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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.

This works presents a Reinforcement Learning (RL) agent to implement a Cooperative Adaptive Cruise Control (CACC) system that simultaneously enhances energy efficiency and comfort, while also ensuring string stability. CACC systems are a new generation of ACC which systems rely on the communication of the so-called ego-vehicle with other vehicles and infrastructure using V2V and/or V2X connectivity. This enables the availability of robust information about the environment thanks to the exchange of information, rather than their estimation or enabling some redundancy of data. CACC systems have the potential to overcome one typical issue that arises with regular ACC, that is the lack of string stability. String stability is the ability of the ACC of a vehicle to avoid unnecessary fluctuations in speed that can cause traffic jams, dampening these oscillations along the vehicle string rather than amplifying them.

In the last few years, the number of Advanced Driver Assistance Systems (ADAS) on road vehicles has been increased with the aim of dramatically reducing road accidents. Therefore, the OEMs need to integrate and test these systems, to comply with the safety regulations. To lower the development cost, instead of experimental testing, many virtual simulation scenarios need to be tested for ADAS validation. The classic multibody vehicle approach, normally used to design and optimize vehicle dynamics performance, is not always suitable to cope with these new tasks; therefore, real-time lumped-parameter vehicle models implementation becomes more and more necessary. This paper aims at providing a methodology to convert experimentally validated light commercial vehicles (LCV) multibody models (MBM) into real-time lumped-parameter models (RTM).

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.

Battery Electric Vehicles (BEVs) and Hybrid Electric Vehicles (HEVs) are becoming relevant in the transportation sector, and it is therefore of utmost importance to find a solution to allow batteries to work safely and in a correct temperature range in which performance degradation and/or thermal runaway do not occur. For this purpose, a Battery Thermal Management System (BTMS) is required to ensure the correct operation of the battery pack. The design and control of an efficient BTMS is a complex task, in which multiple technical fields are involved. The paper mainly focuses on the thermal problems affecting the BTMS and sets two main goals: 1) to provide a comparison of two possible BTMS solutions, analyzing constraints and thermal performance for the design task; 2) to present a battery thermal 1D model able to describe the battery module behavior in real-time application to be implemented in a BMS control.

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.

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.

Flow noise produced by the turbulent motion of the exhaust gases is one of the main contributions to the noise generation for a heavy-duty vehicle. The exhaust system has therefore to be optimized since the early stages of the design to improve the engine’s Noise Vibration Harshness (NVH) performance and to comply with legislation noise limits. In this context, the availability of reliable Computational Aero-Acoustics (CAA) methodologies is crucial to assess the noise mitigation potential of different exhaust system designs. In the present work, a characterization of the sound generation in a heavy-duty exhaust system was carried out evaluating the noise attenuation potential of a design modification, by means of a hybrid CAA methodology.

Worldwide regulations concerning noise emissions of road vehicles are constantly demanding further reductions of acoustic emissions, which are considered a major environmental health concern in several countries. Among the different sources contributing to noise generation in vehicles equipped with internal combustion engines, exhaust flow noise is one of the most significant, being generated by turbulence development in the exhaust gases, and robust and reliable numerical methodologies for its prediction in early design phases are currently still needed. To this extent, Computational Aero-Acoustics (CAA) can be considered a valuable approach to characterize the physical mechanisms leading to flow noise generation and its propagation, and it could therefore be used to support exhaust system development prior to the execution of experimental testing campaigns.

Fuel injection is a key process influencing the performance of Gasoline Direct Injection (GDI) Engines. Injecting fuel at elevated temperature can initiate flash boiling which can lead to faster breakup, reduced penetration, and increased spray-cone angle. Thus, it impacts engine efficiency in terms of combustion quality, CO2, NOx and soot emission levels. This research deals with modelling of flash boiling processes occurring in gasoline fuel injectors. The flashing mass transfer rate is modelled by the advanced Hertz-Knudsen model considering the deviation from the thermodynamic-equilibrium conditions. The effect of nucleation-site density and its variation with degree of superheat is studied. The model is validated against benchmark test cases and a substantiated comparison with experiment is achieved.

A comprehensive experimental and numerical analysis of two state-of-the-art diesel AfterTreatment Systems (ATS) for automotive applications is presented in this work. Both systems, designed to fulfill Euro 6 emissions regulations standards, consist of a closed-coupled Diesel Oxidation Catalyst (DOC) followed by a Selective Catalytic Reduction (SCR) catalyst coated on a Diesel Particulate Filter (DPF), also known as SCR on Filter (SCRoF or SCRF). While the two systems feature the same Urea Water Solution (UWS) injector, major differences could be observed in the UWS mixing device, which is placed upstream of the SCRoF, whose design represents a crucial challenge due to the severe flow uniformity and compact packaging requirements.

In the context of today’s and future legislative requirements for NOx and soot particle emissions as well as today’s market trends for further efficiency gains in gasoline engines, computational fluid dynamics (CFD) models need to further improve their intrinsic predictive capability to fulfill OEM needs towards the future. Improving fuel chemistry modelling, knock predictions and the modelling of the interaction between the chemistry and turbulent flow are three key challenges to improve the predictivity of CFD simulations of Spark-Ignited (SI) engines. The Flamelet Generated Manifold (FGM) combustion modelling approach addresses these challenges. By using chemistry pre-tabulation technologies, today’s most detailed fuel chemistry models can be included in the CFD simulation. This allows a much more refined description of auto-ignition delays for knock as well as radical concentrations which feed into emission models, at comparable or even reduced overall CFD run-time.

In contrast to the well-established “standard” log-law wall function, the analytical wall function (AWF) as an advanced modelling approach has not been extensively used in the industrial computational fluid dynamics (CFD) applications. As the model was originally developed aiming at computations on relatively coarse meshes, potential stability issues may arise due to the pressure-gradient sensitivity if employing locally inappropriate mesh layers, typically associated with the complex geometry details. This work evaluates performance of the thermal AWF, as proposed by Suga [4], in conjunction with the main flow field computed employing the k-ζ-f turbulence model and the hybrid wall treatment (denoted as AWF-e) within the Reynolds-averaged Navier-Stokes (RANS) framework.

In this work, a methodology for building and calibrating the kinetic scheme for the 1D CFD model of a zone-coated automotive Diesel Oxidation Catalyst (DOC) by means of a Genetic Algorithm (GA) approach is presented. The methodology consists of a preliminary experimental activity followed by a modelling, optimization and validation process. The tested aftertreatment component presents zone coating, with the front brick side covered with Zeolites in order to ensure hydrocarbons trapping at low temperature, and Platinum Group Metal (PGM), while the rear brick side presents an alumina washcoat with a different PGM loading. Reactor scale samples representative of each coating zone were tested on a Synthetic Gas Bench (SGB), to fully characterize the component’s behavior in terms of Light-off and hydrocarbons (HC) storage for a wide range of inlet feed compositions and temperatures, representative of engine-out conditions.

The clutch is that mechanical part located in an internal combustion engine vehicle which allows the torque transmission from the shaft to the wheels, permitting at the same time gear shifting and supporting engine revolutions while the car is idling. This component exploits friction as working principle, therefore heat generation is in its own nature. The comprehension of all the critical issues related to thermal emission, and also of the principal physical parameters driving the phenomena are a must in design phases. The subject of this paper is the elaboration of an accurate, but also easy to use and easily replicable, methodology to simulate thermal behavior of a clutch operating inside its usual environment. The present methodology allows to prevent corrective actions in the last phase of the projects (real testing), such as changes in gear ratios, that likely worsen CO2 emissions, permitting to achieve the wished thermal performance of the clutch avoiding late changes.

Automotive manufacturers are facing stronger and stronger pressure to optimize all aspects related to fuel consumption of cars, and aerodynamic drag makes no exception, due to increasing government enforcing rules for the reduction of the emissions and the increasing influence of aerodynamic performance on fuel consumption with WLTC and RDE driving cycles. Nowadays, CFD simulation is a common tool across automotive industries for the assessment and the optimization of vehicle resistance in the design phase. The full power of these numerical methods of studying many design variants in advance of experimental testing, however, can be fully exploited when coupled with optimization techniques, always keeping into account constraints and aesthetical demands. On the other hand, a massive use of CFD optimization can lead to unaffordable computational efforts or a limitation of the design exploration space.

Development trends in modern common rail fuel injection systems (FIS) show dramatically increasing capabilities in terms of optimization of the fuel injection strategy through a constantly increasing number of injection events per engine cycle as well as through the modulation and shaping of the injection rate. In order to fully exploit the potential of the abovementioned fuel injection strategy optimization, numerical simulation can play a fundamental role by allowing the creation of a kind of a virtual test rig, where the input is the fuel injection rate and the optimization targets are the combustion outputs, such as the burn rate, the pollutant emissions, and the combustion noise (CN).

Turbulent combustion modeling in a RANS or LES context imposes the challenge of closing the chemical reaction rate on the sub-grid level. Such turbulent models have as their two main ingredients sources from chemical reactions and turbulence-chemistry interaction. The various combustion models then differ mainly by how the chemistry is calculated (level of detail, canonical flame model) and on the other hand how turbulence is assumed to affect the reaction rate on the sub-grid level (TCI - turbulence-chemistry interaction). In this work, an advanced combustion model based on tabulated chemistry is applied for 3D CFD (computational fluid dynamics) modeling of Diesel engine cases. The combustion model is based on the FGM (Flamelet Generated Manifold) chemistry reduction technique. The underlying chemistry tabulation process uses auto-ignition trajectories of homogeneous fuel/air mixtures, which are computed with detailed chemical reaction mechanisms.

A TGDI (turbocharged gasoline direct injection) engine is developed to realize both excellent fuel economy and high dynamic performance to guarantee fun-to-drive. In order to achieve this target, it is of great importance to develop a superior combustion system for the target engine. In this study, CFD simulation analysis, steady flow test and transparent engine test investigation are extensively conducted to ensure efficient and effective design. One dimensional thermodynamic simulation is firstly conducted to optimize controlling parameters for each representative engine operating condition, and the results serve as the input and boundary condition for the subsequent Three-dimensional CFD simulation. 3D CFD simulation is carried out to guide intake port design, which is then measured and verified on steady flow test bench.