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Hydrogen engines are currently considered as a viable solution to preserve the internal combustion engine as a power unit for vehicle propulsion. In particular, lean-burn gasoline Spark-Ignition (SI) engines have been a major subject of investigations due to the reduced emission levels and high thermodynamic efficiency. This strategy is suitable for the purpose of passenger car applications and cannot be tailored in the field of high performance engine, where the air mass delivered would require oversized turbocharging systems or more complex charging solutions. For this reason, the range of stoichiometric feeding condition is explored in the high performance engine, leading to the consequent issue of abatement of pollutant emissions. In this work a 1D model will be applied to the modeling of a V8 engine fueled with DI of hydrogen. The engine has been derived by a gasoline configuration and adapted to hydrogen in such a way to keep the same performance.

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.

Nowadays quasi-3D approaches are included in many commercial and research 1D numerical codes, in order to increase their simulation accuracy in presence of complex shape 3D volumes, e.g. plenums and silencers. In particular, these are regarded as valuable approaches for application during the design phase of an engine, for their capability of predicting non-planar waves motion and, on the other hand, for their low requirements in terms of computational runtime. However, the generation of a high-quality quasi-3D computational grid is not always straightforward, especially in case of complex elements, and can be a time-consuming operation, making the quasi-3D tool a less attractive option. In this work, a quasi-3D module has been implemented on the basis of the open-source CFD code OpenFOAM and coupled with the 1D code GASDYN.

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.

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

In order to reduce fuel consumption, companies have been looking at hybridizing vehicles. So far, two main hybridization options have been considered: electric and hydraulic hybrids. Because of light duty vehicle operating conditions and the high energy density of batteries, electric hybrids are being widely used for cars. However, companies are still evaluating both hybridization options for medium and heavy duty vehicles. Trucks generally demand very large regenerative power and frequent stop-and-go. In that situation, hydraulic systems could offer an advantage over electric drive systems because the hydraulic motor and accumulator can handle high power with small volume capacity. This study compares the fuel displacement of class 6 trucks using a hydraulic system compared to conventional and hybrid electric vehicles. The paper will describe the component technology and sizes of each powertrain as well as their overall vehicle level control strategies.

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.

Nowadays a great attention is paid to the level and quality of noise radiated from the tailpipe end of intake and exhaust systems, to control the gas dynamic noise emitted by the engine as well as the characteristics of the cabin interior sound. The muffler geometry can be optimized consequently, to attenuate or remark certain spectral components of the engine noise, according to the result expected. Evidently the design of complex silencing systems is a time-consuming operation, which must be carried out by means of concurrent experimental measurements and numerical simulations. In particular, 1D and multiD linear/non-linear simulation codes can be applied to predict the silencer behavior in the time and frequency domain. This paper describes the development of a 1D-multiD integrated approach for the simulation of complex muffler configurations such as reverse chambers with inlet and outlet pipe extensions and perforated silencers with the addition of sound absorbing material.

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.

Striving for sustainable transportation solutions, hydrogen is often identified as a promising energy carrier and internal combustion engines are seen as a cost effective consumer of hydrogen to facilitate the development of a large-scale hydrogen infrastructure. Driven by efficiency and emissions targets defined by the U.S. Department of Energy, a research team at Argonne National Laboratory has worked on optimizing a spark-ignited direct injection engine for hydrogen. Using direct injection improves volumetric efficiency and provides the opportunity to properly stratify the fuel-air mixture in-cylinder. Collaborative 3D-CFD and experimental efforts have focused on optimizing the mixture stratification and have demonstrated the potential for high engine efficiency with low NOx emissions. Performance of the hydrogen engine is evaluated in this paper over a speed range from 1000 to 3000 RPM and a load range from 1.7 to 14.3 bar BMEP.

Pursuing a sustainable energy scenario for transportation requires the blending of renewable oxygenated fuels such as alcohols into commercial hydrocarbon fuels. From a chemical kinetic perspective, this requires the accurate description of both hydrocarbon reference fuels (n-heptane, iso-octane, toluene, etc.) and oxygenated fuels chemistry. A recent systematic investigation of linear C2-C5 alcohols ignition in a rapid compression machine at p = 10-30 bar and T = 650- 900 K has extended the scarcity of fundamental data at such conditions, allowing for a revision of the low temperature chemistry for alcohol fuels in the POLIMI mechanism. Heavier alcohols such as n-butanol and n-pentanol present ignition characteristic of interest for application in HCCI engines, due to the presence of the hydroxyl moiety reducing their low temperature reactivity compared to the parent linear alkanes (i.e. higher octane number).

The dynamics and evolution of turbulent structures inside an engine-like geometry are investigated by means of Large Eddy Simulation. A simplified configuration consisting of a flat-top cylinder head with a fixed, axis-centered valve and low-speed piston has been simulated by the finite volume CFD code OpenFOAM®; the standard version of the software has been extended to include the compressible WALE subgrid-scale model, models for the generation of synthetic turbulence, some improvements to the mesh motion strategy and algorithms for LES data post-processing. In order to study both the initial transient and the quasi- steady operating conditions, ten complete engine cycles have been simulated. Phase and spatial averages have been performed over cycles three to ten in order to extract first and second moment of velocity; these quantities have then been used to validate the numerical procedure by comparison against experimental data.

The objective of this study is to demonstrate the design and construction of an innovative active gear-shift and clutch for racecars, applied to a Formula Student car, based on the use of DC gear-motors. Racecars require extremely quick gear-shifts and every system to be as light as possible. The proposed solution is designed to reduce energy consumption, weight and improve gear-shift precision compared to traditionally employed electro-hydraulic solutions, although maintaining state of the art performances.

In this paper the low temperature reduction process of nitrates stored at high temperatures over model Pt-Ba/Al2O3 LNT catalysts using both H2 and C3H6 is analyzed. The results indicate that over the Pt-Ba/Al2O3 catalyst the reduction of stored NOx with both H2 and C3H6 occurs at temperature below those corresponding to their thermal stability. Accordingly, the reduction process occurs through a Pt-catalyzed surface reaction, which does not involve, as a preliminary step, the thermal decomposition of the adsorbed NOx species. The occurrence of such a pathway also requires the co-presence of the storage element and of the noble metal on the same support.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

This paper presents a unified modeling environment to simulate vehicle driving and powertrain operations within the context of the surrounding environment, including interactions between vehicles and between vehicles and the road. The goal of this framework is to facilitate the analysis of the energy impacts of vehicle connectivity and automation, as well as the development of eco-driving algorithms. Connectivity and automation indeed provide the potential to use information about the environment and future driving to minimize energy consumption. To achieve this goal, the designers of eco-driving control strategies need to simulate a wide range of driving situations, including the interactions with other vehicles and the infrastructure in a closed-loop fashion.