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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.

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.

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.

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.

Advanced technologies such as direct injection DI, turbocharging and variable valve timing, have lead to a significant evolution of the gasoline engine with positive effects on driving pleasure, fuel consumption and emissions. Today's developments are primarily focused on the implementation of improved full load characteristics for driving performance and fuel consumption reduction with stoichiometric operation, following the downsizing approach in combination with turbocharging and high specific power. The requirements of a relatively small cylinder displacement with high specific power and a wide flexibility of DI injection specifications lead to competing development targets and additionally to a high number of degrees of freedom during optimization. In order to successfully approach an optimum solution, FEV has evolved an advanced development methodology, which is based on the combination of simulation, optical diagnostics and engine thermodynamics testing.

This paper introduces a new approach based on a statistical investigation and finite element analysis (FEA) methodology to predict the crankshaft torsional stiffness and stress concentration factors (SCF) due to torsion and bending which can be used as inputs for simplified crankshaft multibody models and durability calculations. In this way the reduction of the development time and effort of passenger car crankshafts in the pre-layout phase is intended with a least possible accuracy sacrifice. With the designated methodology a better approximation to reality is reached for crank torsional stiffness and SCF due to torsion and bending compared with the empirical approaches, since the prediction does not depend on the component tests with limited numbers of specimen, as in empirical equations, but on various FE calculations.

Future HD Diesel engine technology is facing a combination of both extremely low exhaust emission standards (US 2002/2004, EURO IV and later US 2007, EURO V) and new engine test procedures such as the European Transient Cycle (ETC) in Europe and the Not-to-Exceed Area (NTE) in the US). Customers furthermore require increased engine performance, improved efficiency, and long-term durability. In order to achieve all targets simultaneously, future HD Diesel engines must have improved fuel injection and combustion systems and utilize suitable technologies such as exhaust gas recirculation (EGR), variable geometry turbine turbocharger systems (VGT) and exhaust gas after-treatment systems. Future systems require precision controlled EGR in combination with a VGT-turbocharger during transient operation. This will require new strategies and calibration for the Electronic Engine Control Unit (ECU).

The fulfillment of the aggravated demands on future small-size High-Speed Direct Injection (HSDI) Diesel engines requires next to the optimization of the injection system and the combustion chamber also the generation of an optimal in-cylinder swirl charge motion. To evaluate different port concepts for modern HSDI Diesel engines, usually quantities as the in-cylinder swirl ratio and the flow coefficient are determined, which are measured on a steady-state flow test bench. It has been shown that different valve lift strategies nominally lead to similar swirl levels. However, significant differences in combustion behavior and engine-out emissions give rise to the assumption that local differences in the in-cylinder flow structure caused by different valve lift strategies have noticeable impact. In this study an additional criterion, the homogeneity of the swirl flow, is introduced and a new approach for a quantitative assessment of swirl flow pattern is presented.

The new Thermo-Elasto-Hydro-Dynamic (TEHD) code developed by FEV, is designed to improve the predictability of journal bearing designs and thereby increase the reliability of safety factors in the development of highly loaded internal combustion engines. Advanced analysis tools are evaluated by their performance as well as by their ease of use. High performance means on the one hand: taking into account all the important characteristics, like bearing elasticity or cavitation effects, to mention only some major parameters for modern journal bearing analysis. On the other hand: an economic run-time behavior must be a key feature concerning usability of the TEHD-demands for daily development praxis. Ease of use means also, that the TEHD model can easily be used as a plug-in routine of an already existing software package that is well known to the development departments.

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.

The new elastohydrodynamic (EHD) code developed by FEV Motorentechnik GmbH, Aachen, is designed to improve the predictability of journal bearing designs and thereby increase the reliability of safety factors in the development of highly loaded internal combustion engines. Using this tool design targets can be achieved with higher confidence levels. The developed code may be linked to commercial multibody system (MBS) codes such as ADAMS® while simultaneously representing the important characteristics occurring in transiently loaded journal bearings including elastic deformation, cavitation, and non-constant speed. Static deviations from ideal journal and bearing shell shapes caused by manufacturing and assembly processes can be considered and are substantially important in the evaluation of journal bearings. Presented is an economic bearing model approach which includes elastic bearing deformations.

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.

Over the next decade, CO2 legislation will be more demanding and the automotive industry has seen in vehicle electrification a possible solution. This has led to an increasing need for advanced powertrain systems and systematic model-based control approaches, along with additional complexity. This represents a serious challenge for all the OEMs. This paper describes a novel reverse engineering methodology developed to estimate relevant powertrain data required for fuel consumption-oriented hybrid electric vehicle (HEV) modelling. The estimated quantities include high-voltage battery internal resistance, electric motor and transmission efficiency, gearshift thresholds, torque converter performance diagrams, engine fuel consumption map and front/rear hydraulic brake torque distribution. This activity provides a list of dedicated experimental tests, to be carried out on road or on a chassis dynamometer, aiming at powertrain characterization thanks to a suitable post-processing algorithm.

Despite the legislation targets set by several governments of a full electrification of new light-duty vehicle fleets by 2035, the development of innovative, environmental-friendly Internal Combustion Engines (ICEs) is still crucial to be on track toward the complete decarbonization of on road-mobility of the future. In such a framework, the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) project aims at developing a C SUV-class plug-in hybrid (P0/P4) vehicle demonstrator capable to achieve a -10% fuel consumption reduction with respect to current EU6 vehicle while complying with upcoming EU7 pollutant emissions limits. Such ambitious targets will require the optimization of the whole engine system, exploiting the possible synergies among the combustion, the aftertreatment and the exhaust waste heat recovery systems.

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.

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.

The technology used in hybrid vehicle concepts is significantly different from conventional vehicle technology with consequences also for the noise and vibration behavior. In conventional vehicles, certain noise phenomena are masked by the engine noise. In situations where the combustion engine is turned off in hybrid vehicle concepts, these noise components can become dominant and annoying. In hybrid concepts, the driving condition is often decoupled from the operation state of the combustion engine, which leads to unusual and unexpected acoustical behavior. New acoustic phenomena such as magnetic noise due to recuperation occur, caused by new components and driving conditions. The analysis of this recuperation noise by means of interior noise simulation shows, that it is not only induced by the powertrain radiation but also by the noise path via the powertrain mounts. The additional degrees of freedom of the hybrid drive train can also be used to improve the vibrational behavior.