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With the aim to further reduce and limit pollutant emissions and fuel consumption towards carbon neutrality, researchers and automotive manufacturers have been studying new combustion technologies, such as low temperature combustions, which provide an efficient combustion with low pollutant emissions. Despite innovative combustion techniques, such as Homogeneous charge compression ignition (HCCI) and Gasoline compression ignition (GCI), proved to reduce pollutant emissions and increase efficiency of internal combustion engines, their large-scale deployment has been limited by problems in combustion management and stability. In fact, the challenge related to these innovative combustion techniques consists in the development of new control strategies and new calibration methodologies, which allow to limit their combustion instability.

This work aims at addressing the challenge of reconciling the surge in road transportation with the need to reduce CO2 emissions. The research particularly focuses on exploring the potential of fuel cell technology in long-distance road haulage, which is currently a major solution proposed by relevant manufacturers to get zero local emissions and an increased total payload. Specifically, a methodology is applied to enable rapid and accurate identification of techno-economically effective fuel cell hybrid heavy-duty vehicle (FCH2DV) configurations. This is possible by performing model-based co-design of FCH2DV powertrain and related control strategies. Through the algorithm, it is possible to perform parametric scenario analysis to better understand the prospects of this technology in the decarbonization path of the heavy-duty transportation sector, changing in an easy way all the parameters involved.

The last environmental regulations on passenger vehicles’ emissions harden constraints on designing powertrains. A promising solution consists in vehicle electrification leading to hybrid configurations: the tank-to-wheel pollutant emissions can be drastically reduced combining features of typical battery electric vehicles adding an Internal Combustion Engine (ICE) controlled as a Range Extender (REX). Furthermore, HC and CO/CO2 emissions can be avoided using green hydrogen as fuel for the ICE; moreover, in absence of a mechanical coupling between REX and wheels the best operating conditions in terms of maximum ICE efficiency may be easily achieved. In this work, a light quadricycle (EU L6e, classification) series hybrid vehicle with four in-wheel motors is studied for the application of a range extender system.

Due to the greater need to reduce exhaust emissions of harmful gases (GHG, NOx, PM, etc.), to promote the decarbonisation process and to overcome the drawbacks of electric vehicles (low range, high cost, impact of electricity production on CO2 emissions…), the hybrid-electric vehicles are still considered as the more feasible path through sustainable mobility. However, one of the main tasks to be accomplished to get maximum benefit from hybrid-electric powertrain is the management of the energy flows between the different power sources, namely internal combustion engine, electric machine(s) and battery pack. In this paper a methodology for the experimental testing of HEVs energy management strategies at the engine test bed is presented. The experimental set-up consists in an eddy-current dyno and a light-duty common-rail Diesel engine.

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.

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.

Compression-ignited engines are still considered the most efficient and reliable technology for automotive applications. However, current and future emission regulations, which severely limit the production of NOx, particulate matter and CO2, hinder the use of diesel-like fuels. As a matter of fact, the spontaneous ignition of directly-injected Diesel leads to a combustion process that is heterogeneous by nature, therefore characterized by the simultaneous production of particulate matter and NOx. In this scenario, several innovative combustion techniques have been investigated over the past years, the goal being to benefit from the high thermal efficiency of compression-ignited engines, which results primarily from high Compression Ratio and lean and unthrottled operation, while simultaneously mitigating the amount of pollutant emissions.

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.

In the global quest for preventing fossil fuel depletion and reducing air pollution, hybridization plays a fundamental role to achieve cleaner and more fuel-efficient automotive propulsion systems. While hybrid powertrains offer many opportunities, they also present new developmental challenges. Due to the many variants and possible architectures, development issues, such as the definition of powertrain concepts and the optimization of operating strategies, are becoming more and more important. The paper presents model-based fuel economy analyses of different hybrid vehicle configurations, depending on the position of the electric motor generator (EMG). The analyses are intended to support the design of powertrain architecture and the components sizing, depending on the driving scenario, with the aim of reducing fuel consumption and CO2 emissions.

Diesel engines are attractive thanks to good performance in terms of fuel consumption, drivability, power output and efficiency. Nevertheless in the last years, increasing restrictions have been imposed to particulate emissions, concerning both mass (PM) and number (PN). Different technologies have been proposed to meet emissions standards and the wall-flow Diesel Particulate Filter (DPF) is currently the most common after-treatment system used to trap PM from the exhaust gases. This technology exhibits good features such that it can be regenerated to remove any accumulation of PM. However, this process involves oxidation of the filtered PM at a high temperature through after and post fuel injection strategies, which results in an increase of fuel consumption and may lead to physical damages of the filter in the long term. This work deals with the experimental testing of a catalytic silicon carbide (SiC) wall flow DPF, aiming at decreasing the soot oxidation temperature.

Nowadays, compression-ignited engines are considered the most efficient and reliable technology for automotive applications. However, mainly due to the current emission regulations, that require increasingly stringent reductions of NOx and particulate matter, the use of diesel-like fuels is becoming a critical issue. For this reason, a large amount of research and experimentation is being carried out to investigate innovative combustion techniques suitable to simultaneously mitigate the production of NOx and soot, while improving engine efficiency. In this scenario, the combined use of compression-ignited engines and gasoline-like fuels proved to be very promising, especially in case the fuel is directly-injected in the combustion chamber at high pressure. The presented study analyzes the combustion process produced by the direct injection of small amounts of gasoline in a compression-ignited light-duty engine.

Water Injection (WI) has become a key technology for increasing combustion efficiency in modern GDI turbocharged engines. In fact, the addition of water mitigates significantly the occurrence of knock, reduces exhaust gas temperatures, and opens the possibility to reach optimum heat release phasing even at high load. This work presents the latest development of a model-based WI controller, and its experimental validation on a GDI TC engine. The controller is based on a novel approach that involves an analytic combustion model to define the spark advance (SA) required to reach a combustion phase target, considering injected water mass effects. The calibration and experimental validation of the proposed controller is shown in detail in the paper.

Conventional electric vehicles adopt either single-speed transmissions or direct drive architecture in order to reduce cost, losses and mass. However, the integration of optimized multiple-speed transmissions is considered as a feasible method to enhance EVs performances, (i.e. top speed, acceleration and grade climbing), improving powertrain efficiency, saving battery energy and reducing customer costs. Perfectly in line with these objectives, this paper presents a patented fully integrated electric traction system, as scalable solution for electrifying light duty passenger and commercial vehicles (1.5-4.2 tons), with a focus on minibuses (<20 seats). The adoption of high-speed motor coupled to multiple-speed transmission offers the possibility of a relevant efficiency improvement, a 50% volume reduction with respect to a traditional transmission, superior output torque and power density.

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.

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.

1 The wall-flow Diesel Particulate Filter (DPF) is currently the most common after-treatment system used to meet the particulate emissions regulations for automotive engines. Today’s technology shows the best balance between filtration efficiency and back-pressure in the engine exhaust pipe. During the accumulation phase the pressure drop across the filter increases, thus requiring periodic regeneration of the DPF through after and post fuel injection strategies. This paper deals with the development of a control oriented model of a catalytic silicon carbide (SiC) wall flow DPFs with CuFe2O4 loading for automotive Diesel engines. The model is intended to be used for the real-time management of the regeneration process, depending on back-pressure and thermal state.

This paper summarizes the main studies carried out by the authors for the development of indexes for remote combustion sensing applicable to different combustion types, i.e. conventional gasoline and diesel combustions, diesel PCCI and dual fuel gasoline-diesel RCCI. It is well-known that the continuous development of modern Internal Combustion Engine (ICE) management systems is mainly aimed at complying with upcoming increasingly stringent regulations throughout the world, both for pollutants and CO2 emissions. Performing an efficient combustion control is crucial for efficiency increase and pollutant emissions reduction. Over the past years, the authors of this paper have developed several techniques to estimate the most important combustion indexes for combustion control, without using additional cylinder pressure sensors but only using the engine speed sensor (always available on board) and accelerometers (usually available on-board for gasoline engines).

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.

The wall-flow Diesel Particulate Filter (DPF) is currently the most common after-treatment system used to meet the particulate emission limits imposed by government regulations. Today’s technology shows the best balance between filtration efficiency and back-pressure in the engine exhaust pipe. Conventional filters consist in alternately plugged parallel square channels, so that the exhaust gases flow through the porous inner walls leading to particles trapping. During the accumulation phase the pressure drop across the filter increases, thus requiring periodic regeneration of the DPF through after and post fuel injection strategies. This paper deals with the experimental testing of a catalytic silicon carbide (SiC) wall flow DPFs with CuFe2O4 loading. The filter was built following an optimized procedure based on a preliminary controlled chemical erosion of the SiC porous structure.

In the last few years, several studies have proved the benefits of exploiting information about the road topography ahead of the vehicle to adapt vehicle cruising for fuel consumption reduction. Recent technologies have brought on-board more road information enabling the optimization of the driving profile for fuel economy improvement. In the present paper, a cruise controller able to lowering vehicle fuel consumption taking into account the characteristics of the road the vehicle is traveling through is presented. The velocity profile is obtained by minimizing via discrete dynamic programming the energy spent to move the vehicle. In order to further enhance vehicle fuel efficiency, also the gear shifting schedule is optimized, allowing to avoid useless gear shifts and choose the most suitable gear to match current road load and keeping the engine in its maximum efficiency range. Despite the optimality of the solution provided, dynamic programming entails high computational time.