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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 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.

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.

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.

The continuous development of modern Internal Combustion Engine (ICE) management systems is mainly aimed at complying with upcoming increasingly stringent regulations throughout the world. Performing an efficient combustion control is crucial for efficiency increase and pollutant emissions reduction. These aspects are even more crucial for innovative Low Temperature Combustions (such as RCCI), mainly due to the high instability and the high sensitivity to slight variations of the injection parameters that characterize this kind of combustion. Optimal combustion control can be achieved through a proper closed-loop control of the injection parameters. The most important feedback quantities used for combustion control are engine load (Indicated Mean Effective Pressure or Torque delivered by the engine) and center of combustion (CA50), i.e. the angular position in which 50% of fuel burned within the engine cycle is reached.

Recent and forthcoming fuel consumption reduction requirements and exhaust emissions regulations are forcing the development of innovative and particularly complex intake-engine-exhaust layouts. In the case of Spark Ignition (SI) engines, the necessity to further reduce fuel consumption has led to the adoption of direct injection systems, displacement downsizing, and challenging intake-exhaust configurations, such as multi-stage turbocharging or turbo-assist solutions. Further, the most recent turbo-GDI engines may be equipped with other fuel-reduction oriented technologies, such as Variable Valve Timing (VVT) systems, devices for actively control tumble/swirl in-cylinder flow components, and Exhaust Gas Recirculation (EGR) systems. Such degree of flexibility has a main drawback: the exponentially increasing effort required for optimal engine control calibration.

Nowadays, an automotive DI Diesel engine is demanded to provide an adequate power output together with limit-complying NOx and soot emissions so that the development of a specific combustion concept is the result of a trade-off between conflicting objectives. In other words, the development of a low-emission DI diesel combustion concept could be mathematically represented as a multi-objective optimization problem. In recent years, genetic algorithm and CFD simulations were successfully applied to this kind of problem. However, combining GA optimization with actual CFD-3D combustion simulations can be too onerous since a large number of simulations is usually required, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes.

During the last years the deep re-examination of the engine design for lowering engine emissions involved two-wheel vehicles too. The IC engine overall efficiency plays a fundamental role in determining final raw emissions. From this point of view, the optimization of the in-cylinder flow organization is mandatory. In detail, in SI engines the generation of a coherent tumble vortex having dimensions comparable to the engine stroke could be of primary importance to extend the engines' ignition limits toward the field of the dilute/lean mixtures. For motorbike and motor scooter applications, the optimization of the tumble generation is considered an effective way to improve the combustion system efficiency and to lower emissions, considering also that the two-wheels layout represents an obstacle in adopting the advanced post-treatment concepts designed for automotive applications.

Combustion phasing is crucial to achieve high performance and efficiency: for gasoline engines control variables such as Spark Advance (SA), Air-to-Fuel Ratio (AFR), Variable Valve Timing (VVT), Exhaust Gas Recirculation (EGR), Tumble Flaps (TF) can influence the way heat is released. The optimal control setting can be chosen taking into account performance indicators, such as Indicated Mean Effective Pressure (IMEP), Brake Specific Fuel Consumption (BSFC), pollutant emissions, or other indexes inherent to reliability issues, such as exhaust gas temperature, or knock intensity. Given the high number of actuations, the calibration of control parameters is becoming challenging.

This paper presents an optimization algorithm, based on discrete dynamic programming, that aims to find the optimal control inputs both for energy and thermal management control strategies of a Plug-in Hybrid Electric Vehicle, in order to minimize the energy consumption over a given driving mission. The chosen vehicle has a complex P1-P4 architecture, with two electrical machines on the front axle and an additional one directly coupled with the engine, on the rear axle. In the first section, the algorithm structure is presented, including the cost-function definition, the disturbances, the state variables and the control variables chosen for the optimal control problem formulation. The second section reports the simplified quasi-static analytical model of the powertrain, which has been used for backward optimization. For this purpose, only the vehicle longitudinal dynamics have been considered.

The high number of hull losses is a main concern in the UAV field, mostly due to the high cost of on-board equipment. A crashworthiness design can be helpful to control the extent and position of crash impact damage, minimizing equipment losses. However, the wide use of composite materials has recently put the accent on the lack of data about the behavior of these structures under operative loads, such as the crash conditions. This paper presents the outcome of a set of tests carried out to achieve a controlled crush of UAV structures, and to maximize the Specific Energy Absorption. In this work, a small-scale experimental test able to characterize the energy absorption of a Carbon-fiber-reinforced polymer under compression was developed introducing self-supporting sinusoidal shape specimens, which avoid the need for complex anti-buckling devices.