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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.

The demand of game-changing technologies to improve efficiency and abate emissions of heavy-duty trucks and off-road vehicles promoted the development of novel engine concepts. The Recuperated Split-Cycle (R-SC) engine allows to recover the exhaust gases energy into the air intake by separating the compression and combustion stages into two different but connected cylinders: the compressor and expander, respectively. The result is a potential increase of the engine thermal efficiency. Accordingly, the 3D-computational fluid dynamics (CFD) modelling of the gas exchange process and the combustion evolution inside the expander becomes essential to control and optimize the R-SC engine concept. This work aims to address the most challenging numerical aspects encountered in a 3D numerical simulation of an R-SC engine.

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.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

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.

The paper illustrates and validates a novel predictive combustion model for the estimation of performances and pollutant production in CI engines. The numerical methodology was developed by the authors for near real-time applications, while aiming at an accurate description of the air mixing process by means of a multi-zone approach of the air-fuel mass. Charge stratification is estimated via a 2D representation of the fuel spray distribution that is numerically derived by an axial one-dimensional control-volume description of the direct injection. The radial coordinate of each control volume is reconstructed a posteriori by means of a local distribution function. Fuel mass clustered in each zone is further split in ‘liquid’, ‘unburnt’ and ‘burnt’ sub-zones, given the local properties of the fuel spray control volumes with respect to space-time location of modelled ignition delay, liquid length, and flame lift-off.

The present work describes the numerical modeling of medium-speed marine engines, operating in a fumigated dual-fuel mode, i.e. with the second fuel injected in the ports. This engine technology allows reducing engine-out emissions while maintaining the engine efficiency and can be fairly easily retrofitted from current diesel engines. The main premixed fuel that is added can be a low-carbon one and can additionally be of a renewable nature, thereby reducing or even completely removing the global warming impact. To fully optimize the operational parameters of such a large marine engine, computational fluid dynamics can be very helpful. Accurately describing the combustion process in such an engine is key, as the prediction of the heat release and the pollutant formation is crucial. Auto-ignition of the diesel fuel needs to be captured, followed by the combustion and flame propagation of the premixed fuel.

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.

A methodology to estimate the mass of particulate retained in a catalyzed particulate filter as a function of measured total pressure drop, volumetric flow rate, exhaust temperature, exhaust gas viscosity and cake and wall permeability applicable to real-time computation is discussed. This methodology is discussed from the view point of using it to indicate when to initiate active regeneration and as an On-Board Diagnostic tool to detect filter failures. Steady-state loading characterization experiments were conducted on a catalyzed diesel particulate filter (CPF) in a Johnson Matthey CCRT® (catalyzed continuously regenerating trap) system. The experiments were performed using a 10.8 L 2002 Cummins ISM heavy-duty diesel engine. Experiments were conducted at 20, 60 and 75% of full engine load (1120 Nm) and rated speed (2100 rpm) to measure the pressure drop, transient filtration efficiency, particulate mass balance, and gaseous emissions.

In order to further characterize and optimize the performance of Selective Catalytic Reduction (SCR) aftertreatment systems used on heavy-duty diesel engines, an accurately calibrated high-fidelity multi-step global kinetic SCR model and a reduced order estimator for on-board diagnostic (OBD) and control are desirable. In this study, a Cu-zeolite SCR catalyst from a 2010 Cummins ISB engine was experimentally studied in a flow reactor using carefully designed protocols. A 2-site SCR model describing mass transfer and the SCR chemical reaction mechanisms is described in the paper. The model was calibrated to the reactor test data sets collected under temperatures from 200 to 425 °C and SCR space velocities of 60000, 90000, and 120000 hr-1. The model parameters were calibrated using an optimization code to minimize the error between measured and simulated NO, NO₂, N₂O, and NH₃ gas concentration time histories.

In this paper, numerical simulations of an automotive-size optical diesel engine have been conducted employing the Reynolds-Averaged Navier-Stokes (RANS) equations with the standard k-ε turbulence model and a reduced n-heptane chemical mechanism implemented in OpenFOAM. The current paper builds on a previous work where the model has been validated for the same engine using optical diagnostic data. The present study investigates numerically the influence of different operating conditions - relevant for modern diesel engines - on the mixture formation development under non-reactive conditions as well as low- and high-temperature ignition behaviour and flame evolution in the presence of strong jet-wall interactions typically encountered in automotive-size diesel engines. Also, emissions of CO and unburned hydrocarbons (UHC) are considered.

In this paper, computation fluid dynamics (CFD) simulations are employed to describe the effect of flow parameters on the formation of soot and NOx in a heavy duty engine under low load and high load. The complexity of diesel combustion, specially when soot, NOx and other emissions are of interest, requires using a detailed chemical mechanism to have a correct estimation of temperature and species distribution. In this work, Multiple Representative Interactive Flamelets (MRIF) method is employed to describe the chemical reactions, ignition, flame propagation and emissions in the engine. A phenomenological model for soot formation, including soot nucleation, coagulation and oxidation with O2 and OH is incorporated into the flamelet combustion model. Different strategies for modelling NOx are chosen to take into account the longer time scale for NOx formation. The numerical results are compared with experimental data to show the validity of the model for the cases under study.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

The capability to detect combustion in a diesel engine has the potential of being an important control feature to meet increasingly stringent emission regulations and for the development of alternative combustion strategies such as HCCI and PCCI. In this work, block mounted accelerometers are investigated as potential feedback sensors for detecting combustion characteristics in a high-speed, high pressure common rail (HPCR), 1.9L diesel engine. Accelerometers are positioned in multiple placements and orientations on the engine, and engine testing is conducted under motored, single and pilot-main injection conditions. Engine tests are then conducted at varying injection timings to observe the resulting time and frequency domain changes of both the pressure and acceleration signals.

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.

An accurate estimation of cycle-by-cycle in-cylinder mass and the composition of the cylinder charge is required for spark-ignition engine transient control strategies to obtain required torque, Air-Fuel-Ratio (AFR) and meet engine pollution regulations. Mass Air Flow (MAF) and Manifold Absolute Pressure (MAP) sensors have been utilized in different control strategies to achieve these targets; however, these sensors have response delay in transients. As an alternative to air flow metering, in-cylinder pressure sensors can be utilized to directly measure cylinder pressure, based on which, the amount of air charge can be estimated without the requirement to model the dynamics of the manifold.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

Passive regeneration (oxidation of particulate matter without using an external energy source) of particulate filters in combination with active regeneration is necessary for low load engine operating conditions. For low load conditions, the exhaust gas temperatures are less than 250°C and the PM oxidation rate due to passive regeneration is less than the PM accumulation rate. The objective of this research was to experimentally investigate active regeneration of a catalyzed particulate filter (CPF) using diesel fuel injection in the exhaust gas after the turbocharger and before a diesel oxidation catalyst (DOC) and to collect data for extending the MTU 1-D 2-layer model to include the simulation of active regeneration. The engine used in this study was a 2002 Cummins ISM turbo charged 10.8 L heavy duty diesel engine with cooled EGR. The exhaust after-treatment system consisted of a Johnson Matthey DOC and CPF (a CCRT®).

Active regeneration experiments were performed on a Cummins 2007 aftertreatment system by hydrocarbon dosing with injection of diesel fuel downstream of the turbocharger. The main objective was to characterize the thermal oxidation rate as a function of temperature and particulate matter (PM) loading of the catalyzed particulate filter (CPF). Partial regeneration tests were carried out to ensure measureable masses are retained in the CPF in order to model the oxidation kinetics. The CPF was subsequently re-loaded to determine the effects of partial regeneration during post-loading. A methodology for gathering particulate data for analysis and determination of thermal oxidation in a CPF system operating in the engine exhaust was developed. Durations of the active regeneration experiments were estimated using previous active regeneration work by Singh et al. 2006 [1] and were adjusted as the experiments progressed using a lumped oxidation model [2, 3].

A high-fidelity multi-step global kinetic Selective Catalytic Reduction (SCR) model which can predict SCR performance in engine exhaust systems is desirable for optimizing the SCR system, designing on-vehicle control systems and on-board diagnostic (OBD) functions. In this study, a Cu-zeolite SCR catalyst in the exhaust of a 2010 Cummins 6.7L ISB diesel engine was experimentally studied under both steady-state and transient conditions. Steady-state engine tests spanned SCR inlet temperatures from 250 to 400°C with a constant space velocity of 60 khr-1. A 1-D Cu-zeolite model originally developed from reactor data was improved and calibrated to the steady-state engine experimental data. The calibrated model is capable of predicting NO/NO₂ reduction, NH₃ slip, and NH₃ storage associated phenomena.