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Nowadays, green hydrogen can play a crucial role in a successful clean energy transition, thus reaching net zero emissions in the transport sector. Moreover, hydrogen exploitation in internal combustion engines is favoured by its suitable combustion properties and quasi-zero harmful emissions. High flame speeds enable a lean combustion approach, which provides high efficiency and reduces NOx emissions. However, high air flow rates are required to achieve the load levels typical of heavy-duty applications. In this framework, the present study aims to investigate the required boosting system of a 6-cylinder, 13-liter heavy-duty spark ignition engine through 1D numerical simulation. A comparison among various architectures of the turbocharging system and the size of each component is presented, thus highlighting limitations and potentialities of each architecture and providing important insights for the selection of the best turbocharging system.

The engine acoustic character has always represented the product DNA, owing to its strong correlation with in-cylinder pressure gradient, components design and perceived quality. Best practice for engine acoustic characterization requires the employment of a hemi-anechoic chamber, a significant number of sensors and special acoustic insulation for engine ancillaries and transmission. This process is highly demanding in terms of cost and time due to multiple engine working points to be tested and consequent data post-processing. Since Neural Networks potentially predicting capabilities are apparently un-exploited in this research field, the following paper provides a tool able to acoustically estimate engine performance, processing system inputs (e.g. Injected Fuel, Rail Pressure) thanks to the employment of Multi Layer Perceptron (MLP, a feed forward Network working in stationary points).

Polymer electrolyte membrane (PEM) fuel cells will play a crucial role in the decarbonization of the transport sector, in particular for heavy duty applications. However, performance and durability of PEMFC stacks is still a concern especially when operated under high power density conditions, as required in order to improve the compactness and to reduce the cost of the system. In this context, the optimization of the geometry of hydrogen and air distributors represents a key factor to improve the distribution of the reactants on the active surface, in order to guarantee a proper water management and avoiding membrane dehydration.

Compression ignition engine-based transportation is nowadays looking for cleaner combustion solutions. Among them, ducted fuel injection (DFI) is emerging as a cutting-edge technology due to its potential to drastically curtail engine-out soot emissions. Although the DFI capability to abate soot formation has been demonstrated both in constant-volume and optical engine conditions, its optimization and understanding is still needed for its exploitation on series production engines. For this purpose, computational fluid dynamics (CFD) coupled with low-cost turbulence models, like RANS, can be a powerful tool, especially in the industrial context. However, it is often challenging to obtain reliable RANS-based CFD simulations, especially due to the high dependence of the various state-of-the-art turbulence models on the case study.

Ammonia is a new type of carbon-free fuel with low cost, clean and safe. The research and application of zero-carbon fuel internal combustion engines has become the mainstream of future development. However, there still exist problems should be solved in the application of ammonia fuel. Due to the lower flame laminar speed and higher ignition temperature, ammonia may have unstable combustion phenomena. In this work, the characteristics of ammonia combustion have been investigated, based on controllable thermal activated atmosphere burner. The ignition delay has been used to analyze the ammonia combustion characteristics. With the increase in co-flow temperature, the ignition delay of ammonia/air has an obvious decline. In order to investigate the emission characteristics of ammonia, CHEMKIN is used to validate the different chemical reaction mechanisms and analyse the ammonia emissions.

Nowadays numerical simulations play a major role in the development of future sustainable powertrain thanks to their capability of investigating a wide spectrum of innovative technologies with times and costs significantly lower than a campaign of experimental tests. In such a framework, this paper aims to assess the predictive capabilities of an 1D-CFD engine model developed to support the design and the calibration of the innovative highly efficient spark ignition engine of the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) EU H2020 project. As a matter of fact, the availability of a reliable simulation platform is crucial to achieve the project target of 47% peak indicating efficiency, by synergistically exploiting the combination of innovative in-cylinder charge motion, Miller cycle with high compression ratio, lean mixture with cooled Exhaust Gas Recirculation (EGR) and electrified turbocharger.

The demand of game-changing technologies to improve efficiency and abate emissions of heavy-duty trucks and off-road vehicles promoted the development of novel engine concepts. The Recuperated Split-Cycle (R-SC) engine allows to recover the exhaust gases energy into the air intake by separating the compression and combustion stages into two different but connected cylinders: the compressor and expander, respectively. The result is a potential increase of the engine thermal efficiency. Accordingly, the 3D-computational fluid dynamics (CFD) modelling of the gas exchange process and the combustion evolution inside the expander becomes essential to control and optimize the R-SC engine concept. This work aims to address the most challenging numerical aspects encountered in a 3D numerical simulation of an R-SC engine.

The role of numerical simulations in the development of innovative and sustainable powertrains is constantly growing thanks to their capabilities to significantly reduce the calibration efforts and to point out potential synergies among different technologies. In such a framework, this paper describes the development of a fully physical 1D-CFD engine model to support the calibration of the highly efficient spark ignition engine of the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) EU H2020 project. The availability of a reliable simulation platform is essential to effectively exploit the combination of the several features introduced to achieve the project target of 47% peak gross indicated efficiency, such as SwumbleTM in-cylinder charge motion, Miller cycle combined with high Compression Ratio (CR), lean mixture exploiting cooled low pressure Exhaust Gas Recirculation (EGR) and electrified turbocharging.

In a military off-road vehicle, generally designed to operate in an aggressive operating environment, the typical comfort requirements for trucks and passenger cars are revised for robustness, safety and security. An example is the cabin space optimisation to provide easy access to many types of equipment required on-board. In this field, racks hung to the cabin chassis are generally used to support several electronic systems, like radios. The dynamic loads on a rack can reach high values in the operative conditions of a military vehicle. Rack failures should be prevented for the safety of driver, crew and load and the successful execution of a mission. Therefore, dynamic and durability tests of these components, including the fixtures to the vehicle, are required.

Fuel cells are considered one of the promising technologies as possible replacement of Internal Combustion Engine (ICE) for the transportation sector due to their high efficiency, ultra-low (or zero) emissions and for the higher drive range. The Membrane Electrode Assembly (MEA) is what mainly influences the Fuel Cell FC performance, durability, and cost. In PEMFC the proton conductivity of the membrane is a function of the humidification level of the FC membrane, hence the importance of keeping the membrane properly humidified to achieve the best possible fuel cell performance. To have the optimal water content inside the fuel cell’s membrane several strategies could be adopted, dealing with the use of external device (such as membrane humidifier) or to adopt an optimal set of parameters (gas flow rate and temperature for example) to use the water produced at fuel cell cathode as humidity source. The aim of this paper is to study the behavior of a FC vehicle humidification system.

The continuous tightening of CO2 emission targets along with the introduction of Real Driving Emissions (RDE) tests make Water Injection (WI) one of the most promising solutions to improve efficiency, enhance performance and reduce emissions of turbocharged high-performance Spark Ignition engines. This technology, by reducing local in-cylinder mixture temperature, enables higher compression ratios, optimal spark timing and stoichiometric combustion over the entire engine operating range. This research activity, therefore, aims to assess the benefits in terms of CO2 emission reduction of a Port Water Injection (PWI) system integrated in a Downsized Turbocharged Direct Injection Spark Ignition (T-DISI) Engine. In this regard, a 1D-CFD model of the engine capable to predict the impact of the water content on both the combustion process and the knock likelihood was firstly developed.

Despite the legislation targets set by several governments of a full electrification of new light-duty vehicle fleets by 2035, the development of innovative, environmental-friendly Internal Combustion Engines (ICEs) is still crucial to be on track toward the complete decarbonization of on road-mobility of the future. In such a framework, the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) project aims at developing a C SUV-class plug-in hybrid (P0/P4) vehicle demonstrator capable to achieve a -10% fuel consumption reduction with respect to current EU6 vehicle while complying with upcoming EU7 pollutant emissions limits. Such ambitious targets will require the optimization of the whole engine system, exploiting the possible synergies among the combustion, the aftertreatment and the exhaust waste heat recovery systems.

The ongoing global demand for greater energy efficiency plays an essential role in the automotive industry, as the focus is moving from ICEs to hybrid (HEVs) and electric (EVs) vehicles. New virtual methodologies are necessary to reduce the development effort of these technologies. In this context, the thermal management of the vehicle high voltage battery pack is becoming increasingly important, with significant impact on the vehicle’s range in different environmental scenarios. In this paper, an advanced method is proposed to compute 3D temperature distribution of the cells of a high voltage battery pack for Plug-in Hybrid (PHEV) or full electric (EV) applications. The thermal FE model of a complete PHEV vehicle was integrated with an electrical NTG equivalent circuit model of the HV battery to compute the heat loads of the cells.

In the last years, the design in the automotive sector is mainly led by emission reduction and circular economy. To satisfy the first perspective, composites materials are being increasingly used to produce lightweight structural and semi-structural components. However, the automotive mass production arises the problem of the end-of-life disposal of the vehicle and the reduction of the wastes environmental impact. The circular economy of the composite materials has therefore become a challenge of primary importance for car manufacturers and tier 1 suppliers. It is necessary to pursue a different economic model, combining traditional raw materials with the intensive use of materials from recycling processes. New technologies are being studied and developed concerning the reuse of in-line production scraps with out-of-autoclave process that makes them desirable for high production rate applications.

As technology evolves, the number of sensors and available data on vehicles grow exponentially. In this context, it is essential to use sensors for monitoring key components, increasing safety and reliability, and gathering data useful for mechanical dimensioning and control systems. This paper presents an application of strain-gauged bolts on brake calipers fixation of two electric vehicles. With this approach it was possible to evaluate the loads applied to the brake pads fixation zone and correlate them with braking behavior, therefore gaining insights on braking conditions and system state for an improved braking function control. The goal of the study is analyzing the strengths and limitations of the method and proposing developments to deploy it in real applications. This is particularly important and novel for electric vehicles, where powertrains can create positive/negative torques and generate complex interactions with braking system.

JUNO is an urban concept vehicle (developed at the Politecnico of Torino), equipped by an ethanol combustion engine, designed to obtain low consumptions and reduced environmental impact. For these goals the main requirements that were considered during the designing process were mass reduction and aerodynamic optimization, at first on the shape of the car body and then, thanks to add-on devices. JUNO’s aerodynamic development follows a defined workflow: geometry definition and modelling, CFD simulations and analysis, and finally geometry changes and CFD new verification. In this paper the results of the CFD simulations (using STARCCM+ and RANS k-ε) with a corresponding 1/1 scale wind tunnel tests made using the real vehicle. Particularly, the results in term of: total drag coefficient (Cx), total lift coefficient (Cz), the total pressure in the side and rear analyzing twenty different aerodynamics configurations made up of different combination of some aerodynamics add-on devices.

To fulfill stringent emission legislation requirements, it is essential to understand the relation between aging processes of the exhaust gas aftertreatment system (ATS) and its performance. The Stage V compliant heavy-duty non-road aftertreatment system, which was used in this study, is comprised of a diesel oxidation catalyst (DOC) placed directly after the engine, followed by a particulate filter with a selective catalytic reduction (SCR) active coating (SCRoF) and is completed by an SCR-coated substrate combined with an NH3 oxidation catalyst. Each of the ATS components has to work in synergy and interact with each other to fulfill the emission legislation requirements. During vehicle operation, the ATS is exposed to various chemical and physical factors, which deteriorate its performance over its lifetime. In this work, the accelerated aging methodology is presented.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional liquid fuels to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

Dimethyl ether (DME) represents a promising fuel for heavy-duty engines thanks to its high cetane number, volatility, absence of aromatics, reduced tank-to-wheel CO2 emissions compared to Diesel fuel and the possibility to be produced from renewable energy sources. However, optimization of compression-ignition engines fueled with DME requires suitable computational tools to design dedicated injection and combustion systems: reduced injection pressures and increased nozzle diameters are expected compared to conventional Diesel engines, which influences both the air-fuel mixing and the combustion process. This work intends to evaluate the validity of two different combustion models for the prediction of performance and pollutant emissions in compression-ignition engines operating with DME. The first one is the Representative Interactive Flamelet while the second is the Approximated Diffusive Flamelet.

In the intermediate stage towards zero-emissions, use of methane-hydrogen blends in spark ignition (SI) engines could represent an attractive application. The present work investigated the relevance of empirical base rules for choosing maximum brake torque spark timing settings when using methane-hydrogen blends. A 0D/1D model was used for investigating the optimized ignition for maximizing engine output. Calibration was performed by using in-cylinder pressure data recorded on a methane fueled small size SI engine for two-wheel applications. After adaptations of the model such as valves timing, for rendering it more representative for power generation applications, the investigation was focused on how MBT spark advance was correlated to the 50% mass fraction burned mark (CA50) and peak pressure location. The fact that they were optimized for methane was found to be essential only for high concentrations of hydrogen.