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The present paper describes the first results of a cooperative research project between GM Powertrain Europe and Istituto Motori of CNR aimed at studying the impact of Fatty-Acid Methyl Esters (FAME) and gas-to-liquid (GTL) fuel blends on the performance, emissions and fuel consumption of modern automotive diesel engines. The tests were performed on the architecture of GM 1.9L Euro4 diesel engine for passenger car application, both on optical single-cylinder and on production four-cylinder engines, sharing the same combustion system configuration. Various blends of biodiesels as well as reference diesel fuel were tested. The experimental activity on the single-cylinder engine was devoted to an in-depth investigation of the combustion process and pollutant formation, by means of different optical diagnostics techniques, based on imaging multiwavelength spectroscopy.

In the present paper, two different methodologies are adopted and critically integrated to analyze the knock behavior of a last generation small size spark ignition (SI) turbocharged VVA engine. Particularly, two full load operating points are selected, exhibiting relevant differences in terms of knock proximity. On one side, a knock investigation is carried out by means of an Auto-Regressive technique (AR model) to process experimental in-cylinder pressure signals. This mathematical procedure is used to estimate the statistical distribution of knocking cycles and provide a validation of the following 1D-3D knock investigations. On the other side, an integrated numerical approach is set up, based on the synergic use of 1D and 3D simulation tools. The 1D engine model is developed within the commercial software GT-Power™. It is used to provide time-varying boundary conditions (BCs) for the 3D code, Star-CD™.

An innovative quasi-dimensional multizone combustion model for the spray formation, combustion and emission formation analysis in DI diesel engines was assessed and applied to an optical single cylinder engine. The model, which has been recently presented by the authors, integrates a predictive non stationary 1D spray model developed by the Sandia National Laboratory, with a diagnostic multizone thermodynamic model. The 1D spray model is capable of predicting the equivalence ratio of the fuel during the mixing process, as well as the spray penetration. The multizone approach is based on the application of the mass and energy conservation laws to several homogeneous zones identified in the combustion chamber. A specific submodel is also implemented to simulate the dilution of the burned gases. Soot formation is modeled by an expression which derives from Kitamura et al.'s results, in which an explicit dependence on the local equivalence ratio is considered.

Knock is one of the main limitations on Spark-Ignited (SI) Internal Combustion Engine (ICE) performance and efficiency and so has been the object of study for over one hundred years. Great strides have been made in terms of understanding in that time, but certain rather elementary practical problems remain. One of these is how to interpret if a running engine is knocking and how likely this is to result in damage. Knocking in a development environment is typically quantified based on numerical descriptions of the high frequency content of a cylinder pressure signal. Certain key frequencies are observed, which Draper [1] explained with fundamental acoustic theory back in 1935. Since then, a number of approaches of varying complexity have been employed to correlate what is happening within the chamber with what is measured by a pressure transducer.

In view of the new emission regulations seeking to lower the particle cut-off size down to the current 23 nm, an extensive comprehension on the nature of sub-23 nm particles is crucial. In this regard, a new challenge lies ahead considering an even more massive use of biofuels. The objective of this research study was to characterize the sub-23 nm particles and to evaluate their volatile organic fraction (VOF) from a high performance, 1.8 L gasoline direct injection (GDI) engine under the Worldwide harmonized Light vehicles Test Cycle (WLTC). Particle emissions were measured through an Engine Exhaust Particle Sizer (EEPS) capable of particle sizing and counting in the range 5.6 - 560 nm. The sampling and conditioning were performed by both a single diluter and the Dekati Engine Exhaust Diluter (DEED) a Particle Measurement Programme (PMP) compliant sample conditioning system.

Methane supply in diesel engines operating in dual fuel mode has demonstrated to be effective for the reduction of particulate matter and nitric oxides emissions from this type of engine. In particular, methane is injected into the intake manifold to form a premixed charge with air, while a reduced amount of diesel oil is still directly injected to ignite the mixture inside the cylinder. As a matter of fact, the liquid fuel burns following the usual diffusive combustion, so activating the gaseous fuel oxidation in a premixed flame. Clearly, the whole combustion process appears to be more complex to be described in a CFD simulation, mainly because it is not always possible to select in the 3-dimensional codes a different combustion model for each fuel and, also, because other issues arise from the interaction of the two fuels.

In recent years, internal combustion engine (ICE) downsizing coupled with turbocharging was considered the most effective path to improve engine efficiency at low load, without penalizing rated power/torque performance at full load. On the other side, issues related to knocking combustion and excessive exhaust gas temperatures obliged adopting countermeasures that highly affect the efficiency, such as fuel enrichment and delayed combustion. Powertrain electrification allows operating the ICE mostly at medium/high loads, shifting design needs and constraints towards targeting high efficiency under those operating conditions. Conversely, engine efficiency at low loads becomes a less important issue. In this track, the aim of this work is the investigation of the potential of the oversizing of a small Variable Valve ActuationSpark Ignition gasoline engine towards efficiency increase and tailpipe emission reduction.

A growing number of electric vehicles (EV) and hybrid electric vehicles (HEV) in the present market depicts the rapid growing demand for energy storage systems. The battery’s main peculiarities must be the power density and reliability over time. The temperature strongly affects battery performance for low and high intensity. In particular, the management of the heat generated by the battery itself is one of the main aspects to handle to preserve the performance over time. The objective of this paper is to compare the surface temperature of the lithium-ion polymer battery at different discharging rates by infrared thermography. Thermal imaging is performed to detect the battery surface temperature distribution, focusing on its variation over time and the local inhomogeneity. Temperature measurements are then used to estimate the contributions of the different heat transfer mechanisms for the dissipation of the heat generated by the battery.

The ever-increasing quest for sustainable mobility is pushing the automotive sector towards electric-based technologies, allowing the reduction of localized emission sources in highly populated urban areas. Among the many possible solutions, Proton Exchange Membrane Fuel Cells (PEMFC) have the potential to de-carbonise the automotive sector without the range anxiety of present and future batteries. The interaction between physical and chemical processes in PEMFC is crucial to their maximum attainable efficiency, albeit the complexity of such interplay still limits a complete understanding of the governing processes. In this paper a canonical PEMFC from literature is simulated using 3D-CFD, and results are compared against experiments. A Eulerian multi-phase/multi-physics non-isothermal framework is used to account for both fluid (gas channels, porous gas diffusion layers) and solid (bi-polar plates, membrane), as well as for electrochemical and sorption reactions.

The electrochemical performance of a lithium-ion battery is strongly affected by the temperature. During charge and discharge cycles, batteries are subjected to an increment of temperature that can accelerate aging and loss of efficiency if critical values are reached. Knowing the thermal parameters that affect the heat exchange between the battery surface and the surrounding environment (air, cooling fins, plates, etc…) is fundamental to their thermal management. In this work, thermal imaging is applied to a laminated lithium-polymers battery as a non-invasive temperature-indication method. Measurements are taken during the discharge phase and the following cooling down until the battery reaches the ambient temperature. The 2d images are used to analyze the homogeneity of the temperature distribution on the battery surface. Then, experimental results are coupled with mathematical correlations.

Growing concerns about the emissions of internal combustion engines have forced the adoption of aftertreatment devices to reduce the adverse impact of diesel engines on health and environment. Diesel particulate filters are considered as an effective means to reduce the particle emissions and comply with the regulations. Research activity in this field focuses on filter configuration, materials and aging, on understanding the variation of soot layer properties during time, on defining of the optimal strategy of DPF management for on-board control applications. A model was implemented in order to simulate the filtration and regeneration processes of a wall-flow particulate filter, taking into account the emission characteristic of the engine, whose architecture and operating conditions deeply affect the size distribution of soot particles.

The common realization of the necessity to reduce the use of mineral sources is promoting the use of alternative fuels. Big efforts are being made to replace petroleum derivatives in the internal combustion engines (ICEs). For this purpose it is mandatory to evaluate the behavior of non-conventional fuels in the ICEs. The optical diagnostics have proven to be a powerful tool to analyze the processes that take place inside the engine. In particular, 2d imaging in the infrared range can reveal new details about the effect of the fuel properties since this technique is still not very common. In this work, a comparison between commercial diesel fuel and two non-conventional fuels has been made in an optically accessible diesel engine. The non-conventional fuels are: the first generation biofuel Rapeseed Methyl Ester (RME) and an experimental blend of diesel and a fuel with high glycerol content (HG).

The paper reports an activity aiming at characterizing cycle-to-cycle variability (CCV) of the spark-ignition (SI) process in a high performance engine. The numerical simulation of spark-ignition and of early flame kernel evolution are major challenges, mainly due to the time scales of the spark discharge process and to the reduced spatial scales of flame kernel. Typical mesh resolutions are insufficient to resolve the process and a dedicated treatment has to be provided at a subgrid level if the ignition process is to be properly modelled. The focus of this work is on the recent ISSIM-LES (Imposed Stretch Spark-Ignition Model) ignition model, which is based on an extension of the flame surface density (FSD) transport equation for a dedicated flame kernel treatment at subgrid scales. The FSD equation is solved immediately after spark discharge.

An investigation has been carried out on the spray penetration and soot formation processes in a research diesel engine by means of a quasi-dimensional multizone combustion model. The model integrates a predictive non stationary 1D spray model developed by the Sandia National Laboratory, with a diagnostic multizone thermodynamic model, and is capable of predicting the spray formation, combustion and soot formation processes in the combustion chamber. The multizone model was used to analyze three operating conditions, i.e., a zero load point (BMEP = 0 bar at 1000 rpm), a medium load point (BMEP = 5 bar at 2000 rpm) and a medium-high load point (BMEP = 10 bar at 2000 rpm). These conditions were experimentally tested in an optical single cylinder engine with the combustion system configuration of a 2.0L Euro4 GM diesel engine for passenger car applications.

It is well known that 3D CFD simulations can give detailed information about fluid and flow properties in complex 3D domains while 1D CFD simulation can provide important information at a system level, i.e. about the performance of the entire engine. The drawbacks of the two simulation methods are that the former requires high computational cost while the latter is not able to capture complex local 3D features of the flow. Therefore, the two simulation methods are to be seen as complementary, indeed a coupling of the two approaches can benefit from the pros of the two methods while minimizing the cons. In particular, with a multi-scale modeling approach (1D-3D) it is possible to simulate large and complex domains by modeling the complex part with a 3D approach and the rest of the domain with a 1D approach.

CFD and FE tools are intensively adopted by engine manufacturers in order to prevent thermo-mechanical failures reducing time- and cost-to market. The capability to predict correctly the physical factors leading to damages is hence essential for their application in the industrial practice. This is even more important for last generation SI engines, where the more and more stringent need to lower fuel consumption and pollutant emissions is pushing designers to reduce engine displacement in favor of higher specific power, usually obtained by means of turbocharging. This brings to a new generation of SI engines characterized by higher and higher adiabatic efficiency and thermo-mechanical loads. A recent research highlighted the different behavior of the thermal boundary layer of such engines operated at high revving speeds and high loads if compared to the same engines operated at low loads and revving speeds or even engines with a lower specific power.

The increasing limitations in engine emissions and fuel consumption have led researchers to the need to accurately predict combustion and related events in gasoline engines. In particular, knock is one of the most limiting factors for modern SI units, severely hindering thermal efficiency improvements. Modern CFD simulations are becoming an affordable instrument to support experimental practice from the early design to the detailed calibration stage. To this aim, combustion and knock models in RANS formalism provide good time-to-solution trade-off allowing to simulate mean flame front propagation and flame brush geometry, as well as “ensemble average” knock tendency in end-gases. Still, the level of confidence in the use of CFD tools strongly relies on the possibility to validate models and methodologies against experimental measurements.

Engine knock is one of the most limiting factors for modern Spark-Ignition (SI) engines to achieve high efficiency targets. The stochastic nature of knock in SI units hinders the predictive capability of RANS knock models, which are based on ensemble averaged quantities. To this aim, a knock model grounded in statistics was recently developed in the RANS formalism. The model is able to infer a presumed log-normal distribution of knocking cycles from a single RANS simulation by means of transport equations for variances and turbulence-derived probability density functions (PDFs) for physical quantities. As a main advantage, the model is able to estimate the earliest knock severity experienced when moving the operating condition into the knocking regime.

It is widely recognized that spatial and temporal evolution of both macro- and micro- turbulent scales inside internal combustion engines affect air-fuel mixing, combustion and pollutants formation. Particularly, in spark ignition engines, tumbling macro-structure induces the generation of a proper turbulence level to sustain the development and propagation of the flame front. As known, 3D-CFD codes are able to describe the evolution of the in-cylinder flow and turbulence fields with good accuracy, although a high computational effort is required. For this reason, only a limited set of operating conditions is usually investigated. On the other hand, thanks to a lower computational burden, 1D codes can be employed to study engine performance in the whole operating domain, despite of a less detailed description of in-cylinder processes. The integration of 1D and 3D approaches appears hence a promising path to combine the advantages of both.

Engine knock is emerging as the main limiting factor for modern spark-ignition (SI) engines, facing increasing thermal loads and seeking demanding efficiency targets. To fulfill these requirements, the engine operating point must be moved as close as possible to the onset of abnormal combustion events. The turbulent regime characterizing in-cylinder flows and SI combustion leads to serious fluctuations between consecutive engine cycles. This forces the engine designer to further distance the target condition from its theoretical optimum, in order to prevent abnormal combustion to severely damage the engine components just because of few individual heavy-knocking cycles. A RANS-based model is presented in this study, which is able to predict not only the ensemble average knock occurrence but also a knock probability. This improves the knock tendency characterization, since the mean knock onset alone is a poorly meaningful indication in a stochastic event such as engine knock.