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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.

The continuous development of modern Internal Combustion Engine (ICE) management systems is mainly aimed at combustion control improvement. Nowadays, performing an efficient combustion control is crucial for drivability improvement, efficiency increase and pollutant emissions reduction. These aspects are even more crucial when innovative combustions (such as LTC or RCCI) are performed, due to the high instability and the high sensitivity with respect to the injection parameters that are associated to this kind of combustion. Aging of all the components involved in the mixture preparation and combustion processes is another aspect particularly challenging, since not all the calibrations developed in the setup phase of a combustion control system may still be valid during engine life.

The purpose of this paper is to present some innovative techniques developed for an unconventional utilization of currently standard exhaust sensors, such as HEGO, UEGO, and NOx probes. In order to comply with always more stringent legislation about pollutant emissions, intake-exhaust systems are becoming even more complex and sophisticated, especially for CI engines, often including one or two UEGO sensors and a NOx sensor, and potentially equipped with both short-route and long-route EGR. Within this context, the effort to carry out novel methods for measuring the main exhaust gas dynamic properties exploiting sensors installed for different purposes, could be useful both for control applications, such as EGR rates estimation, or cost reduction, minimizing the on-board devices number. In this work, a gray-box model for measuring the gas mass flow rate, based on standard NOx sensor operating parameters of its heating circuit, is analyzed.

A control oriented model of a Dual Clutch Transmission was developed for real time Hardware In the Loop (HIL) applications. The model is an innovative attempt to reproduce the fast dynamics of the actuation system maintaining a step size large enough for real time applications. The model comprehends a detailed physical description of hydraulic circuit, clutches, synchronizers and gears, and simplified vehicle and internal combustion engine sub-models; a stable real time simulation is achieved with a simplification of the model without losing physical validity. After an offline validation, the model was implemented in a HIL system and connected to the TCU (Transmission Control Unit) via two input-output boards, and to a load plate which comprehends all the actuators.

The paper deals with the reduction of pollutant emissions in urban areas by considering a Zero-Emission Zone (ZEZ) in which hybrid electric vehicles (HEVs) are allowed to be driven without using the internal combustion engine, as several cities have planned to realize in the next decades. Moreover, since vehicle connectivity has spread more and more in the last years, a vehicle-to-network (V2N) communication system has been taken into account to retrieve real-time navigation data from a map service provider and thus reconstructing the so-called electronic horizon, which is a reconstruction of the future conditions of the vehicle on the road ahead. The speed profile and the road slope are used as input for an on-board predictive control strategy of a plug-in HEV (PHEV). In particular, a dedicated algorithm predicts the amount of necessary energy to complete the city event in full-electric mode, giving a state of charge (SoC) target value.

This work focuses on the effects of cooled Low Pressure EGR and Water Injection observed by conducting experimental tests consisting mainly of Spark Advance sweeps at different cooled LP-EGR and WI rates. The implications on combustion and main engine performance indexes are then analysed and modelled with a control-oriented approach, showing that combustion duration and phase and exhaust gas temperature are the main affected parameters. Results show that cooled LP-EGR and WI have similar effects, being the associated combustion speed decrease the main cause of exhaust gas temperature reduction. Experimental data is used to identify control-oriented polynomial models able to capture the effects of LP-EGR and WI on both these aspects. The limitations of LP-EGR are also explored, identifying maximum compressor volumetric flow and combustion stability as the main ones.

Engine test benches are crucial instruments to perform tests on internal combustion engines. Since many factors affect tests results, an engine test bench is usually equipped with several conditioning systems (oil, water and air temperature, air humidity, etc.), in order to maintain the controlled variables to the target values, throughout the test duration. The conditioning systems are often independently controlled by means of dedicated programmable logic controllers (PLC), but a centralized model-based management approach could offer several advantages in terms of promptness and accuracy. This work presents the application of such control methodology to oil, water, and HVAC (heating, ventilating, and air conditioning) conditioning systems, where each actuator is managed coupling model-based open loop controls to closed loop actions.

Pre-ignition combustions are extremely harmful and undesired, but the recent search for extremely efficient spark-ignition engines has implied a great increase of the in-cylinder pressure and temperature levels, forcing engine operation to conditions that may trigger this type of anomalous combustion much more frequently. For this reason, an accurate on-board diagnosis system is required to adopt protective measures, preventing engine damage. Ion current signal provides relevant information about the combustion process, and it results in a good compromise between cost, durability and information quality (signal to noise ratio levels). The GDI turbocharged engine used for this study was equipped with a production ion current sensing system, while in-cylinder pressure sensors were installed for research purposes, to better understand the pre-ignition phenomenon characteristics, and to support the development of an on-board diagnostic system solely based on ion current measurements.

Shock absorbers and damper systems are important parts of automobiles and motorcycles because they have effects on safety, ride comfort, and handling. In particular, for vehicle safety, shock absorber system plays a fundamental role in maintaining the contact between tire and road. Generally, to assure the best trade-off between safety and ride comfort, a fine experimental tuning on all shock absorber components is necessary. Inside a common damper system the presence of several conjugated actions made by springs, oil and pressurized air requires a significant experimental support and a great number of prototypes and test. Aimed to reduce the design and tuning phases of a damper system, it is necessary to join these phases together with a numerical modelling phase. The aim of this paper is to present the development of a mono-dimensional (1D) model for simulating dynamic behaviour of damper system.

This paper shows how Rapid Control Prototyping (RCP) and Computational Fluid Dynamics (CFD) techniques have been applied to design and implement an engine control system for a common rail diesel engine. The project aim is to setup a high performance engine in order to participate to the Italian Tractor Pulling Championship (Prostock category). The original engine is a John Deere 6081 Tier2 model, already equipped with a common rail system. Engine performance is substantially determined by the control system, which is in charge of limiting engine speed, boost pressure and Air to Fuel Ratio (AFR). Given that typically the information and equipment needed to change control parameters are not accessible to customers, the first step of the project has been to replace the original control system, while maintaining injectors and pumps. This solution can guarantee the best performance, but it requires time to design the new control system, both in terms of hardware and software.

The aim of this work is to propose modifications to the managing of the 1st generation Common Rail injectors in order to reduce actuation time towards multiple injection strategies. The current Common Rail injector driven by 1st ECU generation is capable of operating under stable conditions with a minimum dwell between two consecutive injections of 1.8 ms. This limits the possibility in using proper and efficient injection strategies for emission control purposes. A previous numerical study, performed by the electro-fluid-mechanical model built up by Matlab-Simulink environment, highlighted different area where injector may be improved with particular emphasis on electronic driving circuit and components design. Experiments carried out at injector Bosch test-bench showed that a proper control of the solenoid valve allowed reducing drastically the standard deviation during the pilot pulses.

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.

New and upcoming exhaust emissions regulations and fuel consumption reduction requirements are forcing the development of innovative and particularly complex intake-engine-exhaust layouts. Especially in the case of Compression Ignition (CI) engines, the HC-CO-NOx-PM after-treatment system is becoming extremely expensive and sophisticated, and the necessity to further reduce engine-out emission levels, without significantly penalizing fuel consumption figures, may lead to the adoption of intricate and challenging intake-exhaust systems configurations. The adoption of both long- and short-route Exhaust Gas Recirculation (EGR) systems is one example of such situation, and the need to precisely measure (or estimate) mass flow rates in the various elements of the gas exchange circuit is one of the consequences.

Scaled models are often used to check the aerodynamic performance of full scale aircraft and airship concepts, which have gone through a conceptual and preliminary design process. Results from these tests can be quite useful to improve the design of unconventional airships whose aerodynamics might be quite different from classical configurations. Once the airship geometry has been defined, testing is required to acquire aerodynamic data necessary to implement the mathematical model of the airship needed by the flight control system to develop full autonomous capabilities. Rapid prototyping has the great potential of playing a beneficial role in unconventional autonomous airship design similarly to the success obtained in the design process of conventional aircrafts.

Added masses computation is a crucial aspect to be considered when the density of a body moving in a fluid is comparable to the density of the fluid displaced: added mass can be defined as the inertia added to a system because an accelerating or decelerating body displaces some volume of neighboring fluid as it moves through it. The motion of vehicles like airships and ships can be addressed only by keeping into account the effect of added masses, while in case of aircrafts and helicopters this contribution is usually neglected. Lighter Than Air flight simulation, unmanned airships flight control system, airships flight dynamics are typical applications in which added masses are fundamental to achieve an effective and realistic modeling. A panel based method using the mesh of an airship external shape is developed to account for the added massed.

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.

This paper presents a 14 degrees of freedom vehicle model. Despite numerous software are nowadays commercially available, the model presented in this paper has been built starting from a blank sheet because the goal of the authors was to realize a model suitable for real-time simulation, compatible with the computational power of typical electronic control units, for on-board applications. In order to achieve this objective a complete vehicle dynamics simulation model has been developed in Matlab/Simulink environment: having a complete knowledge of the model's structure, it is possible to adapt its complexity to the computational power of the hardware used to run the simulation, a crucial feature to achieve real-time execution in actual ECUs.

In the past years, stringent emission regulations for Internal Combustion (IC) engines produced a large amount of research aimed at the development of innovative combustion methodologies suitable to simultaneously reduce fuel consumption and engine-out emissions. Previous research demonstrates that the goal can be obtained through the so-called Low Temperature Combustions (LTC), which combine the benefits of compression-ignited engines, such as high compression ratio and unthrottled lean operation, with a properly premixed air-fuel mixture, usually obtained injecting gasoline-like fuels with high volatility and longer ignition delay. Gasoline Partially Premixed Combustion (PPC) is a promising LTC technique, mainly characterized by the high-pressure direct-injection of gasoline and the spontaneous ignition of the premixed air-fuel mixture through compression, which showed a good potential for the simultaneous reduction of fuel consumption and emissions in CI engines.

Due to the ever increasingly stringent emission regulations for passenger vehicles, the efficiency and performance increase of Spark Ignition (SI) engines have been under the focus of the engine manufacturers. The quest for efficiency and performance increase has led to the development of increasingly complex powertrains and control strategies. The development process requires novel methods that feature a smooth transition between the real and the virtual prototypes. Furthermore, to reduce the development time and cost, developing an engine simulator with a low computational effort and good accuracy, which predicts the engine behavior on the entire operating range, plays a crucial role. This work proposes an Artificial Intelligence-based engine simulator for a Spark Ignition engine. The simulator relies on Neural Networks for the calculation of the main combustion metrics. In the first part of this paper, the data acquired at the engine test cell are analyzed.