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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.

In order to extend the CAI operation range in 4-stroke mode and maximize the benefit of low fuel consumption and emissions in CAI mode, 2-stroke CAI combustion is revived operating in a GDI engine with poppet valves, where the conventional crankcase scavenging is replaced by boosted scavenging. The CAI combustion is achieved through the inherence of the 2-Stroke operation, which is retaining residual gas. A set of flexible hydraulic valve train was installed on the engine to vary the residual gas fraction under the boosting condition. The effects of spark timing, intake pressure and short-circuiting on 2-stroke CAI combustion and its emissions are investigated and discussed in this paper. Results show the engine could be controlled to achieve CAI operation over a wide range of engine speed and load in the 2-stroke mode because of the flexibility of the electro-hydraulic valvetrain system. Presenter Yan Zhang, Brunel University

In order to extend the CAI operation range in 4-stroke mode and maximize the benefit of low fuel consumption and emissions in CAI mode, 2-stroke CAI combustion is revived operating in a GDI engine with poppet valves, where the conventional crankcase scavenging is replaced by boosted scavenging. The CAI combustion is achieved through the inherence of the 2-Stroke operation, which is retaining residual gas. A set of flexible hydraulic valve train was installed on the engine to vary the residual gas fraction under the boosting condition. The effects of spark timing, intake pressure and short-circuiting on 2-stroke CAI combustion and its emissions are investigated and discussed in this paper. Results show the engine could be controlled to achieve CAI operation over a wide range of engine speed and load in the 2-stroke mode because of the flexibility of the electro-hydraulic valvetrain system.

Controlled Auto Ignition (CAI), also known as Homogeneous Charge Compression Ignition (HCCI), is one of the most promising combustion technologies to reduce the fuel consumption and NOx emissions. Currently, CAI combustion is constrained at part load operation conditions because of misfire at low load and knocking combustion at high load, and the lack of effective means to control the combustion process. Extending its operating range including high load boundary towards full load and low load boundary towards idle in order to allow the CAI engine to meet the demand of whole vehicle driving cycles, has become one of the key issues facing the industrialisation of CAI/HCCI technology. Furthermore, this combustion mode should be compatible with different fuels, and can switch back to conventional spark ignition operation when necessary. In this paper, the CAI operation is demonstrated on a 2-stroke gasoline direct injection (GDI) engine equipped with a poppet valve train.

Controlled Auto-Ignition (CAI) also known as Homogeneous Charge Compression Ignition (HCCI) is increasingly seen as a very effective way of lowering both fuel consumption and emissions. Hence, it is regarded as one of the best ways to meet stringent future emissions legislation. It has however, still many problems to overcome, such as limited operating range. This combustion concept was achieved in a production type, 4-cylinder gasoline engine, in two separated tests: naturally aspirated and turbocharged. Very few modifications to the original engine were needed. These consisted basically of a new set of camshafts for the naturally aspirated test and new camshafts plus turbocharger for the test with forced induction. After previous experiments with naturally aspirated CAI operation, it was decided to investigate the capability of turbocharging for extended CAI load and speed range.

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.

Pumping Mean Effective Pressure (PMEP) is the main factor limiting the improvement of thermal efficiency in a spark-ignition (SI) engine under low load. One of the ways to reduce the pumping loss under low load is to use Cylinder DeActivation (CDA). The CDA aims at reducing the firing density (FD) of the SI engine under low load operation and increasing the mass of air-fuel mixture within one cycle in one cylinder to reduce the throttling effect and further reducing the PMEP. The multi-stroke cycles can also reduce the firing density of the SI engine after some certain reasonable design, which is feasible to improve the thermal efficiency of the engine under low load in theory. The research was carried out on a calibrated four-cylinder SI engine simulation platform. The thermal efficiency improvements of the 6-stroke cycle and 8-stroke cycle to the engine performance were studied compared with the traditional 4-stroke cycle under low load conditions.

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.

Nowadays stringent emission regulations are pushing towards new air management strategies like LP-EGR and HP/LP mix both for passenger car and heavy duty applications, increasing the engine control complexity. Within a project in collaboration between Kohler Engines EMEA, Politecnico di Torino, Ricardo and Denso to exploit the potential of EGR-Only technologies, a 3.4 liters KDI 3404 was equipped with a two stage turbocharging system, an extremely high pressure FIS and a low pressure EGR system. The LP-EGR system works in a closed loop control with an intake oxygen sensor actuating two valves: an EGR valve placed downstream of the EGR cooler that regulates the flow area of the bypass between the exhaust line and the intake line, and an exhaust flap to generate enough backpressure to recirculate the needed EGR rate to cut the NOx emission without a specific aftertreatment device.

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.

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.

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.

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.

This paper presents a new 0D phenomenological approach to predict the combustion process in diesel engines operated under various running conditions. The aim of this work is to develop a physical approach in order to improve the prediction of in-cylinder pressure and heat release. The main contribution of this study is the modeling of the premixed part of the diesel combustion with a further extension of the model for multi-injection strategies. In phenomenological diesel combustion models, the premixed combustion phase is usually modeled by the propagation of a turbulent flame front. However, experimental studies have shown that this phase of diesel combustion is actually a rapid combustion of part of the fuel injected and mixed with the surrounding gas. This mixture burns quasi instantaneously when favorable thermodynamic conditions are locally reached. A chemical process then controls this combustion.

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.

Biofuels are a renewable energy source. When used as extenders for transportation fuels, biofuels contribute to the global reduction of Green House Gas and CO2 emissions from the transport sector and to security and independence of energy supply. On a “Well to Wheel” basis they are much more CO2 efficient than conventional fossil fuels. All vehicles currently in circulation in Europe are capable of using 5 % biodiesel. The introduction of higher percentages biodiesel needs new specific standards and vehicle tests validation. The development of vehicles compatible with 30% biodiesel blends in diesel fuel includes the validation of each part of both engine and fuel vehicle systems to guarantee normal operation for the entire life of the vehicle.