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Predicting the fuel economy capability of hybrid electric vehicle (HEV) powertrains by solving the related optimal control problem has been available for a few decades. Dynamic programming (DP) is one of the most popular techniques implemented to this end. Current research aims at integrating further powertrain modeling criteria that improve the fidelity level of the optimal HEV powertrain control behavior predicted by DP, thus corroborating the reliability of the fuel economy assessment. Dedicated methodologies need further development to avoid the curse of dimensionality which is typically associated to DP when increasing the number of control and state variables considered. This paper aims at considerably reducing the overall computational effort required by DP for HEVs by removing the state term associated to the battery state-of-charge (SOC).

One of the first steps in powertrain design is to assess its best performance and consumption in a virtual phase. Regarding hybrid electric vehicles (HEVs), it is important to define the best mode profile through a cycle in order to maximize fuel economy. To assist in that task, several off-line optimization algorithms were developed, with Dynamic Programming (DP) being the most common one. The DP algorithm generates the control actions that will result in the most optimal fuel economy of the powertrain for a known driving cycle. Although this method results in the global optimum behavior, the DP tool comes with a high computational cost. The charge-sustaining requirement and the necessity of capturing extremely small variations in the battery state of charge (SOC) makes this state vector an enormous variable. As things move fast in the industry, a rapid tool with the same performance is required.

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).

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.

Component sizing generally represents a demanding and time-consuming task in the development process of electrified powertrains. A couple of processes are available in literature for sizing the hybrid electric vehicle (HEV) components. These processes employ either time-consuming global optimization techniques like dynamic programming (DP) or near-optimal techniques that require iterative and uncertain tuning of evaluation parameters like the Pontryagin’s minimum principle (PMP). Recently, a novel near-optimal technique has been devised for rapidly predicting the optimal fuel economy benchmark of design options for electrified powertrains. This method, named slope-weighted energy-based rapid control analysis (SERCA), has been demonstrated producing results comparable to DP, while limiting the associated computational time by near two orders of magnitude.

Active tire pressure control (ATPC) is an automatic central tire inflation system (CTIS), designed, prototyped, and tested at the Politecnico di Torino, which is aimed at improving the fuel consumption, safety, and drivability of passenger vehicles. The pneumatic layout of the system and the designed solution for on board integration are presented. The critical design choices are explained in detail and supported by experimental evidence. In particular, the results of experimental tests, including the characterizations of various pneumatic components in working conditions, have been exploited to obtain a design, which allows reliable performance of the system in a lightweight solution. The complete system has been tested to verify its dynamics, in terms of actuation time needed to obtain a desired pressure variation, starting from the current tire pressure, and to validate the design.

Meticulous design of the energy management control algorithm is required to exploit all fuel-saving potentials of a hybrid electric vehicle. Equivalent consumption minimization strategy is a well-known representative of on-line strategies that can give near-optimal solutions without knowing the future driving tasks. In this context, this paper aims to propose an adaptive real-time equivalent consumption minimization strategy for a multi-mode hybrid electric powertrain. With the help of road recognition and vehicle speed prediction techniques, future driving conditions can be predicted over a certain horizon. Based on the predicted power demand, the optimal equivalence factor is calculated in advance by using bisection method and implemented for the upcoming driving period. In such a way, the equivalence factor is updated periodically to achieve charge sustaining operation and optimality.

The present paper describes the results of a research project aimed at studying the impact of nozzle flow number on a Euro5 automotive diesel engine, featuring Closed-Loop Combustion Control. In order to optimize the trade-offs between fuel economy, combustion noise, emissions and power density for the next generation diesel engines, general trend among OEMs is lowering nozzle flow number and, as a consequence, nozzle hole size. In this context, three nozzle configurations have been characterized on a 2.0L Euro5 Common Rail Diesel engine, coupling experimental activities performed on multi-cylinder and optical single cylinder engines to analysis on spray bomb and injector test rigs. More in detail, this paper deeply describes the investigation carried out on the multi-cylinder engine, specifically devoted to the combustion evolution and engine performance analysis, varying the injector flow number.

The paper presents the main results of a study on the simulation of energy efficient management of on-board electric and thermal systems for a medium-size passenger vehicle featuring a parallel-hybrid diesel powertrain with a high-voltage belt alternator starter. A set of advanced technologies has been considered on the basis of very aggressive fuel economy targets: base-engine downsizing and friction reduction, combustion optimization, active thermal management, enhanced aftertreatment and downspeeding. Mild-hybridization has also been added with the goal of supporting the downsized/downspeeded engine performance, performing energy recuperation during coasting phases and enabling smooth stop/start and acceleration. The simulation has implemented a dynamic response to the required velocity and manual gear shift profiles in order to reproduce real-driver behavior and has actuated an automatic power split between the Internal Combustion Engine (ICE) and the Electric Machine (EM).

The sustainable use of energy and the reduction of pollutant emissions are main concerns of the automotive industry. In this context, Hybrid Electric Vehicles (HEVs) offer significant improvements in the efficiency of the propulsion system and allow advanced strategies to reduce pollutant and noise emissions. The paper presents the results of a simulation study that addresses the minimization of fuel consumption, NOx emissions and combustion noise of a medium-size passenger car. Such a vehicle has a parallel-hybrid diesel powertrain with a high-voltage belt alternator starter. The simulation reproduces real-driver behavior through a dynamic modeling approach and actuates an automatic power split between the Internal Combustion Engine (ICE) and the Electric Machine (EM). Typical characteristics of parallel hybrid technologies, such as Stop&Start, regenerative braking and electric power assistance, are implemented via an operating strategy that is based on the reduction of total losses.

The growing concerns on the emission of particles smaller than 23 nm, which are harmful to human health, lead to the necessity of introducing a regulation for these particles not yet included in the current emission standards. Considering that measurements of concentration of sub-23 nm particles are particularly sensitive to the sampling conditions, it is important to identify an effective assessment procedure. Aim of this paper is the characterization of the effect of the sampling conditions on sub-23 nm particles, emitted by PFI (port fuel injection) and DI (direct injection) spark ignition engines fueled with gasoline, ethanol and a mixture of ethanol and gasoline (E30). The experimental activity was carried out on a 250 cm3 displacement four stroke GDI and PFI single cylinder engines. The tests were conducted at 2000 rpm and 4000 rpm full load, representative of the homologation urban driving cycle.

Nowadays, alcohol fuels are of increasing interest as alternative transportation biofuels even in compression ignition engines because they are oxygenated and producible in a sustainable way. In this paper, the experimental research activity was conducted on a single cylinder research engine provided with a modern architecture and properly modified in a dual-fuel (DF) configuration. Looking at ethanol the as one of the future environmental friendly biofuels experimental campaign was aimed to evaluate in detail the effect of the use of the ethanol as port injected fuel in diesel engine on the size, morphology, reactivity and chemical features of the exhaust emitted soot particles. The engine tests were chosen properly in order to represent actual working conditions of an automotive light-duty diesel engine. A proper engine Dual-Fuel calibration was set-up respecting prefixed limits on in-cylinder peak firing pressure, cylinder pressure rise, fuel efficiency and gaseous emissions.

The aim of this work is the assessment of the predictive capabilities of fast running models, obtained through an appropriate reduction and simplification process from detailed 1D fluid-dynamic models, for a turbocharged s.i. engine under highly transient operating conditions. Simulations results have been compared with experimental data for different types of models, ranging from fully detailed 1D fluid-dynamic models to map-based models, quantifying the degradation of the model accuracy and the reduction in the computational time for different kinds of driving cycles, from moderately transient such as the NEDC to highly dynamic such as the US06.

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.

The demanding CO2 emission targets are fostering the development of downsized, turbocharged and electrified engines. In this context, the need for high boost level at low engine speed requires the exploration of dual stage boosting systems. At the same time, the increased electrification level of the vehicles enables the usage of electrified boosting systems aiming to exploit the opportunities of high levels of electric power and energy available on-board. The aim of this work is therefore to evaluate, through numerical simulation, the impact of a 48 V electric supercharger (eSC) on vehicle performance and fuel consumption over different transients. The virtual test rig employed for the analysis integrates a 1D CFD fast running engine model representative of a 1.5 L state-of-the-art gasoline engine featuring an eSC in series with the main turbocharger, a dual voltage electric network (12 V + 48 V), a six-speed manual transmission and a vehicle representative of a B-SUV segment car.

The introduction of new light-duty vehicle emission limits to comply under real driving conditions (RDE) is pushing the diesel engine manufacturers to identify and improve the technologies and strategies for further emission reduction. The latest technology advancements on the after-treatment systems have permitted to achieve very low emission conformity factors over the RDE, and therefore, the biggest challenge of the diesel engine development is maintaining its competitiveness in the trade-off “CO2-system cost” in comparison to other propulsion systems. In this regard, diesel engines can continue to play an important role, in the short-medium term, to enable cost-effective compliance of CO2-fleet emission targets, either in conventional or hybrid propulsion systems configuration. This is especially true for large-size cars, SUVs and light commercial vehicles.

The Vehicle Energy Consumption calculation Tool (VECTO) is used in Europe for calculating standardised energy consumption and CO2 emissions from Heavy-Duty Trucks (HDTs) for certification purposes. The tool requires detailed vehicle technical specifications and a series of component efficiency maps, which are difficult to retrieve for those that are outside of the manufacturing industry. In the context of quantifying HDT CO2 emissions, the Joint Research Centre (JRC) of the European Commission received VECTO simulation data of the 2016 vehicle fleet from the vehicle manufacturers. In previous work, this simulation data has been normalised to compensate for differences and issues in the quality of the input data used to run the simulations. This work, which is a continuation of the previous exercise, focuses on the deeper meaning of the data received to understand the factors contributing to energy and fuel consumption.

This paper deals with the evaluation of the effect of fuel properties on soot formation in a GDI (gasoline direct injection) engine. Experimental investigation was carried out in an optical 4-stroke small single cylinder engine for two-wheel vehicles. The engine displacement was 250 cc. It was equipped with an elongated piston with a wide sapphire window in the head and a quartz cylinder liner. The engine was fuelled with pure gasoline and ethanol, and ethanol/gasoline blends at 20% v/v, 50% v/v and 85% v/v. Optical techniques based on 2D-digital imaging were used to follow the combustion process and soot formation. Spectroscopic measurements were carried out in order to assess the soot evolution. Radical species such as OH and CH, related to fuel quality and to soot formation/oxidation process, were detected. Measurements were carried out at various engine speeds and loads in order to allow optical measurements and to test the engine in real conditions.

The objective of this paper is the evaluation of the effect of the fuel properties and the comparison of a PFI and GDI injection system on the performances and on particle emission in a Spark Ignition engine. Experimental investigation was carried out in a small single cylinder engine for two wheel vehicles. The engine displacement was 250 cc. It was equipped with a prototype GDI head and also with an injector in the intake manifold. This makes it possible to run the engine both in GDI and PFI configurations. The engine was fuelled with neat gasoline and ethanol, and ethanol/gasoline blends at 10% v/v, 50% v/v and 85% v/v. The engine was equipped of a quartz pressure transducer that was flush-mounted in the region between intake and exhaust valves. Tests were carried out at 3000 rpm and 4000 rpm full load and two different lambda conditions. These engine points were chosen as representative of urban driving conditions.

A detailed understanding of Gasoline Direct Injection (GDI) techniques applied to spark-ignition (SI) engines is necessary as they allow for many technical advantages such as increased power output, higher fuel efficiency and better cold start performances. Within this context, the extensive validation of multi-dimensional models against experimental data is a fundamental task in order to achieve an accurate reproduction of the physical phenomena characterizing the injected fuel spray. In this work, simulations of different Engine Combustion Network (ECN) Spray G conditions were performed with the Lib-ICE code, which is based on the open source OpenFOAM technology, by using a RANS Eulerian-Lagrangian approach to model the ambient gas-fuel spray interaction.