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It is well known that backpressure is one of the important parameters to be minimised during the exhaust system development. Unfortunately, during the first phases of an engineering process of a new engine, engine prototypes are not available yet. Due to this the exhaust system backpressure is generally evaluated using simulation software, and/or measuring the backpressure by a flow rig test at room temperature. Goal of this paper is to compare exhaust backpressure results obtained respectively: i) at the room temperature flow rig; ii) at the engine dyno bench; iii) by simulation with one of the most common 1D fluidodynamics simulation tool (Gt-Power). A correlation of the three different techniques is presented.

The Injection Rate Shaping consists in a novel injection strategy to control air-fuel mixing quality via a suitable variation of injection timing that affects the injection rate profile. This strategy has already provided to be useful to increase combustion efficiency and reduce pollutant emissions in the modern compression ignition engines fed with fossil Diesel fuel. But nowadays, the ever more rigorous emission targets are enhancing a search for alternative fuels and/or new blends to replace conventional ones, leading, in turn, a change in the air-fuel mixture formation. In this work, a 1D model of spray injection aims to investigate the combined effects of both Injection Rate Shaping and alternative fuels on the air-fuel mixture formation in a compression ignition engine. In a first step, a ready-made model for conventional injection strategies has been set up for the Injection Rate Shaping.

The paper discusses the concept, specification and overall performance of a small microcogeneration unit of about 1,5 kW of electric power and about 4,5 kW of thermal power, suitable for domestic applications, designed at Istituto Motori CNR of Italy. This unit has been conceived specifically as a energy conversion system for houses, having in durability, electric and thermal efficiency the most important goals to be achieved. The paper starts by defining the state of art of small power microcogeneration units and then the ratio which leaded to the adoption of a single cylinder internal combustion engine derived from a motorcycle unit, in order to produce the above mentioned electric and thermal power. This is followed by an explanation of the main design characteristics of the system, with a discussion over the modified elements, made to enhance electric efficiency, emissions and durability and reduce, at the same time, cost coming from new design and manufacture.

During gasoline direct injection (GDI) in spark ignition engines, droplets may hit piston or liner surfaces and be rebounded or deposit in the liquid phase as wallfilm. This may determine slower secondary atomization and local enrichments of the mixture, hence be the reason of increased unburned hydrocarbons and particulate matter emissions at the exhaust. Complex phenomena indeed characterize the in-cylinder turbulent multi-phase system, where heat transfer involves the gaseous mixture (made of air and gasoline vapor), the liquid phase (droplets not yet evaporated and wallfilm) and the solid walls. A reliable 3D CFD modelling of the in-cylinder processes, therefore, necessarily requires also the correct simulation of the cooling effect due to the subtraction of the latent heat of vaporization of gasoline needed for secondary evaporation in the zone where droplets hit the wall. The related conductive heat transfer within the solid is to be taken into account.

Different hybrid powertrains for a European mid-size passenger car were evaluated in this paper through numerical simulation. Different degrees of hybridizations, from micro to mild hybrids, and different architectures and power sources management strategies were taken into account, in order to obtain a preliminary assessment of the potentialities of different hybrid systems for the European passenger car market. Both diesel and gasoline internal combustion engines were considered: a 1.6 dm₃ Common Rail turbocharged diesel, and a 1.4 dm₃ spark ignition turbocharged engine, equipped with an innovative Variable Valve Actuation system. Diesel hybrid powertrains, although being subject to NOx emissions constraints that could jeopardize their benefits, offered substantial advantages in comparison with gasoline hybrid powertrains. Potentialities for fuel consumption reductions up to 25% over the NEDC were highlighted, approaching the 2020 EU 95 g/km CO₂ target.

This paper reports 1D and 3D CFD analyses aiming to improve the gas-dynamic noise emission of a downsized turbocharged VVA engine through the re-design of the intake air-box device, consisting in the introduction of external or internal resonators. Nowadays, modern spark-ignition (SI) engines show more and more complex architectures that, while improving the brake specific fuel consumption (BSFC), may be responsible for the increased noise radiation at the engine intake mouth. In particular VVA systems allow for the actuation of advanced valve strategies that provide a reduction in the BSFC at part load operations thanks to the intake line de-throttling. In these conditions, due to a less effective attenuation of the pressure waves that travel along the intake system, VVA engines produce higher gas-dynamic noise levels.

Modern vehicles have several active systems on board such as the Electronic Stability Control. Many of these systems require knowledge of vehicle states such as sideslip angle and yaw rate for feedback control. Sideslip angle cannot be measured with the standard sensors present in a vehicle, but it can be measured by very expensive and large optical sensors. As a result, state observers have been used to estimate sideslip angle of vehicles. The current state of the art does not present an algorithm which can robustly estimate the sideslip angle for vehicles with all-wheel drive. A deep learning network based sideslip angle observer is presented in this article for robust estimation of vehicle sideslip angle. The observer takes in the inputs from all the on board sensors present in a vehicle and it gives out an estimate of the sideslip angle. The observer is tested extensively using data which are obtained from proving grounds in high tire-road friction coefficient conditions.

Feed-forward low-throughput models have been developed to predict MFB50 and to control SOI in order to achieve a specific MFB50 target for diesel engines. The models have been assessed on a GMPT-E Euro 5 diesel engine, installed at the dynamic test bench at ICEAL-PT (Internal Combustion Engine Advanced Laboratory at the Politecnico di Torino) and applied to both steady state and transient engine operating conditions. MFB50 indicates the crank angle at which 50% of the fuel mass fraction has burned, and is currently used extensively in control algorithms to optimize combustion phasing in diesel engines in real-time. MFB50 is generally used in closed-loop combustion control applications, where it is calculated by the engine control unit, cycle-by-cycle and cylinder by-cylinder, on the basis of the measured in-cylinder pressure trace, and is adjusted in order to reduce the fuel consumption, combustion noise and engine-out emissions.

Control of knock phenomenon is becoming more and more important in modern SI engine, due to the tendency to develop high boosted turbocharged engines (downsizing). To this aim, improved modeling and experimental techniques are required to precisely define the maximum allowable spark advance. On the experimental side, the knock limit is identified based on some indices derived by the analysis of the in-cylinder pressure traces or of the cylinder block vibrations. The threshold levels of the knock indices are usually defined following an heuristic approach. On the modeling side, in the 1D codes, the knock is usually described by simple correlation of the auto-ignition time of the unburned gas zone within the cylinders. In addition, the latter methodology commonly refers to ensemble-averaged pressure cycles and, for this reason, does not take into account the cycle-by-cycle variations.

The paper presents a diaphragm spring clutch linear thermal model. The main model aim was to estimate the temperature on the clutch disc slipping surfaces. That objective was pursued through a linear model to overcome the memory and computing time problems required by models with a more complex structure. The model parameters were experimentally identified. The model was validated employing a test bench, considering shift transient different as far as energy dissipated, clutch disc wear, frequency of shifting, gearbox temperature. The model structure, the methodology adopted to identify the model parameters, the experimental results obtained are presented and discussed.

This paper presents the modeling of the transient phase of catalyst heating on a high-performance turbocharged spark ignition engine with the aim to accurately predict the exhaust thermal energy available at the catalyst inlet and to provide a “virtual test rig” to assess different design and calibration options. The entire transient phase, starting from the engine cranking until the catalyst warm-up is completed, was taken into account in the simulation, and the model was validated using a wide data-set of experimental tests. The first step of the modeling activity was the combustion analysis during the transient phase: the burn rate was evaluated on the basis of experimental in-cylinder pressure data, considering both cycle-to-cycle and cylinder-to-cylinder variations.

In this paper a novel approach to mimic through numerical simulation Cycle-to-Cycle Variations (CCV) of the combustion process of Spark Ignition (SI) engines is described. The proposed methodology allows to reproduce the variability in combustion which is responsible for knock occurrence and thus to replicate the stochastic behavior of this abnormal combustion phenomenon. On the basis of the analysis of a comprehensive database of experimental data collected on a typical European downsized and turbocharged SI engine, the proposed approach was demonstrated to be capable to replicate in the simulation process the same percentage of knocking cycles experimentally measured in light-knock conditions, after a proper calibration of the Kinetics-Fit (KF), a new phenomenological knock model which was recently developed by Gamma Technologies.

Transported probability density function (PDF) methods are currently being pursued as a viable approach to model the effects of turbulent mixing and mixture stratification, especially for new alternative combustion modes as for example Homogeneous Charge Compression ignition (HCCI) which is one of the advanced low temperature combustion (LTC) concepts. Recently, they have been applied to simple engine configurations to demonstrate the importance of accurate accounting for turbulence/chemistry interactions. PDF methods can explicitly account for the turbulent fluctuations in species composition and temperature relative to mean value. The choice of the mixing model is an important aspect of PDF approach. Different mixing models can be found in the literature, the most popular is the IEM model (Interaction by Exchange with the Mean). This model is very similar to the LMSE model (Linear Mean Square Estimation).

Usually, both an experimental modal analysis or a numerical modal analysis performed on reduced model present the problem of master nodes selection. A methodology based on the experience is normally used or computationally heavy criterion can be applied. In that paper, the Modal-Geometrical Selection Criterion (MoGeSeC) is applied to a crankshaft, both for an EMA (experimental modal analysis) and for a reduction procedure. Then the results are compared with other literature criteria. As far as the EMA is concerned, the nodes suggested by MoGeSeC and other criteria are used for identification of the component. The connection conditions between components are origin of uncertainty but in that case the comparison is done for each methodology in the same conditions. In that way MoGeSeC proves to be a very quick and accurate method because the nodes it selects depicts very well the dynamic behavior of the components.

In this paper, the results of an extensive experimental analysis regarding a twin-cylinder spark-ignition turbocharged engine are employed to build up an advanced 1D model, which includes the effects of cycle-by-cycle variations (CCVs) on the combustion process. Objective of the activity is to numerically estimate the CCV impact primarily on fuel consumption and knock behavior. To this aim, the engine is experimentally characterized in terms of average performance parameters and CCVs at high and low load operation. In particular, both a spark advance and an air-to-fuel ratio (α) sweep are actuated. Acquired pressure signals are processed to estimate the rate of heat release and the main combustion events. Moreover, the Coefficient of Variation of IMEP (CoVIMEP) and of in-cylinder peak pressure (CoVpmax) are evaluated to quantify the cyclic dispersion and identify its dependency on peak pressure position.

A new test bench has been set up and equipped in order to analyze the air mean motion and turbulence quantities in the combustion system of an automotive diesel engine with one helicoidal intake duct and a conical type in-piston bowl. A sophisticated HWA technique employing single- and dual-sensor probes was applied to the in-cylinder flow investigation under motored conditions. The anemometric probe was also operated as a thermometric sensor. An analytical-numerical procedure, based on the heat balance equations for both anemometric and thermometric wires, was refined and applied to compute the gas velocity from the anemometer output signal. The gas property influence, the thermometric sensor lag and the prong temperature effects were taken into account with this procedure. The in-cylinder velocity data were reduced using both a cycle-resolved approach and the conventional ensemble-averaging procedure, in order to separate the mean flow from the fluctuating motion.

In this paper, a downsized twin-cylinder turbocharged spark-ignition engine is experimentally investigated at test-bench in order to verify the potential to estimate the peak pressure value and the related crank angle position, based on vibrational data acquired by an accelerometer sensor. Purpose of the activity is to provide the ECU of additional information to establish a closed-loop control of the spark timing, on a cycle-by-cycle basis. In this way, an optimal combustion phasing can be more properly accomplished in each engine operating condition. Engine behavior is firstly characterized in terms of average thermodynamic and performance parameters and cycle-by-cycle variations (CCVs) at high-load operation. In particular, both a spark advance and an A/F ratio sweep are actuated. In-cylinder pressure data are acquired by pressure sensors flush-mounted within the combustion chamber of both cylinders.

Numerical simulation can be effectively used to reduce the experimental tests which are nowadays required for the analysis and calibration of engine control systems. In particular in this paper the use of a one-dimensional engine model to analyze the response of an UEGO sensor in the exhaust manifold of a 4 cylinder s.i. engine (with multipoint fuel injection) is described: numerical simulation has been used to simulate a misfunction of the fuelling system, which caused one of the four cylinders to be fuelled with an air/fuel ratio that was 10% richer than the others. The simulated UEGO response was then compared with experimental measurements, and after this validation process, the sensor model can be used to study a proper fuel injection control strategy thus reducing the required experimental tests, as outlined in a test case presented at the end of the paper.

Nowadays numerical simulations play a major role in the development of future sustainable powertrain thanks to their capability of investigating a wide spectrum of innovative technologies with times and costs significantly lower than a campaign of experimental tests. In such a framework, this paper aims to assess the predictive capabilities of an 1D-CFD engine model developed to support the design and the calibration of the innovative highly efficient spark ignition engine of the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) EU H2020 project. As a matter of fact, the availability of a reliable simulation platform is crucial to achieve the project target of 47% peak indicating efficiency, by synergistically exploiting the combination of innovative in-cylinder charge motion, Miller cycle with high compression ratio, lean mixture with cooled Exhaust Gas Recirculation (EGR) and electrified turbocharger.

New internal combustion engines (ICE) are characterized by increasing maximum efficiency, thanks to the adoption of strategies like Atkinson cycle, downsizing, cylinder deactivation, waste heat recovery and so on. However, the best performance is confined to a limited portion of the engine map. Moreover, electric driving in urban areas is an increasingly pressing request, but battery electric vehicles use cannot be easily spread, due to limited vehicle autonomy and recharging issues. Therefore, hybrid propulsion systems are under development, in order to reduce vehicle fuel consumption, by decoupling the ICE running from road load, as well as to permit energy recovery and electric driving. This paper analyses a new-patented solution for power split hybrid propulsion system with gearbox. The system comprises an auxiliary power unit, adapted to store and/or release energy, and a planetary gear set, which is interposed between the ICE and the gearbox.