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A computer code oriented to S.I. engine control and powertrain simulation is presented. The model, developed in Matlab-Simulink® environment, predicts engine and driveline states, taking into account the dynamics of air and fuel flows into the intake manifold and the transient response of crankshaft, transmission gearing and vehicle. The model, derived from the code O.D.E.C.S. for the optimal design of engine control strategies now in use at Magneti Marelli, is suitable both for simulation analysis and to achieve optimal engine control strategies for minimum consumption with constraints on exhaust emissions and driveability via mathematical programming techniques. The model is structured as an object oriented modular framework and has been tested for simulating powertrain system and control performance with respect to any given transient and control strategy.

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.

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.

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.

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.

This paper describes the design and development of a virtual environment conceived to support flight operations of an Unmanned Air Vehicle (UAV) used for wind mapping in the proximity of existing or planned wind farms. The virtual environment can be used in pre-flight briefings aiming to define a trajectory from a list of waypoints, to change and eventually re-plan the mission in case of intersection with no fly zones, to simulate the mission, and to preview images/videos taken from the UAV on-board cameras. During flight, the tool can be used to compute the wind speed along the trajectory by analyzing the data streaming from the UAV. The integration of Augmented Reality (AR) techniques in the flight environment provides assistance in remotely piloted landings, and allows visualizing flight and environmental information that are critical to the mission.

Knock control systems based on engine block vibrations analysis are widely adopted in passenger car engines, but such approach shows its main limits at high engine speeds, since knock intensity measurement becomes less reliable due to the increased background mechanical noise. For small two wheelers engines, knock has not been historically considered a crucial issue, mainly due to small-sized combustion chambers and mixture enrichment. Due to more stringent emission regulations and in search of reduced CO2 emissions, an effective on-board knock controller acquires today greater importance also for motorcycle applications, since it could protect the engine when different fuel types are used, and it could significantly reduce fuel consumption (by avoiding lambda enrichment and/or allowing higher compression ratios to be adopted). These types of engines typically work at high rotational speeds and the reduced signal to noise ratio makes knock onset difficult to identify.

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 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 need to reduce carbon dioxide emissions from motor vehicles pushes the European Union towards drastic choices on future mobility. Despite this, the engines of the “future” have not yet been defined: the choice of engine type will undoubtedly depend on the type of application (journey length, availability of recharging/refueling facilities), practical availability of alternative fuels, and electricity to recharge the batteries. The electrification of vehicles (passenger and transportation cars) may be unsuitable for several aspects: the gravimetric energy density could be too low if the vehicle has to be lightweight, must achieve a high degree of autonomy, or needs a very short refueling time.

To meet the requirements in relation to pollutants, CO2-emissions, performances, comfort and costs for 2025 timeframe, many technology options for the powertrain, that plays a key role in the vehicle, are possible. Beside the central aspect of reducing standard cycle consumption levels and emissions, consumer demands are also growing with respect to comfort and functionality. In addition, there is also the challenge of finding cost efficient ways of integrating technologies into a broad range of vehicles with different levels of hybridization. High degrees of electrification simultaneously provide opportunities to reduce the technology content of the internal combustion engines (ICE), resulting in a cost balancing compromise between combustion engine and hybrid technology. The design and optimization of powertrain topologies, functionalities, and components require a complex development process.

This paper describes a dual-processor platform for automotive powertrain control with a high-bandwidth interconnection network among processors, memory, and I/O sub-systems, which is suitable for a System-On-Chip (SOC) implementation. The two processors share memory and I/O address space and can operate in parallel at full speed. The cost of this solution, in terms of gates and power dissipation, is not substantially higher than more classical architectures with a multi-master bus or multiple processor busses connected through gateways, but offers almost twice the performance.

The paper presents a study made to define the optimal parameter configuration, which enables the mixture preparation, and ignition systems to perform a low-temperature engine start by pure ethanol fuelling without misfiring or failure. A numerical virtual engine, simulating the behavior of a real small displacement 8 valves passenger car engine, is set up to describe and understand the physical phenomena of mixture preparation, spatial and temporal in-cylinder mixture distribution and the ignition/combustion events. The complex phenomena, which govern the gas flow patterns and mixture formation in the intake port and the combustion chamber are particularly analyzed during low-temperature engine cranking. Furthermore is discussed the influence of open and closed valve injection modes.

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.

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.

Turbocharged (TC) engines work at high Indicated Mean Effective Pressure (IMEP), resulting in high in-cylinder pressures and temperatures, improving thermal efficiency, but at the same time increasing the possibility of abnormal combustion events like knock and pre-ignition. To mitigate knocking conditions, engine control systems typically apply spark retard and/or mixture enrichment, which decrease indicated work and increase specific fuel consumption. Many recent studies have advocated Water Injection (WI) as an approach to replace or supplement existing knock mitigation techniques. Water reduces temperatures in the end gas zone due to its high latent heat of vaporization. Furthermore, water vapor acts as diluent in the combustion process. In this paper, the development of a novel closed-loop, model-based WI controller is discussed and critically analyzed.

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.

Due to the recent anti-pollution policies, the performance increase in Spark Ignition (SI) engines is currently under the focus of automotive manufacturers. This trend drives control systems designers to investigate accurate solutions and build more sophisticated algorithms to increase the efficiency of this kind of engines. The development of a control strategy is composed of several phases and steps, and the first part of such process is typically spent in defining and investigating the logic of the strategy. During this phase it is often useful to have a light engine simulator, which allows to have robust synthetic combustion data with a low calibration and computational effort. In the first part of this paper, a description of the control-oriented ANalytical Engine SIMulator (ANESIM) is carried out.