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The aim of this work is to analyze particle number and size distribution from a small displacement Euro 5 common rail automotive diesel engine, equipped with a close coupled aftertreatment system, featuring a DOC and a DPF integrated in a single canning. In particular the effects of different combustion processes on PM characteristics were investigated, by comparing measurements made both under normal operating condition and under DPF regeneration mode. Exhaust gas was sampled at engine outlet, at DOC outlet and at DPF outlet, in order to fully characterize PM emissions through the whole exhaust line. After a two stage dilution system, sampled gas was analyzed by means of a TSI 3080 SMPS, in the range from 6 to 240 nm. Particle number and size distribution were evaluated at part load operating conditions, representative of urban driving.

The aerodynamic properties of a BMW car model, representing a 40%-scaled model of a relevant car configuration, are studied computationally by means of the Unsteady RANS (Reynolds-Averaged Navier-Stokes) and Hybrid RANS/LES (Large-Eddy Simulation) approaches. The reference database (geometry, operating parameters and surface pressure distribution) are adopted from an experimental investigation carried out in the wind tunnel of the BMW Group in Munich (Schrefl, 2008). The present computational study focuses on validation of some recently developed turbulence models for unsteady flow computations in conjunction with the universal wall treatment combining integration up to the wall and high Reynolds number wall functions in such complex flow situations. The turbulence model adopted in both Unsteady RANS and PANS (Partially-Averaged Navier Stokes) frameworks is the four-equation ζ − f formulation of Hanjalic et al. (2004) based on the Elliptic Relaxation Concept (Durbin, 1991).

This paper describes a method for optimization of engine settings in view of best total cost of operation fluids. Under specific legal NOX tailpipe emissions requirements the engine out NOX can be matched to the current achievable SCR NOX conversion efficiency. In view of a heavy duty long haul truck application various specific engine operation modes are defined. A heavy duty diesel engine was calibrated for all operation modes in an engine test cell. The characteristics of engine operation are demonstrated in different transient test cycles. Optimum engine operation mode (EOM) selection strategies between individual engine operation modes are discussed in view of legal test cycles and real world driving cycles which have been derived from on-road tests.

Automotive embedded systems have become very complex, are strongly integrated, and the safety-criticality and real-time constraints of these systems raise new challenges. The OSEK/VDX standard provides an open-ended architecture for distributed real-time capable units in vehicles. This is supported by the OSEK Implementation Language (OIL), a language aiming at specifying the configuration of these real-time operating systems. The challenge, however, is to ensure consistency of the concept constraints and configurations along the entire product development. The contribution of this paper is to bridge the existing gap between model-driven systems engineering and software engineering for automotive real-time operating systems (RTOS). For this purpose a bidirectional tool bridge has been established based on OSEK OIL exchange format files.

The use of Ducted Fuel Injection (DFI) for attenuating soot formation throughout mixing-controlled diesel combustion has been demonstrated impressively effective both experimentally and numerically. However, the last research studies have highlighted the need for tailored engine calibration and duct geometry optimization for the full exploitation of the technology potential. Nevertheless, the research gap on the response of DFI combustion to the main engine operating parameters has still to be fully covered. Previous research analysis has been focused on numerical soot-targeted duct geometry optimization in constant-volume vessel conditions. Starting from the optimized duct design, the herein study aims to analyze the influence of several engine operating parameters (i.e. rail pressure, air density, oxygen concentration) on DFI combustion, having free spray results as a reference.

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

This paper describes the development of a 0-D-sulfur poisoning model for a NOx storage catalyst (NSC). The model was developed and calibrated using findings and data obtained from a passenger car diesel engine used on testbed. Based on an empirical approach, the developed model is able to predict not only the lower sulfur adsorption with increasing temperature and therefore the higher SOx (SO2 and SO3) slip after NSC, but also the sulfur saturation with increasing sulfur loading, resulting in a decrease of the sulfur adsorption rate with ongoing sulfation. Furthermore, the 0-D sulfur poisoning model was integrated into an existing 1-D NOx storage catalyst kinetic model. The combination of the two models results in an “EAS Model” (exhaust aftertreatment system) able to predict the deterioration of NOx-storage in a NSC with increasing sulfation level, exhibiting higher NOx-emissions after the NSC once it is poisoned.

Nowadays, injection rate shaping and multi-pilot events can help to improve fuel efficiency, combustion noise and pollutant emissions in diesel engine, providing high flexibility in the shape of the injection that allows combustion process control. Different strategies can be used in order to obtain the required flexibility in the rate, such as very close pilot injections with almost zero Dwell Time or boot shaped injections with optional pilot injections. Modern Common-Rail Fuel Injection Systems (FIS) should be able to provide these innovative patterns to control the combustion phases intensity for optimal tradeoff between fuel consumption and emission levels.

A model-based approach to control BMEP (Brake Mean Effective Pressure) and NOx emissions has been developed and assessed on a FPT F1C 3.0L Euro VI diesel engine for heavy-duty applications. The controller is based on a zero-dimensional real-time combustion model, which is capable of simulating the HRR (heat release rate), in-cylinder pressure, BMEP and NOx engine-out levels. The real-time combustion model has been realized by integrating and improving previously developed simulation tools. A new discretization scheme has been developed for the model equations, in order to reduce the accuracy loss when the computational step is increased. This has allowed the required computational time to be reduced to a great extent.

The paper deals with the design and manufacturing of a McPherson suspension arm made from short glass fiber reinforced polyamide (PA66). The design of the arm and the design of the molds have been made jointly. According to Industry 4.0 paradigms, a full digitalization of both the product and process has been performed. Since the mechanical behavior of the suspension arm strongly depends on constraints which are difficult to be modelled, a simpler structure with well-defined mechanical constraints has been developed. By means of such simple structure, the model for the behavior of the material has been validated. Since the suspension arm is a hybrid structure, the associated simple structure is hybrid as well, featuring a metal sheet with over-molded polymer. The issues referring to material flow, material to material contact, weld lines, fatigue strength, high and low temperature behavior, creep, dynamic strength have been investigated on the simple structure.

To comply with the stringent fuel consumption requirements, many automobile manufacturers have launched vehicle electrification programs which are representing a paradigm shift in vehicle design. Looking specifically at powertrain calibration, optimization approaches were developed to help the decision-making process in the powertrain control. Due to computational power limitations the most common approach is still the use of powertrain calibration tables in a rule-based controller. This is true despite the fact that the most common manual tuning can be quite long and exhausting, and with the optimal consumption behavior rarely being achieved. The present work proposes a simulation tool that has the objective to automate the process of tuning a calibration table in a powertrain model. To achieve that, it is first necessary to define the optimal reference performance.

As an era of autonomous driving approaches, it is necessary to translate handling comfort - currently a responsibility of human drivers - to a vehicle imbedded algorithm. Therefore, it is imperative to understand the relationship between perceived driving comfort and human driving behaviour. This paper develops a methodology able to generate the information necessary to study how this relationship is expressed in highway overtakes. To achieve this goal, the approach revolved around the implementation of sensor Data Fusion, by processing data from CAN, camera and LIDAR from experimental tests. A myriad of variables was available, requiring individuating the key-information and parameters for recognition, classification and understanding of the manoeuvres. The paper presents the methodology and the role each sensor plays, by expanding on three main steps: Data segregation and parameter selection; Manoeuvre detection and processing; Manoeuvre classification and database generation.

The world of automotive engineering shows a clear direction for upcoming development trends. Stringent fleet average fuel consumption targets and CO2 penalties as well as rising fuel prices and the consumer demand to lower operating costs increases the engineering efforts to optimize fuel economy. Passenger car engines have the benefit of higher degree of technology which can be utilized to reach the challenging targets. Variable valve timing, downsizing and turbo charging, direct gasoline injection, highly sophisticated operating strategies and even more electrification are already common technologies in the automotive industry but can not be directly carried over into a motorcycle application. The major differences like very small packaging space, higher rated speeds, higher power density in combination with lower production numbers and product costs do not allow implementation such high of degree of advanced technology into small-engine applications.

Recently, a particle number (PN) limit was introduced in the European light-duty vehicles legislation. The legislation requires measurement of PN, and particulate mass (PM), from the full dilution tunnel with constant volume sampling (CVS). Furthermore, PN measurements will be introduced in the next stage of the European Heavy-Duty regulation. Heavy-duty engine certification can be done either from the CVS or from a partial flow dilution system (PFDS). For research and development purposes, though, measurements are often conducted from the raw exhaust, thereby avoiding the high installation costs of CVS and PFDS. Although for legislative measurements requirements exist regarding sampling and transport of the aerosol sample, such requirements do not necessarily apply for raw exhaust measurements. Thus, measurement differences are often observed depending on where in the experimental set up sampling occurs.

Sustainable and energy-efficient consumption is a main concern in contemporary society. Driven by more stringent international requirements, automobile manufacturers have shifted the focus of development into new technologies such as Hybrid Electric Vehicles (HEVs). These powertrains offer significant improvements in the efficiency of the propulsion system compared to conventional vehicles, but they also lead to higher complexities in the design process and in the control strategy. In order to obtain an optimum powertrain configuration, each component has to be laid out considering the best powertrain efficiency. With such a perspective, a simulation study was performed for the purpose of minimizing well-to-wheel CO2 emissions of a city car through electrification. Three different innovative systems, a Series Hybrid Electric Vehicle (SHEV), a Mixed Hybrid Electric Vehicle (MHEV) and a Battery Electric Vehicle (BEV) were compared to a conventional one.

The particulate emissions of two brake systems were characterized in a dilution tunnel optimized for PM10 measurements. The larger of them employed a fixed caliper (FXC) and the smaller one a floating caliper (FLC). Both used ECE brake pads of the same lining formulation. Measured properties included gravimetric PM2.5 and PM10, Particle Number (PN) concentrations of both untreated and thermally treated (according to exhaust PN regulation) particles using Condensation Particle Counters (CPCs) having 23 and 10 nm cut-off sizes, and an Optical Particle Sizer (OPS). The brakes were tested over a section (trip-10) novel test cycle developed from the database of the Worldwide harmonized Light-Duty vehicles Test Procedure (WLTP). A series of trip-10 tests were performed starting from unconditioned pads, to characterize the evolution of emissions until their stabilization. Selected tests were also performed over a short version of the Los Angeles City Cycle.

Developing of innovative technologies and materials to meet the requirements of environmental legislation on vehicle emissions has paramount importance for researchers and industries. Therefore, improvement of engine efficiency and fuel saving of modern internal combustion engines (ICEs) is one of the key factors, together with the weight reduction. Thermoplastic composite materials might be one of the alternative materials to be employed to produce engine components to achieve these goals as their properties can be engineered to meet application requirements. Unidirectional carbon fiber reinforced PolyEtherImide (CF/PEI) thermoplastic composite is used to design engine connecting rod and wrist pin, applying commercial engine data and geometries. The current study is focused on some elements of the crank mechanism as the weight reduction of these elements affects not only the curb weight of the engine but the overall structure.

In automotive market, today more than in the past, it is very important to reduce time to market and, mostly, developing costs before the final production start. Ideally, bench and on-road tests can be replaced by multi-body studies because virtual approach guarantees test conditions very close to reality and it is able to exactly replicate the standard procedures. Therefore, today, it is essential to create very reliable models, able to forecast the vehicle behavior on every road condition (including uneven surfaces). The aim of this study is to build an accurate multi-body model of a heavy-duty truck, check its handling performance, and correlate experimental and numerical data related to comfort tests for model tuning and validation purposes. Experimental results are recorded during tests carried out at different speeds and loading conditions on a Belgian blocks track. Simulation data are obtained reproducing the on-road test conditions in multi-body environment.

In the framework of an increasing demand for a more sustainable mobility, where the fuel consumption reduction is a key driver for the development of innovative internal combustion engines, Turbulent Jet Ignition (TJI) represents one of the most promising solutions to improve the thermal efficiency. However, details concerning turbulent jet assisted combustion are still to be fully captured, and therefore the design and the calibration of efficient TJI systems require the support of reliable simulation tools that can provide additional information not accessible through experiments. To this aim, an experimental investigation combined with a 3D-CFD study was performed to analyze the TJI combustion characteristics in a single-cylinder spark-ignition (SI) engine. Firstly, the model was validated against experiments considering stoichiometric mixture at 3000 rpm, wide open throttle operating conditions.

This paper presents a technique for extracting modal parameters of a linear multi degree of freedom system in the frequency domain. The roots of the technique are the well known rational fraction polynomials method but emphasis is given to the application to output-only data in the form of cross-spectral density functions. A discussion is presented on the possibility of achieving reliable results also for structures undergoing multiple input excitations. Numerical stability of the technique is obtained by properly scaling both the frequency and the cross-spectrum axes. Good performance of the method are shown for numerical examples and for a test case on an actual structure.