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Water management in PEMFC power generation systems is a key point to guarantee optimal performances and durability. It is known that a poor water management has a direct impact on PEMFC voltage, both in drying and flooding conditions: furthermore, water management entails phenomena from micro-scale, i.e., formation and water transport within membrane, to meso-scale, i.e., water capillary transport inside the GDL, up to the macro-scale, i.e., water droplet formation and removal from the GFC. Water transport mechanisms through the membrane are well known in literature, but typically a high computational burden is requested for their proper simulation. To deal with this issue, the authors have developed an analytical model for the water membrane content simulation as function of stack temperature and current density, for fast on-board monitoring and control purposes, with good fit with literature data.

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.

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.

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.

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.

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.

1 The Selective Catalytic reduction (SCR) using urea as reducing agent is currently regarded as the most promising after-treatment technology in order to comply with strict RDE targets for NOX and particulate in Diesel application. Model-based control strategies are promising to satisfy the demands of high NOX conversion efficiency and low tailpipe ammonia slip. This paper deals with the development of a control oriented model of a Cu-zeolite urea-SCR system for automotive Diesel engines. The model is intended to be used for the real-time urea-SCR management, depending on engine NOX emissions and ammonia storage. In order to ensure suitable computational demand for the on-board implementation, a reduced order one-state model of ammonia storage has been derived from a quasi-dimensional four-state model of the urea-SCR plant.

New gasoline engine design is highly influenced by CO2 and emission limits defined by legislations, the demand for real conditions fuel economy, higher torque, higher specific power and lower cost. To reach the requirements coming from the end-users and legislations, especially for SI engines, several technologies are available, such as downsizing, including turbocharging in combination with direct injection. These technologies allow to solve the main issues of gasoline engines in terms of efficiency and performance which are knocking, part-load losses, and thermal stress at high power conditions. Moreover, other possibilities are under evaluation to allow further steps of enhancement for the even more challenging requirements. However, the benefits and costs given by the mix of these technologies must be accurately evaluated by means of objective tools and procedures in order to choose among the best alternatives.

Road topography has a remarkable impact on vehicle fuel consumption for both passenger and heavy duty vehicles. In addition, erroneous or non-optimized scheduling of both velocity set-point and gear shifting may be detrimental for fuel consumption and performance. Recent technologies have made road data, such as elevation or slope, either available or measurable on board, thus making possible the exploitation of this additional information in innovative controllers. The aim of this paper is the development of a smart, fuel-economy oriented controller adapting cruising speed and engaged gear to current road load (i.e. local slope). Unlike traditional cruise controllers, the velocity set-point is not constant, but it is set by applying a mathematical transformation of the current slope, accounting for the mission time duration as well.

In the last years, the research effort of the automotive industry has been mainly focused on the reduction of CO2 and pollutants emissions. In this scenario, concepts such as the engines downsizing, stop/start systems as well as more costly full hybrid solutions and, more recently, Waste Heat Recovery technologies have been proposed. These latter include Thermo-Electric Generator (TEG), Organic Rankine Cycle (ORC) and Electric Turbo-Compound (ETC) that have been practically implemented on few heavy-duty applications but have not been proved yet as effective and affordable solutions for passenger cars. The paper deals with modeling of ORC power plant for simulation analyses aimed at evaluating the opportunities and challenges of its application for the waste heat recovery in a compact car, powered by a turbocharged SI engine.

Nowadays the high competition reached by the automotive market forces Original Equipment Manufacturers (OEMs) towards innovative solutions. Strict emission standards and fuel economy targets make the work hard to be accomplished. Therefore modern engines feature complex architecture and embed new devices for Exhaust Gas Recirculation (EGR), turbocharging (e.g. multi-stage compressors), gas after-treatment (e.g. the Selective Catalyst Reduction (SCR)) and fuel injection (either high or low pressure). In this context the Engine Management System (EMS) plays a fundamental role to optimize engine operation. The paper deals with fuel spray and combustion simulation by a multi-zone phenomenological model aimed at the steady-state optimal tuning of the injection pattern.

The emissions limits of CO2 for vehicles are becoming more stringent with the aim of reducing greenhouse gas emissions and improve fuel economy. The New European Driving Cycle (NEDC) is adopted to measure emissions for all new internal combustion engines in the European Union, and it is performed on cold vehicle, starting at a temperature of 22°C ± 2°C. Consequently, the cold-start efficiency of internal combustion engine is becoming of predominant interest. Since at cold start the lubricant oil viscosity is higher than at the target operating temperature, the consequently higher energy losses due to increased frictions can substantially affect the emission cycle results in terms of fuel consumption and CO2 emissions. A suitable thermal management system, such as an exhaust-to-oil heat exchanger, could help to raise the oil temperature more quickly.

International regulations continuously restrict the standards for the exhaust emissions from automotive engines. In order to comply with these requirements, innovative control and diagnosis systems are needed. In this scenario the application of methodologies based on the in-cylinder pressure measurement finds widespread applications. Indeed, almost all engine thermodynamic variables useful for either control or diagnosis can be derived from the in-cylinder pressure. Apart for improving the control accuracy, the availability of the in-cylinder pressure signal might also allow reducing the number of existing sensors on-board, thus lowering the equipment costs and the engine wiring complexity. The paper focuses on the detection of the engine thermal state, which is fundamental to achieve suitable control of engine combustion and after-treatment devices.

This paper deals with modeling and analysis of the integration of ThermoElectric generators (TEG) into a conventional vehicle, specifically aimed at recovering waste heat from exhaust gases. The model is based on existing and commercial thermoelectric materials, specifically Bi2Te3, having ZTs not exceeding 1 and efficiency below 5%, but a trade-off between cost and performance that would be acceptable for automotive applications. TEGs operate on the principle of thermoelectric energy conversion via Seebeck effect, utilizing thermal gradients to generate electric current, with exhaust gases at the hot side and coolant at the cold side. In the simulated configuration the TEG converters are interfaced with the battery/alternator supporting the operation of the vehicle, reducing the energy consumption due to electrical accessories and HVAC.

In the last years the automotive industry has been involved in the development and implementation of CO2 reducing concepts such as the engines downsizing, stop/start systems as well as more costly full hybrid solutions and, more recently, waste heat recovery technologies. These latter include ThermoElectric Generator (TEG), Rankine cycle and Electric Turbo Compound (ETC) that have been practically implemented on few heavy-duty application but have not been proved yet as effective and affordable solutions for the automotive industry. The paper deals with the analysis of opportunities and challenges of the Electric Turbo Compound for automotive light-duty engines. In the ETC concept the turbine-compressor shaft is connected to an electric machine, which can work either as generator or motor. In the former case the power can satisfy the vehicle electrical demand to drive the auxiliaries or stored in the batteries.

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 Euro 6 compliancy for light and medium duty trucks and bigger passenger cars. Moreover, new more stringent emission regulations and homologation cycles are being proposed for Euro 6c stage and they are scheduled to be applied by the end of 2017. In this context, the interest for SCR technology and its application on light-duty trucks is growing, with a special focus on its potential benefit in term of fuel consumption reduction, thanks to combustion optimization. Nevertheless, the need to warm up the exhaust gas line, to meet the required NOx conversion efficiency, remains an issue for such kind of applications.

While the Diesel Particulate Filter (DPF) is actually a quasi-standard equipment in the European Diesel passenger cars market, an interesting solution to fulfill NOx emission limits for the next EU 6 legislation is the application of a Selective Catalytic Reduction (SCR) system on the exhaust line, to drastically reduce NOx emissions. In this context, one of the main issues is the performance of the SCR system during cold start and warm up phases of the engine. The exhaust temperature is too low to allow thermal activation of the reactor and, consequently, to promote high conversion efficiency and significant NOx concentration reduction. This is increasingly evident the smaller the engine displacement, because of its lower exhaust system temperature (reduced gross power while producing the same net power, i.e., higher efficiency).