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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.

SI engines fueled with hydrogen represent a promising powertrain solution to meet the ambitious target of carbon-free emissions at the tailpipe. Therefore, fast and reliable numerical tools can significantly support the automotive industry in the optimization of such technology. In this work, a 1D-3D methodology is presented to simulate in detail the combustion process with minimal computational effort. First, a 1D analysis of the complete engine cycle is carried out on the user-defined powertrain configuration. The purpose is to achieve reliable boundary conditions for the combustion chamber, based on realistic engine parameters. Then, a 3D simulation of the power-cycle is performed to mimic the combustion process. The flow velocity and turbulence distributions are initialized without the need of simulating the gas exchange process, according to a validated technique.

We present a framework for the robust optimization of the heat flux distribution for an anti-ice electro-thermal ice protection system (AI-ETIPS) and iced airfoil performance analysis under uncertain conditions. The considered uncertainty regards a lack of knowledge concerning the characteristics of the cloud i.e. the liquid water content and the median volume diameter of water droplets, and the accuracy of measuring devices i.e., the static temperature probe, uncertain parameters are modeled as uniform random variables. A forward uncertainty propagation analysis is carried out using a Monte Carlo approach. The optimization framework relies on a gradient-free algorithm (Mesh Adaptive Direct Search) and three different problem formulations are considered in this work. Two bi-objective deterministic optimizations aim to minimize power consumption and either minimize ice formations or the iced airfoil drag coefficient.

The tightening trend of regulations on the levels of admitted pollutant emissions has given a great spur to the research work in the field of combustion and after-treatment devices. Despite the improvements that can be applied to the development of the combustion process, pollutant emissions cannot be reduced to zero; for this reason, the aftertreatment system will become a key component in the path to achieving near-zero emission levels. This study focuses on the numerical analysis and optimization of different metallic substrates, specifically developed for three-way catalyst (TWC) and Diesel oxidation catalyst (DOC) applications, to improve their thermal efficiency by reducing radial thermal losses through the outer mantle. The optimization process relies on computational fluid dynamics (CFD) simulations supported by experimental measurements to validate the numerical models carried out under uncoated conditions, where chemical reactions do not occur.

The paper illustrates and validates a novel predictive combustion model for the estimation of performances and pollutant production in CI engines. The numerical methodology was developed by the authors for near real-time applications, while aiming at an accurate description of the air mixing process by means of a multi-zone approach of the air-fuel mass. Charge stratification is estimated via a 2D representation of the fuel spray distribution that is numerically derived by an axial one-dimensional control-volume description of the direct injection. The radial coordinate of each control volume is reconstructed a posteriori by means of a local distribution function. Fuel mass clustered in each zone is further split in ‘liquid’, ‘unburnt’ and ‘burnt’ sub-zones, given the local properties of the fuel spray control volumes with respect to space-time location of modelled ignition delay, liquid length, and flame lift-off.

Brake calipers for high-end cars are typically realized using Aluminum alloys, with Silicon as the most common alloying element. Despite the excellent castability and machinability of Aluminum-Silicon alloys (AlSix), anodization is often required in order to increase its corrosion resistance. This is particularly true in Chlorides-rich environments where Aluminum can easily corrode. Even if anodization process is known for almost 100 years, anodization of AlSix -based materials is particularly challenging due to the presence of eutectic Silicon precipitates. These show a poor electric conductivity and a slow oxidation kinetics, leading to inhomogeneous anodic layers. Continuous research and process optimization are required in order to develop anodic layers with enhanced morphological and electrochemical properties, targeting a prolonged resistance of brake calipers under endurance corrosive tests (e.g. >1000 hours Neutral Salt Spray (NSS) tests).

Selective Catalytic Reduction (SCR) systems are nowadays widely applied for the reduction of NOx emitted from Diesel engines. The typical process is based on the injection of aqueous urea in the exhaust gases before the SCR catalyst, which determines the production of the ammonia needed for the catalytic reduction of NOx. However, this technology is affected by two main limitations: a) the evaporation of the urea water solution (UWS) requires a sufficiently high temperature of the exhaust gases and b) the formation of solid deposits during the UWS evaporation is a frequent phenomenon which compromise the correct operation of the system. In this context, to overcome these issues, a technology based on the injection of gaseous ammonia has been recently proposed: in this case, ammonia is stored at the solid state in a cartridge containing a Strontium Chloride salt and it is desorbed by means of electrical heating.

A multi-objective optimal design of a brushless DC electric motor for a brake system application is presented. Fifteen design variables are considered for the definition of the stator and rotor geometry, pole pieces and permanent magnets included. Target performance indices (peak torque, efficiency, rotor mass and inertia) are defined together with design constraints that refer to components stress levels and temperature thresholds, not to be surpassed after heavy duty cycles. The mathematical models used for optimization refer to electromagnetic field and related currents computation, to thermo-fluid dynamic simulation, to local stress and vibration assessment. An Artificial Neural Network model, trained with an iterative procedure, is employed for global approximation purposes. This allows to reduce the number of simulation runs needed to find the optimal configurations. Some of the Pareto-optimal solutions resulting from the optimal design process are analysed.

This work describes the development of a computational model for the CFD simulation of compact heat exchangers applied for the oil cooling in internal combustion engines. Among the different cooler types, the present modeling effort will be focused on liquid-cooled solutions based on offset strip fins turbulators. The design of this type of coolers represents an issue of extreme concern, which requires a compromise between different objectives: high compactness, low pressure drop, high heat-transfer efficiency. In this work, a computational framework for the CFD simulation of compact oil-to-liquid heat exchangers, including offset-strip fins as heat transfer enhancer, has been developed. The main problem is represented by the need of considering different scales in the simulation, ranging from the characteristic size of the turbulator geometry (tipically μm - mm) to the full scale of the overall device (typically cm - dm).

Todays tuning of hydraulic vehicle shock absorbers is mainly an empirical iterative process performed in time-consuming and expensive ride tests, whereas the majority of damper simulation models used for investigating vehicle ride behavior is based on an abstract parameterization. For the manufacturing of automotive dampers, however, the valve code is essential. Minor changes in the valve code describing the shim stack in the hydraulic valves may have a noticeable impact on the damper characteristics, while the physical effects are still not sufficiently understood. Therefore, the paper presents a detailed physics-based structural model to investigate the pressure-deflection behavior of shim stacks and the influence of specific discs in the stack. The model includes a variety of effects like friction and preload, and is capable to predict the damper characteristics.

In the last decades numerical simulations have become reliable tools for the design and the optimization of silencers for internal combustion engines. Different approaches, ranging from simple 1D models to detailed 3D models, are nowadays commonly applied in the engine development process, with the aim to predict the acoustic behavior of intake and exhaust systems. However, the acoustic analysis is usually performed under the hypothesis of infinite stiffness of the silencer walls. This assumption, which can be regarded as reasonable for most of the applications, can lose validity if low wall thickness are considered. This consideration is even more significant if the recent trends in the automotive industry are taken into account: in fact, the increasing attention to the weight of the vehicle has lead to a general reduction of the thickness of the metal sheets, due also to the adoption of high-strength steels, making the vibration of the components a non negligible issue.

Mass minimization is a key objective for the design of racing motorcycle wheels. The structural optimization of a front motorcycle wheel is presented in the paper. Topology Optimization has been employed for deriving optimized structural layouts. The minimum compliance problem has been solved, symmetry and periodicity constraints have been introduced. The wheel has been optimized by considering several loading conditions. Actual loads have been measured during track tests by means of a special measuring wheel. The forces applied by the tire to the rim have been introduced in an original way. Different solutions characterized by different numbers of spokes have been analyzed and compared. The actual racing wheel has been further optimized accounting for technological constraints and the mass has been reduced down to 2.9 kilograms.

This paper presents a nonlinear control approach to achieve good performances in vehicle path following and collision avoidance when the vehicle is driving under cruise highway conditions. Nonlinear model predictive control (NLMPC) is adopted to achieve online trajectory control based on a simplified vehicle model. GMRES/Continuation algorithm is used to solve the online optimization problem. Simulations show that the proposed controller is capable of tracking the desired path as well as avoiding the obstacles.

In this paper a rule-based energy management for parallel hybrid electric vehicles (HEVs) is presented, which is based on the principles describing the optimal control behavior. Therefore we first show the general relations that can be used to describe the optimal limit of electric driving as well as the optimal torque split among the two propulsion systems. Subsequently these relations are employed to derive maps, which represent the optimal behavior depending on several input parameters. These maps are then used as inputs for the rules in the proposed energy management. This not only makes it possible to automatically calibrate the rule-based controller but also gives the optimal control in every driving situation. Given it is not fuel-efficient to turn the internal combustion engine (ICE) on or off for short intervals, it is further shown how this approach allows to adjust the established limit for electric driving by additional rules.

The worldwide automotive industry is currently preparing for a market introduction of hydrogen-fueled powertrains. These powertrains in fuel cell electric vehicles (FCEVs) offer many advantages: high efficiency, zero tailpipe emissions, reduced greenhouse gas footprint, and use of domestic and renewable energy sources. To realize these benefits, hydrogen vehicles must be competitive with conventional vehicles with regards to fueling time and vehicle range. A key to maximizing the vehicle's driving range is to ensure that the fueling process achieves a complete fill to the rated Compressed Hydrogen Storage System (CHSS) capacity. An optimal process will safely transfer the maximum amount of hydrogen to the vehicle in the shortest amount of time, while staying within the prescribed pressure, temperature, and density limits. The SAE J2601 light duty vehicle fueling standard has been developed to meet these performance objectives under all practical conditions.

In this work a multilevel CFD analysis have been applied for the design of an intake air-box with improved characteristics of noise reduction and fluid dynamic response. The approaches developed and applied for the optimization process range from the 1D to fully 3D CFD simulation, exploring hybrid approaches based on the integration of a 1D model with quasi-3D and 3D tools. In particular, the quasi-3D strategy is exploited to investigate several configurations, tailoring the best trade-off between noise abatement at frequencies below 1000 Hz and optimization of engine performances. Once the best configuration has been defined, the 1D-3D approach has been adopted to confirm the prediction carried out by means of the simplified approach, studying also the impact of the new configuration on the engine performances.

Rising oil prices and increasing strict emission legislation force vehicle manufacturers to reduce fuel consumption of future vehicles. In order to meet this target, the process of converting fuel into useable energy and the use of this energy by the different energy-consuming vehicle's subsystems have to be examined. Vehicles' subsystems consist of energy-supplying, energy-consuming, and in some cases energy-storing components. Due to the high complexity of these systems and their interaction, optimization of their energy efficiency is a challenging task. By introducing individual operational strategies for each subsystem, it is possible to increase the energy efficiency for a specific function. To further improve the vehicle's overall energy efficiency, holistic control strategies are introduced that distribute the energy between the subsystems intelligently.

This work focuses on the analysis of the vertical dynamics of an agricultural tractor, investigating the influence of suspensions' parameters on riding comfort and contact forces. The use of lugged tires coupled with the operation over banked, irregular and deformable tracks, determines significant levels of vertical acceleration over several components of the tractor. These operating conditions have a direct effect on the driver, whose alertness and efficiency are undermined by the exposure to high levels of acceleration for a long time. Secondly, variations of the normal and traction forces provided by the tires affect the quality of tillage and other operations. The paper presents a multi-body vehicle model of a tractor interfaced with a tire-soil contact model allowing to take into account soil's deformation and tread pattern design.

An overview of Daimler?s progression to advance powertrain technology in a growth industry shows many different solutions to improvement in transportation. Daimler continues to make breakthroughs in technology development and application building on 125 years of automotive development. Optimization of current powertrains will enable a significant gain in CO2/mi reductions, that dependent on product mix can be augmented with additional technologies. There is however no bypass to some form of electrification, enabling efficiency gains and alternative forms of power supply. Development of hybrid powertrains continues in an established manner and enhanced development of further electrified powertrains are in development. Organizationally and technically, significant skills and adjustments need to continue to be undertaken enabling OEMs and in particular the supply base to develop optimized solutions efficiently. The outlook is bright for novel component development and innovation.

Beginning in 2010, Daimler's well-known Diesel Sprinter van has to fulfill the new and clearly tighter NOx emission standards of NAFTA10 (EPA, CARB). This requires an integrated approach of further engine optimizations and the implementation of an innovative exhaust aftertreatment technology. The goal was to develop an overall concept which meets simultaneously the tightened emission standards (including OBD limits) and the increasing customer demands of more power and torque without losing the high fuel efficiency of the small and highly efficient 3-liter V6 diesel engine OM642, which already has been installed in the NAFTA07 Sprinter. In the early stages of the concept phase, the most appropriate NOx aftertreatment technology and certification form (engine or vehicle) had to be selected for this specific vehicle class in the van segment with enhanced requirements to durability, economical efficiency and specific driving behavior.