow field, transition between different combustion regimes and gas expansion at very high temperatures. In this work, the authors intend to present a comprehensive, multi-dimensional model that can be used to predict the initial combustion stages in SI engines. In particular, the spark channel is represented by a set of Lagrangian particles where each one of them acts as a single flame kernel.

SI engines fueled with hydrogen represent a promising powertrain solution to meet the ambitious target of carbon-free emissions at the tailpipe. Therefore, fast and reliable numerical tools can significantly support the automotive industry in the optimization of such technology. In this work, a 1D-3D methodology is presented to simulate in detail the combustion process with minimal computational effort. First, a 1D analysis of the complete engine cycle is carried out on the user-defined powertrain configuration. The purpose is to achieve reliable boundary conditions for the combustion chamber, based on realistic engine parameters. Then, a 3D simulation of the power-cycle is performed to mimic the combustion process. The flow velocity and turbulence distributions are initialized without the need of simulating the gas exchange process, according to a validated technique.

As the number of actuators and sensors increases in modern combustion engines, the task of optimizing engine performance becomes increasingly complex. Efficient information processing techniques are therefore important, both for off-line calibration of engine maps, and on-line adjustments based on sensor data. In-cylinder pressure sensors are slowly spreading from laboratory use to production engines, thus making data with high temporal resolution of the combustion process available. The standard way of using the cylinder pressure data for control and diagnostics is to focus on a few important physical features extracted from the pressure trace, such as the combustion phasing CA50, the indicated mean effective pressure IMEP, and the ignition delay. These features give important information on the combustion process, but much information is lost as the information from the high-resolution pressure trace is condensed into a few key parameters.

The paper describes a novel method for calculating the residual gas fraction and the trapping efficiency in a 2 stroke engine. Assuming one dimensional compressible flow through the inlet and exhaust ports, the method estimates the instantaneous mass flowing in and out from the combustion chamber; later the residual gas fraction and trapping efficiency are estimated combining together the perfect displacement and perfect mixing scavenging models. It is assumed that when the intake port opens, the fresh mixture is pushing out the burned charge without any mixing and after a multiple of the time needed for the largest eddy to perform one rotation, the two gasses are instantly mixed up together and expelled. The result is a very simple algorithm that does not require much computational time and is able to estimate with high level of precision the trapping efficiency and the residual gas fraction in 2 stroke engines.

The emission control in heavy-duty vehicles today is based on predefined injection strategies and after-treatment systems such as SCR (selective catalytic reduction) and DPF (diesel particulate filter). State-of-the-art engine control is presently based on cycle-to-cycle resolution. The introduction of the crank angle resolved pressure measurement, from a piezo-based pressure sensor, enables the possibility to control the fuel injection based on combustion feedback while the combustion is occurring. In this paper a study is presented on the possibility to control NOx (nitrogen oxides) formation with a crank angle resolved NOx estimator as feedback. The estimator and the injection control are implemented on an FPGA (Field-Programmable Gate Array) to manage the inherent time constraints. The FPGA is integrated with the rest of the engine control system for injection control and measurement.

In recent years, stricter regulations on emissions and higher demands for more fuel efficient vehicles have led to a greater focus on increasing the efficiency of the internal combustion engine. Nowadays, there is increasing interest in the recovery of waste heat from different engine sources such as the coolant and exhaust gases using, for example, a Rankine cycle. In diesel engines 15% to 30% of the energy from the fuel can be lost to the coolant and hence, does not contribute to producing work on the piston. This paper looks at reducing the heat losses to the coolant by increasing coolant temperatures within a single cylinder Scania D13 engine and studying the effects of this on the energy balance within the engine as well as the combustion characteristics. To do this, a GT Power model was first validated against experimental data from the engine.

A 6-cylinder truck engine is modified for turbo charged dual fuel Homogeneous Charge Compression Ignition (HCCI) engine operation. Two different fuels, ethanol and n-heptane, are used to control the ignition timing. The objective of this study is to demonstrate high load operation of a full size HCCI engine and to discuss some of the typical constraints associated with HCCI operation. This study proves the possibility to achieve high loads, up to 16 bar Brake Mean Effective Pressure (BMEP), and ultra low NOx emissions, using turbo charging and dual fuel. Although the system shows great potential, it is obvious that the lack of inlet air pre heating is a drawback at low loads, where combustion efficiency suffers. At high loads, the low exhaust temperature provides little energy for turbo charging, thus causing pump losses higher than for a comparable diesel engine. Design of turbo charger therefore, is a key issue in order to achieve high loads in combination with high efficiency.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional liquid fuels to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

In the last couple of decades, countries have enacted new laws concerning environmental pollution caused by heavy-duty commercial and passenger vehicles. This is done mainly in an effort to reduce smog and health impacts caused by the different pollutions. One of the legislated pollutions, among a wide range of regulated pollutions, is nitrogen oxides (commonly abbreviated as NOx). The SCR (Selective Catalytic Reduction) was introduced in the automotive industry to reduce NOx emissions leaving the vehicle. The basic idea is to inject a urea solution (AdBlue™) in the exhaust gas before the gas enters the catalyst. The optimal working temperature for the catalyst is somewhere in the range of 300 to 400 °C. For the reactions to occur without a catalyst, the gas temperature has to be at least 800 °C. These temperatures only occur in the engine cylinder itself, during and after the combustion.

This article deals with study of ionization current sensing technique's signal characteristics while operating with pre-chamber spark plug to achieve plasma jet ignition in a 6 cylinder 9 liter turbo-charged natural gas engine under EGR and excess air dilution. Unlike the signal with conventional spark plug which can be divided into distinct chemical and thermal ionization peaks, the signal with pre-chamber spark plug shows a much larger first peak and a negligible second peak thereafter. Many studies in past have found the time of second peak coinciding with the time of maximum cylinder pressure and this correlation has been used as an input to combustion control systems but the absence of second peak makes application of this concept difficult with pre-chamber spark plug.

Modeling the combustion process of a diesel-biodiesel fuel spray in a 3-dimensional (3D) computational fluid dynamics (CFD) domain remains challenging and time-consuming despite the recent advancement in computing technologies. Accurate representation of the in-cylinder processes is essential for CFD studies to provide invaluable insights into these events, which are typically limited when using conventional experimental measurement techniques. This is especially true for emerging new fuels such as biodiesels since fundamental understanding of these fuels under combusting environment is still largely unknown. The reported work here is dedicated to evaluating the Adaptive Local Mesh Refinement (ALMR) approach in OpenFOAM® for improved simulation of reacting biodiesel fuel spray. An in-house model for thermo-physical and transport properties is integrated to the code, along with a chemical mechanism comprising 113 species and 399 reactions.

The definition of a robust methodology to perform a full-cycle CFD simulation of IC engines requires as first step the availability of a reliable grid generation tool, which does not only have to guarantee a high quality mesh but also has to prove to be efficient in terms of required time. In this work the authors discuss a novel approach entirely based on the OpenFOAM technology, in which the available 3D grid generator was employed to automatically create meshes containing hexahedra and split-hexahedra from triangulated surface geometries in Stereolithography (STL) format. The possibility to introduce local refinements and boundary layers makes this tool suitable for IC engine simulations. Grids are sequentially generated at target crank angles which are automatically determined depending on user specified settings such as maximum mesh validity interval and quality parameters like non-orthogonality, skewness and aspect ratio.

Prediction of in-cylinder flows and fuel-air mixing are two fundamental pre-requisites for a successful simulation of direct-injection engines. Over the years, many efforts were carried out in order to improve available turbulence and spray models. However, enhancements in physical modeling can be drastically affected by how the mesh is structured. Grid quality can negatively influence the prediction of organized charge motion structures, turbulence generation and interaction between in-cylinder flows and injected sprays. This is even more relevant for modern direct injection engines, where multiple injections and control of charge motions are employed in a large portion of the operating map. Currently, two different approaches for mesh generation exist: manual and automatic. The first makes generally possible to generate high-quality meshes but, at the same time, it is very time consuming and not completely free from user errors.

Homogeneous Charge Compression Ignition (HCCI) holds great promises for good fuel economy and low emissions of NOX and soot. The concept of HCCI is premixed combustion of a highly diluted mixture. The dilution limits the combustion temperature and thus prevents extensive NOX production. Load is controlled by altering the quality of the charge, rather than the quantity. No throttling together with a high compression ratio to facilitate auto ignition and lean mixtures results in good brake thermal efficiency. However, HCCI also presents challenges like how to control the combustion and how to achieve an acceptable load range. This work is focused on solutions to the latter problem. The high dilution required to avoid NOX production limits the mass of fuel relative to the mass of air or EGR. For a given size of the engine the only way to recover the loss of power due to dilution is to force more mass through the engine.

The increasing diffusion of gasoline direct injection (GDI) engines requires a more detailed and reliable description of the phenomena occurring during the fuel injection process. As well known the thermal and fluid-dynamic conditions present in the combustion chamber greatly influence the air-fuel mixture process deriving from GDI injectors. GDI fuel sprays typically evolve in wide range of ambient pressure and temperatures depending on the engine load. In some particular injection conditions, when in-cylinder pressure is relatively low, flash evaporation might occur significantly affecting the fuel-air mixing process. In some other particular injection conditions spray impingement on the piston wall might occur, causing high unburned hydrocarbons and soot emissions, so currently representing one of the main drawbacks of GDI engines.

The abatement of carbon dioxide and pollutant emissions on motorbike spark-ignition (SI) engines is a challenging task, considering the small size, the low cost and the high power-to-weight ratio required by the market for such powertrain. In this context, the passive pre-chamber (PPC) technology is an attractive solution. The combustion duration can be reduced by igniting the air-fuel mixture inside a small volume connected to the cylinder, unfolding the way to high engine efficiencies without penalization of the peak performance. Moreover, no injectors are needed inside the PPC, guaranteeing a cheap and fast retrofitting of the existing fleet. In this work, a 3D computational fluid dynamics (CFD) investigation is carried out over an experimental configuration of motorbike SI engine, operated at fixed operating conditions with both traditional and PPC configurations.

The thorough understanding of the effects due to the fuel direct injection process in modern gasoline direct injection engines has become a mandatory task to meet the most demanding regulations in terms of pollutant emissions. Within this context, computational fluid dynamics proves to be a powerful tool to investigate how the in-cylinder spray evolution influences the mixture distribution, the soot formation and the wall impingement. In this work, the authors proposed a comprehensive methodology to simulate the air-fuel mixture formation into a gasoline direct injection engine under multiple operating conditions. At first, a suitable set of spray sub-models, implemented into an open-source code, was tested on the Engine Combustion Network Spray G injector operating into a static vessel chamber. Such configuration was chosen as it represents a typical gasoline multi-hole injector, extensively used in modern gasoline direct injection engines.

Predictive combustion models are useful tools towards the development of clean and efficient engines operating with alternative fuels. This work intends to validate two different combustion models on compression-ignition engines fueled with Dimethyl Ether. Both approaches give a detailed characterization of the combustion kinetics, but they substantially differ in how the interaction between fluid-dynamics and chemistry is treated. The first one is single-flamelet Representative Interactive Flamelet, which considers turbulence-kinetic interaction but cannot correctly describe the stabilization of the flame. The second, named Tabulated Well Mixed, correctly accounts for local flow and mixture conditions but does not consider interaction between turbulence and chemistry. An experimental campaign was carried out on a heavy-duty truck engine running on DME at a constant load considering trade-off of EGR and SOI.