Search Results

Ammonia has emerged as a promising carbon-free alternative fuel for internal combustion engines (ICE), particularly in large-bore engine applications. However, integrating ammonia into conventional engines presents challenges, prompting the exploration of innovative combustion strategies like dual-fuel combustion. Nitrous oxide (N2O) emissions have emerged as a significant obstacle to the widespread adoption of ammonia in ICE. Various studies suggest that combining exhaust gas recirculation (EGR) with adjustments in inlet temperature and diesel injection timing can effectively mitigate nitrogen oxides (NOx) emissions across diverse operating conditions in dual-fuel diesel engines.

Increasing awareness of the harmful effects on the environment of traditional Internal Combustion Engines (ICE) drives the industry toward cleaner powertrain technologies such as battery-driven Electric Vehicles (EV). Nonetheless, the high energy density of Li-Ion batteries can cause strong exothermic reactions under certain conditions that can lead to catastrophic results, called Thermal Runaway (TR). Hence, a strong effort is being made to understand this phenomenon and increase battery safety. Specifically, the vented gases and their ignition can cause the propagation of this phenomenon to adjacent batteries in a pack. In this work, Computational Fluid Dynamics (CFD) is employed to predict this venting process in an LG18650 cylindrical battery. The shape of the venting cap deformation obtained from experimental results was introduced in the computational model.

The employment of hydrogen as energy carrier for transportation sector represents a significant challenge for powertrains. Spark-ignition (SI) engines are feasible and low-cost devices to convert the hydrogen chemical energy into mechanical work. However, significant efforts are needed to successfully retrofit the available configurations. The computational fluid dynamics (CFD) modelling represents a useful tool to support experiments, clarifying the impact of the engine characteristics on both the mixture preparation and the combustion development. In this work, a CFD investigation is carried out on typical light-duty SI engine configurations, exploring the two main strategies of hydrogen addition: port fuel injection (PFI) and direct injection (DI). The purpose is to assess the behaviour of widely-used numerical models and methodologies when hydrogen is employed instead of traditional carbon-based fuels.

Mitigating human-made climate change means cutting greenhouse gas (GHG) emissions, especially carbon dioxide (CO2), which causes climate change. One approach to achieving this is to move to a carbon-free economy where carbon emissions are offset by carbon removal or sequestration. Transportation is a significant contributor to CO2 emissions, so finding renewable alternatives to fossil fuels is crucial. Green hydrogen-fueled engines can reduce the carbon footprint of transportation and help achieve a carbon-free economy. However, hydrogen combustion is challenging in an internal combustion engine due to flame instabilities, pre-ignition, and backfire. Numerical modeling of hydrogen combustion is necessary to optimize engine performance and reduce emissions. In this work, a numerical methodology is proposed to model lean hydrogen combustion in a turbocharged port fuel injection (PFI) spark-ignition (SI) engine for automotive applications.

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.

Fuel film deposits on combustion chamber walls are understood to be the main source of particle emissions in GDI engines under homogenous charge operation. More precisely, the liquid film that remains on the injector tip after the end of injection is a fuel rich zone that undergoes pyrolysis reactions leading to the formation of poly-aromatic hydrocarbons (PAH) known to be the precursors of soot. The physical phenomena accompanying the fuel film deposit, evaporation, and the chemical reactions associated to the injector film are not yet fully understood and require high fidelity CFD simulations and controlled experimental campaigns in optically accessible engines. To this end, a simplified model based on physical principles is developed in this work, which couples an analytical model for liquid film formation and evaporation on the injector tip with a stochastic particle dynamics model for particle formation.

Lithium-ion batteries have a well-documented failure tendency under abuse conditions with a significant release of gases and heat. This failure originated from the decomposition reactions within the battery’s electrochemical components, resulting in gas generation and increased internal pressure. To optimize battery safety, it is crucial to understand their behaviors when subjected to abuse conditions. The 18650 format cell incorporates a vent mechanism within a crimped cap to relieve pressure and mitigate the risk of rupture. However, cell venting introduces additional safety concerns associated with flammable gases and liquid electrolyte that flow into the environment. Experiments were performed with two venting caps with well-known geometries to quantify key parameters in describing the external dynamic flow of battery venting and to validate a CFD model.

Fleet electrification has been demonstrated as a feasible solution to decarbonize the heavy-duty transportation sector. The combination of hybridization and advanced combustion concepts may provide further advantages by also introducing reductions on criteria pollutants such as nitrogen oxides and soot. In this scenario, the interplay among the different energy paths must be understood and quantified to extract the full potential of the powertrain. One of the key devices in such powertrains is the battery, which involves different aspects regarding operation, safety, and degradation. Despite this complexity, most of the models still rely on resistance-capacity models to describe the battery operation. These models may lead to unpractical results since the current flow is governed by limiters rather than physical laws. Additionally, phenomena related with battery degradation, which decreases the nominal capacity and enhances the heat generation are also not considered in this approach.

Electrification and hybridization of powerplants in the transportation sector is one of the most important changes in the last few decades. Lithium-ion batteries are the main energy storage systems, but despite the maturity of this technology, it has certain constrains compared to traditional internal combustion engines in the day-to-day usage. As the operating conditions of the batteries are pushed to the limits to overcome certain disadvantages relative to other conventional systems like charge and discharge times or vehicle driving range, new concerns and safety limitations must be considered. High power rates and cooling deficiencies can produce excessive operating temperatures within the cells, leading to problems with degradation or even unchain chemical reactions that can end in thermal runaway, one of the most worrying failure modes attaining electric platforms nowadays.

Split injection processes have been analyzed by means of a Quasi-1D spray model that has been recently coupled to a laminar tabulated unsteady-flamelet progress-variable (UFPV) combustion model. The modelling approach can predict ignition delay and lift-off for long injection profiles, and it is now extended to a two-pulse injection scheme. In spite of the simplicity of the approach, relevant phenomena are adequately reproduced. In particular, the faster penetration of the second injection pulse compared to the first one is captured by the model both under inert and reacting conditions. The second pulse ignites much faster than the first one due to the injection into the remnants of the first one, where high temperature oxygen-depleted regions can be found. Ignition of the second pulse happens as soon as the first pulse reaches this region, with a faster low- to high-temperature transition.

The need to control global warming by regulating automotive emission levels has led to a lot of changes in the policies of different countries globally, specifically the United States (US) and the European Union (EU). More recently, the governments have been strongly pushing the integration of Electric Vehicles (EVs) in the market to replace the conventional Internal Combustion Engine (ICE) vehicles for CO₂ emissions reduction, with the enforcement of 50% EV sales by 2030 in the US and complete 100% by 2035 in the EU for passenger cars. However, these policies are misleading by considering EVs as zero emission vehicles, as there is no such technology yet available that has zero emissions during its lifecycle. During the manufacturing phase, any vehicle produced gives out emissions, with EVs emitting even higher than the conventional ICE vehicles with their battery manufacturing.

In recent years, the automotive industry has been increasingly committed to developing new solutions for better and more efficient engines. One of them is the use of new insulating materials (thermal conductivity < 0.4 W/m-K, heat capacitance < 500 kJ/m3-K) to coat the engine combustion chamber walls, as well as the exhaust manifold. The main idea when coating the combustion chamber with these materials is to obtain a reduction of the temperature difference (thermal swing) between gas and walls during the engine cycle and minimize heat losses. Experimental measurements of the possible performance improvements are very difficult to obtain, mainly because the techniques available to measure wall temperature are limited. Therefore, simulations are typically used to investigate insulated combustion chambers. Nevertheless, the new generation of insulating coatings is posing challenges to numerical modelling, as layer thickness is very small (~100 μm).

Computational fluid dynamics (CFD) modeling has many potentials for the design and calibration of modern and future engine concepts, including facilitating the exploration of operation conditions and casting light on the involved physical and chemical phenomena. As more attention is paid to the matching of different fuel types and combustion strategies, the use of detailed chemistry in characterizing auto-ignition, flame stabilization processes and the formation of pollutant emissions is becoming critical, yet computationally intensive. Therefore, there is much interest in using tabulated approaches to account for detailed chemistry with an affordable computational cost. In the present work, the tabulated flamelet progress variable approach (TFPV), based on flamelet assumptions, was investigated and validated by simulating constant-volume Diesel combustion with primary reference fuels - binary mixtures of n-heptane and iso-octane.

An existing one-dimensional (1D) spray model, which successfully captures inert spray processes, has been extended to enable prediction of ignition delay and lift-off length under reacting conditions. For that purpose, an additional transport equation for the progress variable has been incorporated, which includes detailed chemistry effects by means of a tabulation method based upon an external flamelet solver. The transport equation for the progress variable is solved in a quasi-1D fashion, along presumed mixture fraction trajectories, while the 1D approach is retained for the mixture fraction and axial velocity fields. The paper includes the model development, as well as the validation against Spray A measurements from the Engine Combustion Network. In spite of the simplified approach, the model captures some of the experimental trends of the lift-off length and ignition delay with a quite low computational cost.

The use of predictive models in the study of Internal Combustion Engines (ICE) allows reducing developing cost and times. However, those models are challenging due to the complex and multi-phase phenomena occurring in the combustion chamber, but also because of the different spatial and temporal scales in different components of the injection systems. This work presents a methodology to accurately simulate the spray by Discrete Droplet Models (DDM) without experimentally measuring the injector mass flow rate and/or momentum flux. Transient nozzle flow simulations are used instead to define the injection conditions of the spray model. The methodology is applied to a multi-hole Gasoline Direct injection (GDi) injector. Firstly, the DDM constant values are calibrated comparing simulation results to Diffused Back-light Illumination (DBI) experimental technique results. Secondly, transient nozzle flow simulations are carried out.

Experimental visualization of current gasoline direct injection (GDi) systems are even more complicated especially due to the proximity of spray plumes and the interaction between them. Computational simulations may provide additional information to understand the complex phenomena taking place during the injection process. Nozzle flow simulations with a Volume-of-Fluid (VOF) approach can be used not only to analyze the flow inside the nozzle, but also the first 2-5 mm of the spray. A methodology to obtain plume direction and spray angle from the simulations is presented. Results are compared to experimental data available in the literature. It is shown that plume direction is well captured by the model, whilst the uncertainty of the spray angle measurements does not allow to clearly validate the developed methodology.

It is known that in-cylinder airflow structures during intake and compression strokes deeply affects the combustion process in compression ignition (CI) engines. This work presents a methodology for the analysis of the swirling structures by means of the CFD proprietary code Converge 2.3. The methodology is based on the CFD modelling and the comparison of results with in-cylinder velocity fields measured by particle image velocimetry (PIV). Furthermore, the analysis is extended to the accuracy evaluation of other methods available to define the flow in the cylinder of internal combustion engines, such as experiments in steady flow rigs. These methods, in junction with simple phenomenological models, have been traditionally used to determine some of the fundamental variables that define the in-cylinder flow in ICE engines. The CFD analysis is focused in the flow structures around top dead centre (TDC) at the end of the compression stroke.

The Engine Combustion Network (ECN) is a coordinate effort from research partners from all over the world which aims at creating a large experimental database to validate CFD calculations. Two injectors from ECN, namely Spray C and D, have been compared in a constant pressure flow vessel, which enables a field of view of more than 100 mm. Both nozzles have been designed with similar flow metrics, with Spray D having a convergent hole shape and Spray C a cylindrical one, the latter being therefore more prone to cavitation. Although the focus of the study is on reacting conditions, some inert cases have also been measured. High speed schlieren imaging, OH* chemiluminescence visualization and head-on broadband luminosity have been used as combustion diagnostics to evaluate ignition delay, lift off length and reacting tip penetration. Parametric variations include ambient temperature, oxygen content and injection pressure variations.

It is challenging to develop highly efficient and clean engines while meeting user expectations in terms of performance, comfort, and drivability. One of the critical aspects in this regard is combustion noise control. Combustion noise accounts for about 40 percent of the overall engine noise in typical turbocharged diesel engines. The experimental investigation of noise generation is difficult due to its inherent complexity and measurement limitations. Therefore, it is important to develop efficient numerical strategies in order to gain a better understanding of the combustion noise mechanisms. In this work, a novel methodology was developed, combining computational fluid dynamics (CFD) modeling and genetic algorithm (GA) technique to optimize the combustion system hardware design of a high-speed direct injection (HSDI) diesel engine, with respect to various emissions and performance targets including combustion noise.

Knock is a major bottleneck to achieving higher thermal efficiency in spark ignition (SI) engines. The overall tendency to knock is highly dependent on fuel anti-knock quality as well as engine operating conditions. It is, therefore, critical to gain a better understanding of fuel-engine interactions in order to develop robust knock mitigation strategies. In the present work, a numerical model based on three-dimensional (3-D) computational fluid dynamics (CFD) was developed to capture knock in a Cooperative Fuel Research (CFR) engine. For combustion modeling, a hybrid approach incorporating the G-equation model to track turbulent flame propagation, and a homogeneous reactor multi-zone model to predict end-gas auto-ignition ahead of the flame front and post-flame oxidation in the burned zone, was employed.