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Biofuel usage is increasingly expanding thanks to its significant contribution to a well-to-wheel (WTW) reduction of greenhouse gas (GHG) emissions. In addition, stringent emission standards make mandatory the use of Diesel Particulate Filter (DPF) for the particulate emissions control. The different physical properties and chemical composition of biofuels impact the overall engine behaviour. In particular, the PM emissions and the related DPF regeneration strategy are clearly affected by biofuel usage due mainly to its higher oxygen content and lower low heating value (LHV). More specifically, the PM emissions and the related DPF regeneration strategy are clearly affected by biofuel usage due mainly to its higher oxygen content and lower low heating value, respectively. The particle emissions, in fact, are lower mainly because of the higher oxygen content. Subsequently less frequent regenerations are required.

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.

The present paper describes some results of a cooperative research project between GM Powertrain Europe and Istituto Motori of CNR aimed at studying the impact of FAME and GTL fuel blends on the performance, emissions and fuel consumption of the latest-generation automotive diesel engines. The investigation was carried out on the newly released GM 2.0L 4-cylinder “torque-controlled” Euro 5 diesel engine for PC application and followed previous tests on its Euro 4 version, in order to track the interaction between the alternative fuels and the diesel engine, as the technology evolves. Various blends of first generation biodiesels (RME, SME) and GTL with a reference diesel fuel were tested, notably B20, B50 and B100. The tests were done in a wide range of engine operation points for the complete characterization of the biodiesels performance in the NEDC cycle, as well as in full load conditions.

The present paper describes some results of a research project aimed at studying the impact of alternative fuels blends on the emissions and fuel consumption of an Euro 5 automotive diesel engine. Two alternative fuels were chosen for the experiments: RME and GTL. The tests were done in the three most important operating conditions for the engine emission calibration. Moreover, the NOx-PM trade-off by means of EGR sweep was performed in the same operating conditions, in order to evaluate the engine EGR tolerability when burning low sooting fuels as the RME. The investigations put in evidence that the impact of the alternative fuels on modern diesel engines remains significant. This also depends on the interaction between the alternative fuel characteristics and the engine-management strategies, as described in detail in the paper.

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™.

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.

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.

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.

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.

New SI engine generations are characterized by a simultaneous reduction of the engine displacement and an increase of the brake power; such targets are achieved through the adoption of several techniques such as turbocharging, direct fuel injection, variable valve timing and variable port lengths. This design approach, called “downsizing”, leads to a marked increase in the thermal loads acting on the engine components, in particular on those facing the combustion chamber. Hence, an accurate evaluation of the thermal field is of primary importance in order to avoid mechanical failures. Moreover, the correct evaluation of the temperature distribution improves the prediction of pointwise abnormal combustion onset.

The occurrence of knock is the most limiting hindrance for modern Spark-Ignition (SI) engines. In order to understand its origin and move the operating condition as close as possible to onset of this potentially harmful phenomenon, a joint experimental and numerical investigation is the most recommended approach. A preliminary experimental activity was carried out at IM-CNR on a 0.4 liter GDI unit, equipped with a flat transparent piston. The analysis of flame front morphology allowed to correlate high levels of flame front wrinkling and negative curvature to knock prone operating conditions, such as increased spark timings or high levels of exhaust back-pressure. In this study a detailed CFD analysis is carried out for the same engine and operating point as the experiments. The aim of this activity is to deeper investigate the reasons behind the main outcomes of the experimental campaign.

With the aim of identifying technical solutions to lower the particulate matter emissions, the engine research community made a consistent effort to investigate the root causes leading to soot formation. Nowadays, the computational power increase allows the use of advanced soot emissions models in 3D-CFD turbulent reacting flows simulations. However, the adaptation of soot models originally developed for Diesel applications to gasoline direct injection engines is still an ongoing process. A limited number of studies in literature attempted to model soot produced by gasoline direct injection engines, obtaining a qualitative agreement with the experiments. To the authors’ best knowledge, none of the previous studies provided a methodology to quantitatively match particulate matter, particulate number and particle size distribution function measured at the exhaust without a case-by-case soot model tuning.

The diesel particulate filters (DPF) are considered the most robust technologies for particle emission reduction both in terms of mass and number. On the other hand, the increase of the backpressure in the exhaust system due to the accumulation of the particles in the filter walls leads to an increase of the engine fuel consumption and engine power reduction. To limit the filter loading, and the backpressure, a periodical regeneration is needed. Because of the growing interest about particle emission both in terms of mass, number and size, it appears important to monitor the evolution of the particle mass and number concentrations and size distribution during the regeneration of the DPFs. For this matter, in the presented work the regeneration of a catalyzed filter was fully analyzed. Particular attention was dedicated to the dynamic evolution both of the thermodynamic parameters and particle emissions.

The detailed study of part-load conditions is essential to characterize engine-out emissions in key operating conditions. The relevance of part-load operations is further emphasized by the recent regulations such as the new WLTP standard. Combustion development at part-load operations depends on a complex interplay between moderate turbulence levels (low engine speed and tumble ratio), low in-cylinder pressure and temperature, and stoichiometric-to-lean mixture quality (to maximize fuel efficiency). From a modelling standpoint, the reduced turbulence intensity compared to full-load operations complicates the interaction between different sub-models (e.g., reconsideration of the flamelet hypothesis adopted by common combustion models). In this article, the authors focus on chemistry-based simulations for laminar flame speed of gasoline surrogates at conditions typical of part-load operations. The analysis is an extension of a previous study focused on full-load operations.