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In the framework of an increasing demand for a more sustainable mobility, where the fuel consumption reduction is a key driver for the development of innovative internal combustion engines, Turbulent Jet Ignition (TJI) represents one of the most promising solutions to improve the thermal efficiency. However, details concerning turbulent jet assisted combustion are still to be fully captured, and therefore the design and the calibration of efficient TJI systems require the support of reliable simulation tools that can provide additional information not accessible through experiments. To this aim, an experimental investigation combined with a 3D-CFD study was performed to analyze the TJI combustion characteristics in a single-cylinder spark-ignition (SI) engine. Firstly, the model was validated against experiments considering stoichiometric mixture at 3000 rpm, wide open throttle operating conditions.

Sustainable mobility has become a major issue for internal combustion engines and has led to increasing research efforts in the field of alternative fuels, such as bio-fuel, CNG and hydrogen addition, as well as into engine design and control optimization. To that end, a thorough control of the air-to-fuel ratio appears to be mandatory in SI engine in order to meet the even more stringent thresholds set by the current regulations. The accuracy of the air/fuel mixture highly depends on the injection system dynamic behavior and to its coupling to the engine fluid-dynamic. Thus, a sound investigation into the mixing process can only be achieved provided that a proper analysis of the injection rail and of the injectors is carried out. The present paper carries out a numerical investigation into the fluid dynamic behavior of a commercial CNG injection system by means of a 0D-1D code.

Reducing computational time has become a critical issue in recent years, particularly in the transportation field, where the complexity of scenarios demands lightweight controllers to run large simulations and gather results to study different behaviors. This study proposes two novel formulations of the Optimal Control Problem (OCP) for the Energy Management System of a Plug-in Hybrid Electric Vehicle (PHEV) and compares their performance with a benchmark found in the literature. Dynamic Programming was chosen as the optimization algorithm to solve the OCP in a Matlab environment, using the DynaProg toolbox. The objective is to address the optimality of the fuel economy solution and computational time. In order to improve the computational efficiency of the algorithm, an existing formulation from the literature was modified, which originally utilized three control inputs.

The potentialities in terms of engine performance and emissions reduction of pure biodiesel were examined on a Common Rail HSDI Diesel engine, trying to define a proper tuning of the injection strategies to bio-fuel characteristics. An experimental investigation was therefore carried out on a typical European passenger car Diesel engine, fuelled with a soybean oil derived biodiesel. A standard European diesel fuel was also used as a reference. In particular, the effects of an equal relative air/fuel ratio at full load condition were analysed; further, a sensitivity study on the outcome of the pilot injection timing and duration at part load on engine emissions was performed. Potentialities in recovering the performance gap between fossil fuel and biodiesel and in reducing NOx specific emissions, affecting only to a limited extent the biodiesel emission benefit in terms of CO, HC and FSN, were highlighted.

Hybrid electric vehicle (HEV) powertrains are characterized by a complex design environment as a result of both the large number of possible layouts and the need for dedicated energy management strategies. When selecting the most suitable hybrid powertrain architecture at an early design stage of HEVs, engineers usually focus solely on fuel economy (directly linked to tailpipe emissions) and vehicle drivability performance. However, high voltage batteries are a crucial component of HEVs as well in terms of performance and cost. This paper introduces a multitarget assessment framework for HEV powertrain architectures which considers both fuel economy and battery lifetime. A multi-objective formulation of dynamic programming is initially presented as an off-line optimal HEV energy management strategy capable of predicting both fuel economy performance and battery lifetime of HEV powertrain layout options.

This paper presents the results of part of the research activity carried out by the Politecnico di Torino and AVL List GmbH as part of the European Community InGAS Collaborative Project. The work was aimed at developing a combustion system for a mono-fuel turbocharged CNG engine, with specific focus on performance, fuel economy and emissions. A numerical and experimental analysis of the jet development and mixture formation in an optically accessible, single cylinder engine is presented in the paper. The experimental investigations were performed at the AVL laboratories by means of the planar laser-induced fluorescence technique, and revealed a cycle-to-cycle jet shape variability that depended, amongst others, on the injector characteristics and in-cylinder backpressure. Moreover, the mixing mechanism had to be optimized over a wide range of operating conditions, under both stratified lean and homogeneous stoichiometric modes.

The selection and tuning of the Fuel Injection System (FIS) are among the most critical tasks for the automotive diesel engine design engineers. In fact, the injection strongly affects the combustion phenomena through which controlling a wide range of related issues such as pollutant emissions, combustion noise and fuel efficiency becomes feasible. In the scope of the engine design optimization, the simulation is an efficient tool in order to both predict the key performance parameters of the FIS, and to reduce the amount of experiments needed to reach the final product configuration. In this work a complete characterization of a solenoid ballistic injector for a Light-Duty Common Rail system was therefore implemented in a commercially available one-dimensional computational software called GT-SUITE. The main phenomena governing the injector operation were simulated by means of three sub-models (electro-magnetic, hydraulic and mechanical).

An experimental investigation on a group of unleaded gasolines of different chemical composition has been carried out, in order to analyze their knock behaviour in a mass-produced engine at high revolution speed, to highlight possible inconsistencies with their standard Research and Motor octane numbers and to try to discover explanations for the abovementioned inconsistencies. The investigation has been focused on fuels containing oxygenated compounds, such as alcohols (methanol and ethanol) and ethers (MTBE), with the aim of pointing out the influence of the fuel composition on the octane rating, especially as far as the variation in the stoichiometric air/fuel ratio (due to oxygenated compounds blending) is concerned. In particular, the rating of all the fuels under the same relative air/fuel ratio has shown to be a mandatory condition in order to obtain a proper estimate of antiknock performances. The evaluations obtained are consistent with the standard Motor octane numbers.

This paper describes the optimization of the layout and of the control strategy of through-the-road (TTR) parallel hybrid electric vehicles equipped with two compression-ignition engines that feature different values of maximum output power. First, a tool has been developed to define the optimal layout of each TTR vehicle. This is based on the minimization of the powertrain and fuel cost over a 10-year time span, taking into account the fuel consumption. Several performance requirements are guaranteed during the optimization, namely maximum vehicle velocity, 0-100 km/h acceleration time, gradeability and the all-electric range. A benchmark optimizer that is based on the dynamic programming theory has been developed to identify the optimal working mode and the gear number, which are the control variables of the problem. A mathematical technique, based on the pre-processing of a configuration matrix, has been developed in order to speed up the calculation time.

In the face of growing concerns about environmental sustainability and urban congestion, the integration of eco-driving strategies has emerged as a pivotal solution in the field of the urban transportation sector. This study explores the potential benefits of a CAV functioning as a virtual eco-driving controller in an urban traffic scenario with a group of following human-driven vehicles. A computationally inexpensive and realistic powertrain model and energy management system of the Chrysler Pacifica PHEV are developed with the field experiment data and integrated into a forward-looking vehicle simulator to implement and validate an eco-driving speed planning and energy management strategy assuming longitudinal automation. The eco-driving algorithm determines the optimal vehicle speed profile and energy management strategy.

The aim of this work is to analyze particle number and size distribution from a small displacement Euro 5 common rail automotive diesel engine, equipped with a close coupled aftertreatment system, featuring a DOC and a DPF integrated in a single canning. In particular the effects of different combustion processes on PM characteristics were investigated, by comparing measurements made both under normal operating condition and under DPF regeneration mode. Exhaust gas was sampled at engine outlet, at DOC outlet and at DPF outlet, in order to fully characterize PM emissions through the whole exhaust line. After a two stage dilution system, sampled gas was analyzed by means of a TSI 3080 SMPS, in the range from 6 to 240 nm. Particle number and size distribution were evaluated at part load operating conditions, representative of urban driving.

Experimental work was carried out on a small displacement Euro 5 automotive diesel engine alternatively fuelled with ultra low sulphur diesel (ULSD) and with two blends (30% vol.) of ULSD and of two different fatty acid methyl esters (FAME) obtained from both rapeseed methyl ester (RME) and jatropha methyl ester (JME) in order to evaluate the effects of different fuel compositions on particle number (PN) emissions. Particulate matter (PM) emissions for each fuel were characterized in terms of number and mass size distributions by means of two stage dilutions system coupled with a scanning mobility particle sizer (SMPS). Measurements were performed at three different sampling points along the exhaust system: at engine-out, downstream of the diesel oxidation catalyst (DOC) and downstream of the diesel particulate filter (DPF). Thus, it was possible to evaluate both the effects of combustion and after-treatment efficiencies on each of the tested fuels.

An experimental investigation was performed on a turbocharged spark-ignition 4-cylinder production engine fuelled with natural gas and with two blends of natural gas and hydrogen (15% and 25% in volume of H₂). The engine was purposely designed to give optimal performance when running on CNG. The first part of the experimental campaign was carried out at MBT timing under stoichiometric conditions: load sweeps at constant engine speed and speed sweeps at constant load were performed. Afterwards, spark advance sweeps and relative air/fuel ratio sweeps were acquired at constant engine speed and load. The three fuels were compared in terms of performance (fuel conversion efficiency, brake specific fuel consumption, brake specific energy consumption and indicated mean effective pressure) and brake specific emissions (THC, NOx, CO).

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.

The trend towards powertrain electrification is expected to grow significantly in the next future also for super-cars. The aim of this paper is therefore to assess, through numerical simulation, the impact on both fuel economy and performance of different 48 Volt mild hybrid architectures for a high-performance sport car featuring a Turbocharged Direct Injection Spark Ignition (TDISI) engine. In particular the hybrid functionalities of both a P0 (Belt Alternator Starter - BAS) and a P2 (Flywheel Alternator Starter - FAS) architecture were investigated and optimized for this kind of application through a global optimization algorithm. The analysis pointed out CO2 emission reductions potential of about 6% and 25% on NEDC, 7% and 28% on WLTC for P0 and P2 respectively. From the performance perspective, a 10% reduction in the time-to-torque was highlighted for both architectures in a load step maneuver at 2000 RPM constant speed.

The DEXA Cluster consisted of three closely interlinked projects. In 2003 the DEXA Cluster concluded by demonstrating the successful development of critical technologies for Diesel exhaust particulate after-treatment, without adverse effects on NOx emissions and maintaining the fuel economy advantages of the Diesel engine well beyond the EURO IV (2000) emission standards horizon. In the present paper the most important results of the DEXA Cluster projects in the demonstration of advanced particulate control technologies, the development of a simulation toolkit for the design of diesel exhaust after-treatment systems and the development of novel particulate characterization methodologies, are presented. The motivation for the DEXA Cluster research was to increase the market competitiveness of diesel engine powertrains for passenger cars worldwide, and to accelerate the adoption of particulate control technology.

The effects of using neat FAME (Fatty Acid Methyl Ester) in a modern small displacement passenger car diesel engine have been evaluated in this paper. In particular the effects on engine performance at full load with standard (i.e., without any special tuning) ECU calibration were analyzed, highlighting some issues in the low end torque due to the lower exhaust gas temperatures at the turbine inlet, which caused a remarkable decrease of the available boost, with a substantial decrease of the engine torque output, far beyond the expected engine derating due to the lower LHV of the fuel. However, further tests carried out after ECU recalibration, showed that the same torque levels measured under diesel operation can be obtained with neat biodiesel too, thus highlighting the potential for maintaining the same level of performance.

In Motorsports the understanding of the real engine performance within a complete circuit lap is a crucial topic. On the basis of the telemetry data the engineers are able to monitor this performance and try to adapt the engine to the vehicle's and race track's characteristics and driver's needs. However, quite often the telemetry is the sole analysis instrument for the Engine-Vehicle-Driver (EVD) system and it has no prediction capability. The engine optimization for best lap-time or best fuel economy is therefore a topic which is not trivial to solve, without the aid of suitable, reliable and predictive engineering tools. A complete EVD model was therefore built in a GT-SUITE™ environment for a Motorsport racing car (STCC-VW-Scirocco) equipped with a Compressed Natural Gas (CNG) turbocharged S.I. engine and calibrated on the basis of telemetry and test bench data.

The next generation of gasoline turbo-charged engines will have to deal with the continuous tightening of emissions regulations. In fact, to better represent real-world emission figures, WLTP and RDE cycles focus on stricter criteria; spanning higher speeds and loads potentially covering the whole engine operating map. It is common practice at present to use overfueling to avoid catastrophic failure of turbine and aftertreatment systems at very high engine speeds and loads due to excessive temperatures. A past technology, which is presently enjoying a resurgence of interest, is water injection. In particular, for high-specific-power applications, this could be used as replacement strategy for overfueling, potentially enabling full operating range stoichiometric operation with no compromise in terms of maximum performance with respect to today.