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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.

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.

The paper deals with the design and manufacturing of a McPherson suspension arm made from short glass fiber reinforced polyamide (PA66). The design of the arm and the design of the molds have been made jointly. According to Industry 4.0 paradigms, a full digitalization of both the product and process has been performed. Since the mechanical behavior of the suspension arm strongly depends on constraints which are difficult to be modelled, a simpler structure with well-defined mechanical constraints has been developed. By means of such simple structure, the model for the behavior of the material has been validated. Since the suspension arm is a hybrid structure, the associated simple structure is hybrid as well, featuring a metal sheet with over-molded polymer. The issues referring to material flow, material to material contact, weld lines, fatigue strength, high and low temperature behavior, creep, dynamic strength have been investigated on the simple structure.

A methodology for an efficient failure prediction of automotive steel wheels during fatigue experimental tests is proposed. The strategy joins the CDTire simulative package effectiveness to a specific wheel finite element model in order to deeply monitor the stress distribution among the component to predict damage. The numerical model acts as a Software-in-the-loop and it is calibrated with experimental data. The developed tool, called VirtualWheel, can be applied for the optimisation of design reducing prototyping and experimental test costs in the development phase. In the first section, the failure criterion is selected. In the second one, the conversion of hardware test-rig into virtual model is described in detail by focusing on critical aspects of finite element modelling. In conclusion, failure prediction is compared with experimental test results.

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.

Nowadays, powertrain development activity is performed on the base of fulfilling the stricter emission standards under real driving conditions (RDE). However, the pressure on automotive industry to reduce CO2 emissions in high efficient diesel applications results in lower exhaust gas temperatures. Therefore, it is highly needed to develop advanced vehicle thermal management methods to both fulfil the targets of emission standards and high thermal efficiency, without increasing dramatically the powertrain cost. The aim of this work is to experimentally demonstrate that by utilizing advanced engine and ATS control methods and revising the engine hardware and subsystems can lead to significant improvement on the fuel efficiency and emissions of the conventional diesel powertrain. The revised engine includes an improved combustion system, completely revised turbocharging and air handling system whilst being heavily reworked with respect to FMEP reduction.

This paper presents a numerical methodology to generate lookup tables that provide d- and q-axis stator current references for the control of electric motors. The main novelty with respect to other literature references is the introduction of the iron power losses in the equivalent-circuit electric motor model implemented in the optimization routine. The lookup tables generation algorithm discretizes the motor operating domain and, given proper constraints on maximum stator current and magnetic flux, solves a numerical optimization problem for each possible operating point to determine the combination of d- and q- axis stator currents that minimizes the imposed objective function while generating the desired torque. To demonstrate the versatility of the proposed approach, two different variants of this numerical interpretation of the motor control problem are proposed: Maximum Torque Per Ampere and Minimum Electromagnetic Power Loss.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional liquid fuels to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

A quasi-dimensional multizone combustion model, that was previously developed by the authors, has been refined and applied for the analysis of combustion and emission formation in a EURO V diesel engine equipped with a piezo indirect-acting injection system. The model is based on the integration of the predictive non-stationary variable-profile 1D spray model recently presented by Musculus and Kattke, with a diagnostic multizone thermodynamic model specifically developed by the authors. The multizone approach has been developed starting from the Dec conceptual scheme, and is based on the identification of several homogeneous zones in the combustion chamber, to which mass and energy conservation laws have been applied: an unburned gas zone, made up of air, EGR (Exhaust Gas Recirculation) and residual gas, several fuel/unburned gas mixture zones, premixed combustion burned gas zones and diffusive combustion burned gas zones.

Although the use of Exhaust Gas Recirculation (EGR) is nowadays mandatory for automotive diesel engines to achieve NOx emissions levels complying with more and more stringent legislation requirements, electronically controlled EGR systems still represent an expensive technology, often unsuitable for small diesel engines for off-road applications or for two/three wheelers. An interesting option for these categories of small diesel engines is the so-called “internal EGR”, which is obtained by modifying the intake or the exhaust valve lift profile, in order to increase the fraction of exhaust residuals at the end of the intake stroke. Different valve lift profiles were therefore evaluated for a 2 cylinders, 700 cc, Lombardini IDI diesel engine, equipping a light 4 wheelers vehicle.

The effects of using a B30 blend of ultra-low sulfur diesel and two different Fatty Acid Methyl Esters (FAME) obtained from both Rapeseed Methyl Ester (RME) and Jatropha Methyl Ester (JME) in a Euro 5 small displacement passenger car diesel engine on both full load performance and part load emissions have been evaluated in this paper. In particular the effects on engine torque were firstly analyzed, for both a standard ECU calibration (i.e., without any special tuning for the different fuel characteristics) and for a specifically adjusted ECU calibration obtained by properly increasing the injected fuel quantities to compensate for the lower LHV of the B30: with the latter, the same torque levels measured under diesel operation could be observed with the B30 blend too, with lower smoke levels, thus highlighting the potential for maintaining the same level of performance while achieving substantial emissions benefits.

In this work, a methodology for building and calibrating the kinetic scheme for the 1D CFD model of a zone-coated automotive Diesel Oxidation Catalyst (DOC) by means of a Genetic Algorithm (GA) approach is presented. The methodology consists of a preliminary experimental activity followed by a modelling, optimization and validation process. The tested aftertreatment component presents zone coating, with the front brick side covered with Zeolites in order to ensure hydrocarbons trapping at low temperature, and Platinum Group Metal (PGM), while the rear brick side presents an alumina washcoat with a different PGM loading. Reactor scale samples representative of each coating zone were tested on a Synthetic Gas Bench (SGB), to fully characterize the component’s behavior in terms of Light-off and hydrocarbons (HC) storage for a wide range of inlet feed compositions and temperatures, representative of engine-out conditions.

The detection and evaluation of damage in composite materials components is one of the main concerns for automotive engineers. It is acknowledged that defects appeared in the manufacturing stage or due to the impact and/or fatigue loads can develop along the vehicle riding. To avoid an unexpected failure of structural components, engineers ask for cheap methodologies assessing the health state of composite parts by means of continuous monitoring. Non Destructive Technique (NDT) for the damage assessment of composite structures are nowadays common and accurate, but an on-line monitoring requires properties as low cost, small size and low power that do not belong to common NDT. The presence of a damage in composite materials, either due to fatigue cycling or low-energy impact, leads to progressive degradation of elastic moduli and strengths.

The engine acoustic character has always represented the product DNA, owing to its strong correlation with in-cylinder pressure gradient, components design and perceived quality. Best practice for engine acoustic characterization requires the employment of a hemi-anechoic chamber, a significant number of sensors and special acoustic insulation for engine ancillaries and transmission. This process is highly demanding in terms of cost and time due to multiple engine working points to be tested and consequent data post-processing. Since Neural Networks potentially predicting capabilities are apparently un-exploited in this research field, the following paper provides a tool able to acoustically estimate engine performance, processing system inputs (e.g. Injected Fuel, Rail Pressure) thanks to the employment of Multi Layer Perceptron (MLP, a feed forward Network working in stationary points).

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 predictive capabilities of an innovative multizone combustion model DIPulse, developed by Gamma Technologies, were assessed in this work for a last generation common rail automotive diesel engine. A detailed validation process, based on an extensive experimental data set, was carried out concerning the predicted heat release rate, the in-cylinder pressure trace, as well as NOx and soot emissions for several operating points including both part load and full load points. After a preliminary calibration of the model, the combustion model parameters were then optimized through a Latin Hypercube Design of Experiment (DoE), with the aim of minimizing the RMS error between the predicted and experimental burn rate of several engine operating points, thus achieving a satisfactory agreement between simulation and experimental engine combustion and emissions parameters.

Fuel cells are considered one of the promising technologies as possible replacement of Internal Combustion Engine (ICE) for the transportation sector due to their high efficiency, ultra-low (or zero) emissions and for the higher drive range. The Membrane Electrode Assembly (MEA) is what mainly influences the Fuel Cell FC performance, durability, and cost. In PEMFC the proton conductivity of the membrane is a function of the humidification level of the FC membrane, hence the importance of keeping the membrane properly humidified to achieve the best possible fuel cell performance. To have the optimal water content inside the fuel cell’s membrane several strategies could be adopted, dealing with the use of external device (such as membrane humidifier) or to adopt an optimal set of parameters (gas flow rate and temperature for example) to use the water produced at fuel cell cathode as humidity source. The aim of this paper is to study the behavior of a FC vehicle humidification system.

In this work, several nanostructured ceria-based catalysts were prepared by the hydrothermal technique varying two synthesis parameters (namely, temperature and pH). Then, cerias with different shapes (i.e., cubes, rods, combination of them, other polyhedra) and structural properties were obtained. The prepared materials were tested for the CO oxidation and soot oxidation efficiency. The results have shown that, for the CO oxidation, activities depend on the surface properties of the catalysts. Conversely, for the soot oxidation, the most effective catalysts exhibit better soot-catalyst contact conditions.

The concept of Partially Premixed Combustion is known for reduced hazardous emissions and improved efficiency. Since a low-reactive fuel is required to extend the ignition delay at elevated loads, controllability and stability issues occur at the low-load end. In this investigation seven fuel blends are used, all having a Research Octane Number of around 70 and a distinct composition or boiling range. Four of them could be regarded as ‘viable refinery fuels’ since they are based on current refinery feedstocks. The latter three are based on primary reference fuels, being PRF70 and blends with ethanol and toluene respectively. Previous experiments revealed significant ignition differences, which asked for further understanding with an extended set of measurements. Experiments are conducted on a heavy duty diesel engine modified for single cylinder operation. In this investigation, emphasis is put on idling (600 rpm) and low load conditions.

A 2007 Cummins ISL 8.9L direct-injection common rail diesel engine rated at 272 kW (365 hp) was used to load the filter to 2.2 g/L and passively oxidize particulate matter (PM) within a 2007 OEM aftertreatment system consisting of a diesel oxidation catalyst (DOC) and catalyzed particulate filter (CPF). Having a better understanding of the passive NO2 oxidation kinetics of PM within the CPF allows for reducing the frequency of active regenerations (hydrocarbon injection) and the associated fuel penalties. Being able to model the passive oxidation of accumulated PM in the CPF is critical to creating accurate state estimation strategies. The MTU 1-D CPF model will be used to simulate data collected from this study to examine differences in the PM oxidation kinetics when soy methyl ester (SME) biodiesel is used as the source of fuel for the engine.