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A detailed analysis of knocking events can help improving engine performance and diagnosis strategies. The paper aim is a better understanding of the phenomena involved in knocking combustions through the combination of CFD and signals analysis tools. CFD simulations have been used in order to reproduce knock effect on the in-cylinder pressure trace. In fact, the in-cylinder pressure signal holds information about waves propagation and heat losses: for the sake of the diagnosis it is important to relate knock severity to knock indexes values. For this purpose, a CFD model has been implemented, able to predict the combustion evolution with respect to Spark Advance, from non-knocking up to heavy knocking conditions. The CFD model validation phase is crucial for a correct representation of both regular and knocking combustions: the operation has been carried out by means of an accurate statistical analysis of experimental in-cylinder pressure data.

Fork system is a primary component for motorcycles because it assures the contact between tires and road, therefore the safety and the driving feeling. Usually fork optimization and tuning are experimentally made involving the generation of a high large number of prototypes and an expensive experimental campaign. To reduce the design and the tuning phases of a generic damper system, the numerical simulation should be considered. In this paper, a one-dimensional (1D) model of fore-carriage forks for road applications is presented. The model was built-up in AMESim code. In particular, the authors’ attention was focused on the detection and analysis of cavitation phenomenon inside the fork. As well known, the cavitation is a complex three-dimensional (3D) phenomenon that implies the phase transition.

The optimization of turbocharging systems for automotive applications has become crucial in order to increase engine performance and meet the requirements for pollutant emissions and fuel consumption reduction. Unfortunately, performing an optimal turbocharging system control is very difficult, mainly due to the fact that the flow through compressor and turbine is highly unsteady, while only steady flow maps are usually provided by the manufacturer. For these reasons, one of the most important quantities to be used onboard for optimal turbocharger system control is the rotational speed fluctuation, since it provides information both on turbocharger operating point and on the energy of the unsteady flow in the intake and exhaust circuits. This work presents a methodology that allows determining the instantaneous turbocharger rotational speed through a proper frequency processing of the signal coming from one accelerometer mounted on the turbocharger compressor.

The first cross-industry guidelines for the implementation of structural health monitoring for aerospace applications have been created as a SAE International Aerospace Recommended Practices document: SAE ARP 6461 ‘Guidelines for Implementation of Structural Health Monitoring on Fixed Wing Aircraft’ [1]. These guidelines have brought together manufacturers, operators / users, systems integrators, regulators, technology providers and researchers to produce information on the integration of SHM into aircraft maintenance procedures, generic requirements and advice on validation, verification and airworthiness. The take-up of SHM in the aerospace industry has been slow, in part due to the lack of accepted industry practices surrounding not just the technology itself (sensors and sensor systems) but also the associated issues arising from the introduction of new methods into aircraft maintenance.

The simulation of heat exchanger air flow characteristics in a sub-scale wind tunnel test requires an accurate representation of the full-scale pressure drop across the element. In practice this is normally achieved using laminations of various porous materials and honeycombs on the basis of experience and ad hoc data. In view of this, a series of measurements of the pressure drop, in both the near and far field, across screens with porosity (β) in the range 0.41 ≺ β ≺ 0.76 are reported. The aim being to establish a relationship between the porosity and the pressure drop characteristics of a given material at various angles of inclination to the free-stream flow. Furthermore, the effect of screen depth was investigated using honeycombs. This data will facilitate detailed design and accurate representation of the flow characteristics at sub scale.

The incorporation of hydrogen fuel cells into heavy duty tactical mobility vehicles can bring about great opportunities in reducing the pollutant emissions of this kind of platforms (GVW > 30,000 kg). Furthermore the transportation of fuel to operational areas has become a key aspect for any deployment therefore optimal use of this resource is of paramount importance. Finally, it is also quite common for such platforms to serve additional purposes, besides freight delivery, such as powering external equipment (i.e. field hospitals or mobile artillery pieces). This work will describe the intelligent energy management system for a PEM Fuel Cell-Battery-Ultracapacitor Hybrid 8×8 heavy truck of the aforementioned weight class which also contemplates an internal electric/traction power generation unit. It will describe how the system optimizes the use of battery and hydrogen fuel energy while keeping system efficiency and performance at a maximum.

The recent advance in the development of various hybrid vehicle technologies comes along with the need of establishing optimal energy management strategies, in order to minimize both fuel economy and pollutant emissions, while taking into account an increasing number of state and control variables, depending on the adopted hybrid architecture. One of the objectives of this research was to establish benchmarking performance, in terms of fuel economy, for real time on-board management strategies, such as ECMS (Equivalent Consumption Minimization Strategy), whose structure has been implemented in a SIMULINK model for different hybrid vehicle concepts.

Diesel engine performances are strictly correlated to the fluid dynamic characteristics of the injection system. Actual Diesel engines employ injector characterized by micro-orifices operating at injection pressure till 20MPa. These main injection characteristics resulted in the critical relation between engine performance and injector hole shape. In the present study, the authors' attention was focused on the hole geometry influence on the main injector fluid dynamic characteristics. At this purpose, three different nozzle hole shapes were considered: cylindrical, k, and ks nozzle shapes. Because of the lack of information available about ks-hole real geometry, firstly it was completely characterized by the combined use of two non-destructive techniques. Secondly, all the three nozzle layouts were characterized from the fluid dynamic point of view by a fully transient CFD multiphase simulation methodology previously validated by the authors against experimental results.

In a multi-pass weld, the development of residual stress to a large extent depends on the response of the weld metal, heat affected zone and parent material to complex thermo-mechanical cycles during welding. Previous investigations on this subject mostly focused on mechanical tensioning or heat treatment to modify the residual stress distribution in and around the weld. In this research, microstructural refinement with modification of residual stress state was attempted by applying post weld cold rolling followed by laser processing. The hardening of the weld metal was evaluated after welding, post weld cold rolling and post weld cold rolling followed by laser processing. The residual stress was determined non-destructively by using neutron diffraction. Hardness results showed evidence of plastic deformation up to 4 mm below the weld surface.

The Selective Catalytic Reduction (SCR) system installed on the exhaust line is currently widely used on Diesel heavy-duty trucks and it is considered a promising technique for light and medium duty trucks, large passenger cars and off-highway vehicles, to fulfill future emission legislation. Some vehicles of these last categories, equipped with SCR, have been already put on the market, not only in the US, where the emission legislation on Diesel vehicles is more restrictive, but also in Europe, demonstrating to be already compliant with the upcoming Euro 6. Moreover, new and more stringent emission regulations and homologation cycles are being proposed all over the world, with a consequent rapidly increasing interest for this technology. As a matter of fact, a physical model of the Diesel Exhaust Fluid (DEF) supply system is very useful, not only during the product development phase, but also for the implementation of the on-board real-time controller.

Internal combustion engines are the primary transportation mover for today society and they will likely continue to be for decades to come. Hybridization is the most common solution to reduce the petrol-fuels consumption and to respect the new raw emission limits. The gasoline engines designed for running together with an electric motor need to have a very high thermal efficiency because they must work at high loads, where engine thermal efficiency is close to the maximum one. Therefore, the technical solutions bringing to thermal efficiency enhancement were adopted on HVs (Hybrid Vehicles) prior to conventional vehicles. In these days, these solutions are going to be adopted on conventional vehicles too. The purpose of this work was to trace development guidelines useful for engine designers, based on the target power and focused on the maximization of the engine thermal efficiency, following the engine rightsizing concept.

This work focuses on the development and validation of a data-driven model capable of predicting the maximum in-cylinder pressure during the operation of an internal combustion engine, with the least possible computational effort. The model is based on two parameters, one that represents engine load and another one the combustion phase. Experimental data from four different gasoline engines, two turbocharged Gasoline Direct Injection Spark Ignition, a Naturally Aspirated SI and a Gasoline Compression Ignition engine, was used to calibrate and validate the model. Some of these engines were equipped with technologies such as Low-Pressure Exhaust Gas Recirculation and Water Injection or a compression ignition type of combustion in the case of the GCI engine. A vast amount of engine points were explored in order to cover as much as possible of the operating range when considering automotive applications and thus confirming the broad validity of the model.

Over the last decade, there has been an impetus in the automobile industry to develop new diesel injector systems, driven by a desire to reduce fuel consumption and proscribed by the requirement to fulfil legislation emissions. The modern common-rail diesel injector system has been developed by the industry to fulfil these aspirations, designed with ever-higher tolerances and pressures, which have led to concomitant increases in fuel temperatures after compression with reports of fuel temperatures of ~150°C at 1500-2500 bar. This engineering solution in combination with the introduction of Ultra Low Sulphur diesel fuel (ULSD) has been found to be highly sensitive to deposit formation both external injector deposits (EDID) and internal (IDID). The deposits have caused concerns for customers with poor spray patterns misfiring injector malfunction and failure, producing increased fuel consumption and emissions.

Modern turbo-charged downsized engines reach high values of specific power, causing a significant increase of the exhaust gas temperature. Such parameter plays a key role in the overall powertrain environmental impact because it strongly affects both the catalyst efficiency and the turbine durability. In fact, common techniques to properly manage the turbine inlet gas temperature are based on mixture enrichment, which causes both a steep increase in specific fuel consumption and a decrease of catalyst efficiency. At the test bench, exhaust gas temperature is typically measured using thermocouples that are not available for on-board application, and such information is processed to calibrate open-loop look-up-tables. A real-time, reliable, and accurate exhaust temperature model would then represent a strategic tool for improving the performance of the engine control system.

In the field of passenger car engines, recent research advances have proven the effectiveness of downsized, turbocharged and direct injection concepts, applied to gasoline combustion systems, to reduce the overall fuel consumption while respecting particularly stringent exhaust emissions limits. Knock and turbocharger control are two of the most critical factors that influence the achievement of maximum efficiency and satisfactory drivability, for this new generation of engines. The sound emitted from an engine encloses many information related to its operating condition. In particular, the turbocharger whistle and the knock clink are unmistakable sounds. This paper presents the development of real-time control functions, based on direct measurement of the engine acoustic emission, captured by an innovative and low cost acoustic sensor, implemented on a platform suitable for on-board application.

The paper presents possible solutions for developing fast and reliable turbocharger models, to be used mainly for control applications. This issue is of particular interest today for SI engines since, due to the search for consistent CO2 reduction, extreme downsizing concepts require highly boosted air charge solutions to compensate for power and torque de-rating. For engines presenting at least four in-line cylinders, twin-entry turbines offer the ability of maximizing the overall energy conversion efficiency, and therefore such solutions are actually widely adopted. This work presents a critical review of the most promising (and recent) modeling approaches for automotive turbochargers, highlighting the main open issues especially in the field of turbine models, and proposing possible improvements.

Knocking combustions heavily influence the efficiency of Spark Ignition engines, limiting the compression ratio and sometimes preventing the use of Maximum Brake Torque (MBT) Spark Advance (SA). A detailed analysis of knocking events can help in improving the engine performance and diagnostic strategies. An effective way is to use advanced 3D Computational Fluid Dynamics (CFD) simulation for the analysis and prediction of the combustion process. The standard 3D CFD approach based on RANS (Reynolds Averaged Navier Stokes) equations allows the analysis of the average engine cycle. However, the knocking phenomenon is heavily affected by the Cycle to Cycle Variation (CCV): the effects of CCV on knocking combustions are then taken into account, maintaining a RANS CFD approach, while representing a complex running condition, where knock intensity changes from cycle to cycle.

The next steps of the current European and US legislation, EURO 6c and LEV III, and the incoming new test cycles will impose more severe restrictions on pollutant emissions for Gasoline Direct Injection (GDI) engines. In particular, soot emission limits will represent a challenge for the development of this kind of engine concept, if injection and after-treatment systems costs are to be minimized at the same time. The paper illustrates the results obtained by means of a numerical and experimental approach, in terms of soot emissions and combustion stability assessment and control, especially during catalyst-heating conditions, where the main soot quantity in the test cycle is produced. A number of injector configurations has been designed by means of a CAD geometrical analysis, considering the main effects of the spray target on wall impingement.

Energy management strategies greatly influence the power performance and fuel economy of series hybrid electric tracked bulldozers. In this paper, we present a procedure for the design of a power management strategy by defining a cost function, in this case, the minimization of the vehicle’s fuel consumption over a driving cycle. To explore the fuel-saving potential of a series hybrid electric tracked bulldozer, a dynamic programming (DP) algorithm is utilized to determine the optimal control actions for a series hybrid powertrain, and this can be the benchmark for the assessment of other control strategies. The results from comparing the DP strategy and the rule-based control strategy indicate that this procedure results in approximately a 7% improvement in fuel economy.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.