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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.

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 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.

Modern ‘DOC-cDPF’ systems for diesel exhaust are employing Pt-, Pd- as well as Pt/Pd alloy- based coatings to ensure high conversion efficiency of CO, HC even at low temperatures. Depending on the target application, these coatings should be also optimized towards NO2 generation which is involved in low temperature soot oxidation as well as in SCR-based deNOx. Zeolite materials are also frequently used to control cold-start HC emissions. Considering the wide variety of vehicles, engines and emission targets, there is no single optimum coating technology. The main target is therefore to maximize synergies rather than to optimize single components. At the same time, the system designer has nowadays a wide range of technologies to choose from, including PGM alloyed combinations (Pt/Pd), multiple layers and zones applicable to both DOCs and DPFs.

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.

In the last years automotive industry has shown a growing interest in exploring the field of vehicle dynamic control, improving handling performances and safety of the vehicle, and actuating devices able to optimize the driving torque distribution to the wheels. These techniques are defined as torque vectoring. The potentiality of these systems relies on the strong coupling between longitudinal and lateral vehicle dynamics established by tires and powertrain. Due to this fact the detailed (and correct) simulation of the dynamic behaviour of the driveline has a strong importance in the development of these control systems, which aim is to optimize the contact forces distribution. The aim of this work is to build an integrated vehicle and powertrain model in order to provide a proper instrument to be used in the development of such systems, able to reproduce the dynamic interaction between vehicle and driveline and its effects on the handling performances.

This paper presents the results of CFD study on sunroof buffeting suppression using a dividing bar. The role of a dividing bar in side window buffeting case was illustrated in a previous study [8]. For the baseline model of the selected vehicle in this study, a very high level of sunroof buffeting, 133dB, has been found. The CFD simulation shows that the buffeting noise can be significantly reduced if a dividing bar is installed at the sunroof. A further optimization study on the dividing bar demonstrates that the peak buffeting level can be reduced to 123dB for the selected vehicle if the dividing bar is installed at its optimal location, 65% of the total length from the front edge of the sunroof. The peak buffeting level can be further reduced to 100dB if the dividing bar takes its optimal width 80mm, 15% of the total length of the sunroof for this vehicle, while staying at its optimal location.

Achieving upcoming HD emissions legislation, Euro VI/EPA 10, is a challenge for all engine manufacturers. A likely solution to meet the NOx limit is to use a combination of EGR and SCR. Combining these two technologies poses new challenges and possibilities when it comes to optimization and calibration. Using a complete system approach, i.e., considering the engine and the aftertreatment system as a single unit, is important in order to achieve good performance. Optimizing the complete system is a tedious task; first there are a large number of variables which affect both emissions and fuel consumption (injection timing, EGR rate, urea dosing, injection pressure, pilot/post injections, for example). Secondly, the chemical reactions in the SCR catalyst are substantially slower than the dynamics of the diesel engine and the rest of the system, making the optimization problem time dependent.

The current research focuses in understanding how inlet pressure, EGR, combustion phasing, engine speed and pilot main ratio are affecting the main parameters of the combustion (e.g. efficiency, NOx, soot, maximum pressure rise rate) in the novel concept of injecting high octane number fuels in partially premixed combustion. The influence of the above mentioned parameters was studied by performing detailed sweeps at 32 bar fuel MEP (c.a. 16-18 bar gross IMEP); three different kinds of gasoline were tested (RON: 99, 89 and 69). The experiments were ran in a single cylinder heavy duty engine; Scania D12. At the end of these sweeps the optimized settings were computed in order to understand how to achieve high efficiency, low emissions and acceptable maximum pressure rise rate.

The vibration-generating mechanisms inside an engine are highly non-linear (combustion, valve operation, hydraulic bearing behavior, etc.). However, the engine structure, under the influence of these vibration-generating mechanisms, responds in a highly linear way. For the development and optimization of the engine structure for noise and vibration it is beneficial to use fast and ‘simple’ linear models, like linear FE-models, measured modal models or measured FRF-models. All these models allow a qualitative assessment of variants without excitation information. But, for true optimization, internal excitation spectra are needed in order to avoid that effort is spent to optimize non-critical system properties. Unfortunately, these internal excitation spectra are difficult to measure. Direct measurement of combustion pressure is still feasible, but crank-bearing forces, piston guidance forces etc. can only be identified indirectly.

For the 2003 model year DaimlerChrysler Corporation will launch a totally new 5.7L V-8 engine for applications of the Dodge Ram pick-up truck. The new engine was created largely within a digital environment using the latest computer aided design (CAD) and computer aided engineering (CAE) techniques and tools. Utilizing a co-located team of design engineers, designers, and CAE engineers enabled the simulations to impact the design from program inception to the assembly line, saving program time and investment. This paper describes the successful merging of design and advanced analysis techniques by highlighting examples throughout the new HEMI® program. Case studies include issues in the areas of structural optimization, engine loading, lubrication circuit, cooling circuit, and manufacturing.

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 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.

The successful design and especially the control of the SCR system is a challenging process that can be supported by the application of simulation tools. As a first step, we employ physico-chemically informed ‘off-line’ models that are calibrated with the help of targeted small- and full-scale tests. Despite their high level of sophistication, this SCR model is able to be integrated in a control-oriented simulation software platform and connected to other powertrain simulation blocks. The target is to use this simulation platform as a virtual environment for the development and optimization of SCR control strategies. The above process is demonstrated in the case of a passenger car SCR. The model is calibrated at both fresh and aged catalyst condition and validated using experimental data from the engine bench under a wide variety of operating conditions. Next, the calibrated model was coupled with embedded control models, developed for Euro 6 passenger car powertrains.

In the paper several application techniques of MonteCarlo (MC) method applied to thermal analysis of space vehicles are presented. Although these methods are widely used in other engineering domains, their introduction to the thermal one is quite recent and not fully developed in the industrial practice. This paper aims at showing that, even without demanding computation resources (all what presented has been obtained with a single processor PC) MonteCarlo analysis techniques, in a preliminary design phase, can support and integrate engineering judgment of the thermal designer. In particular, it is exploited the applicability of the method to reduced thermal models, with a clear advantage in terms of computation time. An original approach is proposed, and results are shown. The papers shows the applicability of the MC method to the case when experimental data of the uncertain parameters are available, using the bootstrap re-sampling techniques.

This paper presents the results of optimization study for sunroof buffeting reduction using CFD technology. For an early prototype vehicle as a baseline model in this study a high level of sunroof buffeting 133dB has been found. The CFD simulation shows that the buffeting noise can be reduced by installing a wind deflector at its optimal angle 40 degrees from the upward vertical line. Further optimization study demonstrates that the buffeting peak SPL can be reduced to 97dB if the sunroof glass moves to its optimal position, 50% of the total length of the sunroof from the front edge. For any other vehicles, the optimization procedure is the same to get the optimal parameters. On the other hand, however, this optimization study is only based on fluid dynamics principle without considering manufacturability, styling, cost, etc. Further work is needed to utilize the results in the production design.

In Plug in hybrid electric vehicles (PHEVs), the management of the main drivetrain components and the shift between pure electric and hybrid propulsion is decided by the on-board energy management system (EMS). The EMS decisions have a direct impact on CO2 emissions and need to be optimized to achieve as low emissions as possible. This paper presents optimization methods for EMS algorithms of a parallel P2 PHEV. Two different supervisory control algorithms are examined, employing simulations on a validated PHEV platform. An Equivalent Consumption Minimization Strategy (ECMS) algorithm is implemented and compared to a rule-based one, the latter derived by back-engineering of available experimental data. The different EMS algorithms are analyzed and compared on an equal basis in terms of distance, demanded energy and state of charge levels over different driving cycles.

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.

The relationship of the airbag fire-distribution as a function of impact velocity to the airbag fire-time is studied through the use of an optimization procedure. The study is conducted by abstracting the sensor algorithm and its associated constraints into a simple mathematical formulation. An airbag fire objective function is constructed that integrates the fire-rate and fire-time requirements. The function requires the input of a single acceleration time history; it produces an output depending on the airbag fire condition. Numerical search of the optimal fire threshold curve is achieved through parameterizing this curve and applying a modified simplex search optimization algorithm that determines the optimal threshold function parameters without computing the complete objective function in the parameter space. Numerical results are given to show the effectiveness and potential difficulties with the automatic search scheme.

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.