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Thermal comfort in the vehicle cabin environment is an important factor for passengers of both internal combustion engines and electric vehicles. Heating, Ventilation and Air Conditioning (HVAC) is a critical system for electric vehicles (EVs) as it is the second most power consumer after electric motor. Novel solutions dedicated to EV, including thermoelectric air conditioning (AC) modules, vapor compression refrigeration (VCR), cycle positive temperature coefficient (PTC) heater as well as heat pumps (HP), are being investigated to maintain a stable and comfortable interior environment under hot and cold weather conditions. At present, the mostly dominated automotive AC systems are those using R134a refrigerant characterized by high global warming potential. Therefore, an innovative and ecofriendly AC system design still must be developed to supply sufficient cooling or heating capacity while minimizing the influence of the AC system on driving ranges and environmental performance.

In the recent past, an always increasing attention have been addressed to the definition and optimization of the HVAC system for fully electric vehicles. The new vehicle layouts and the different operating temperatures of the whole powertrain ask for a re-thinking of the HVAC concept for the modern architectures. In this ballpark, the possibility to deal with a compact and efficient apparatus without moving parts and capable to provide both cold and hot fluxes is really attractive. This is the reason why this work deals with the design and optimization of a vortex tube for automotive applications. Such a component, in fact, is capable to separate a highly swirled flow in two different branches, a cold one and a hot one (one inlet - two outlets). The balance in between the two obtained mass flows can be simply realized via ruling the backpressure at the hot side, with keeping constant the cold one.

Turbulence modeling is a key aspect for the accurate simulation of ICE related fluid flow phenomena. RANS-based turbulence closures are still the preferred modeling framework among industrial users, mainly because they are robust, not much demanding in terms of computational resources and capable to extract ensemble-averaged information on a complete engine cycle without the need for multiple cycles simulation. On the other hand, LES-like approaches are gaining popularity in recent years due to their inherent scale-resolving nature, which allows the detailed modeling of unsteady flow features such as cycle-to-cycle variations in a DI engine. An LES requires however a large number of simulated engine cycles to extract reliable flow statistics, which coupled to the higher spatial and temporal resolution compared to RANS still poses some limits to a wider application of such methodology on realistic engine geometries.

The interest in Unsteady Reynolds-Averaged Navier-Stokes (URANS)/Large Eddy Simulation (LES) hybrids, for the simulation of turbulent flows in Internal Combustion Engines (ICE), is consistently growing. An increasing number of applications can be found in the specialized literature for the past few years, including both seamless and zonal hybrid formulations. Following this trend, we have already developed a Detached Eddy Simulation (DES)-based zonal modeling technique, which was found to have adequate scale-resolving capabilities in several engine-like reference tests. In the present article we further extend our study by evaluating the effects of the underlying turbulence model and of the grid quality/morphology on the scale-resolved part of the flow. For that purpose, we consider DES formulations based on an enhanced version of the k-g URANS model and on the URANS form of the popular RNG k-ε model.

A two-equation Zonal-DES (ZDES) approach has been recently proposed by the authors as a suitable hybrid URANS/LES turbulence modeling alternative for Internal Combustion Engine flows. This approach is conceptually simple, as it is all based on a single URANS-like framework and the user is only required to explicitly mark which parts of the domain will be simulated in URANS, DES or LES mode. The ZDES rationale was initially developed for external aerodynamics applications, where the flow is statistically steady and the transition between zones of different types usually happens in the URANS-to-DES or URANS-to-LES direction. The same “one-way” transition process has been found to be fairly efficient also in steady-state internal flows with engine-like characteristics, such as abrupt expansions or intake ports with fixed valve position.

In European Union (EU), transport causes about a quarter of the total greenhouse gases (GHG) emissions and road vehicles are the biggest contributors, with nearly three-quarters of the overall GHG emissions. In this context, many governments are adopting different strategies to achieve a sustainable mobility, including the electrification of public transport, such as full electric taxis (e-taxis). Indeed, battery electric vehicles (BEVs) represent a promising solution towards the achievement of sustainability since they involve zero emissions during the use phase, despite indirect emissions are generated during the charging of the traction battery according to the specific national electricity mix. However, a proper choice of the vehicle segment for the e-taxi and its battery capacity can represent a crucial factor in reducing the overall environmental impacts.

Turbulence modeling for fuel spray simulation plays a prominent role in the understanding of the flow behavior in Internal Combustion Engines (ICEs). Currently, a lot of research work is actively spent on Large Eddy Simulation (LES) turbulence modeling as a replacement option of standard Reynolds averaged approaches in the Eulerian-Lagrangian spray modeling framework, due to its capability to accurately describe flow-induced spray variability and to the lower dependence of the results on the specific turbulence model and/or modeling coefficients. The introduction of LES poses, however, additional questions related to the implementation/adaptation of spray-related turbulence sources and to the rise of conflicting numerics and grid requirements between the Lagrangian and Eulerian parts of the simulated flow.

Scale-resolving turbulence modeling for engine flow simulation has constantly increased its popularity in the last decade. In contrast to classical RANS modeling, LES-like approaches are able to resolve a larger number of unsteady flow features. In principle, this capability allows to accurately predict some of the key parameters involved in the development and optimization of modern engines such as cycle-to-cycle variations in a DI engine. However, since multiple simulated engine cycles are required to extract reliable flow statistics, the spatial and temporal resolution requirements of pure LES still represent a severe limit for its wider application on realistic engine geometries. In this context, Hybrid URANS-LES methodologies can therefore become a potentially attractive option. In fact, their task is to preserve the turbulence scale-resolving in the flow core regions but at a significantly lower computational cost compared to standard LES.

In this paper, we deploy a novel, multidimensional approach to simulate SCR reactors across physical scales. For the first time, a full 3D Lattice Boltzmann (LB) solver is developed, able to accurately capture the fluid dynamic phenomena taking place inside SCR reactors, as well as the catalytic conversion of NOx. The influence of engine load on exhaust gas mass flow rate and catalytic converter activity is taken into account. The proposed approach is computationally light and the results prove the reliability and versatility of the LB Method for the simulation of the complex phenomena that take place inside the after-treatment devices.

The second-life use of batteries from electric vehicles (EV) represents an excellent and cost-effective option for energy storage applications, including the control of fluctuations in energy supply and demand or in combination with solar photovoltaic and wind turbine. Indeed, these batteries are normally replaced from EV use before the end of their service life, when they still have 70-80% of the original capacity. Depending on the cell chemistry and the specific design, such batteries can still be employed in less stressful applications than the automotive one, including commercial, residential, and industrial applications. With the aim to promote the transition to a circular closed-loop economy for spent traction batteries, this study consists in a systematic literature review of available options for reusing EV batteries as a storage system in a factory environment, highlighting benefits and critical aspects.