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GTL (Gas-To-Liquid) fuel is well known to improve tailpipe emissions when fuelling a conventional diesel vehicle, that is, one optimized to conventional fuel. This investigation assesses the additional potential for GTL fuel in a GTL-dedicated vehicle. This potential for GTL fuel was quantified in an EU 4 6-cylinder serial production engine. In the first stage, a comparison of engine performance was made of GTL fuel against conventional diesel, using identical engine calibrations. Next, adaptations enabled the full potential of GTL fuel within a dedicated calibration to be assessed. For this stage, two optimization goals were investigated: - Minimization of NOx emissions and - Minimization of fuel consumption. For each optimization the boundary condition was that emissions should be within the EU5 level. An additional constraint on the latter strategy required noise levels to remain within the baseline reference.

Partly competing objectives, as low fuel consumption, low friction, long oil maintenance rate, and at the same time lowest exhaust emissions have to be fulfilled. Diminishing resources, continuously reduced development periods, and shortened product cycles yield detailed knowledge about oil consumption mechanisms in combustion engines to be essential. There are different ways for the lubricating oil to enter the combustion chamber: for example as blow-by gas, leakage past valve stem seals, piston rings (reverse blow-by) and evaporation from the cylinder liner wall and the combustion chamber. For a further reduction of oil consumption the investigation of these mechanisms has become more and more important. In this paper the influence of the mixture formation and the resulting fuel content in the cylinder liner wall film on the lubricant oil emission was examined.

The steady increase of engine power and the demand of lightweight design along with enhanced reliability require an optimized dimensioning process, especially in cylinder head valve bridge, which is progressively prone to cracking. The problems leading to valve bridge cracking are high temperatures and temperature gradients on one hand and high mechanical restraining on the other hand. The accurate temperature estimation at the valve bridge center has significant outcomes for valve bridge thickness and width optimization. This paper presents a 1D heat transfer model, which is constructed through the cross section of the valve bridge center by the use of well known quasi-stationary heat convection and conduction equations and reduced from 3D to 1D via regression and empirical weighting coefficients. Several diesel engine cylinder heads with different application types and materials are used for model setup and verification.

An operational scheme with fuel-lean and exhaust gas dilution in spark-ignited engines increases thermal efficiency and decreases NOx emission, while these operations inherently induce combustion instability and thus large cycle-to-cycle variation in engine. In order to stabilize combustion variations, the development of an advanced ignition system is becoming critical. To quantify the impact of spark-ignition discharge, ignitability tests were conducted in an optically accessible combustion vessel to characterize the flame kernel development of lean methane-air mixture with CO₂ simulating exhaust diluent. A shrouded fan was used to generate turbulence in the vicinity of J-gap spark plug and a Variable Output Ignition System (VOIS) capable of producing a varied set of spark discharge patterns was developed and used as an ignition source. The main feature of the VOIS is to vary the secondary current during glow discharge including naturally decaying and truncated with multiple strikes.

Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

A copula-based approach for model bias characterization was previously proposed [18] aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to preprocess data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

Simulation based design optimization has become the common practice in automotive product development. Increasing computer models are developed to simulate various dynamic systems. Before applying these models for product development, model validation needs to be conducted to assess their validity. In model validation, for the purpose of obtaining results successfully, it is vital to select or develop appropriate metrics for specific applications. For dynamic systems, one of the key obstacles of model validation is that most of the responses are functional, such as time history curves. This calls for the development of a metric that can evaluate the differences in terms of phase shift, magnitude and shape, which requires information from both time and frequency domain. And by representing time histories in frequency domain, more intuitive information can be obtained, such as magnitude-frequency and phase-frequency characteristics.

Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.

One of the major challenges in multiobjective, multidisciplinary design optimization (MDO) is the long computational time required in evaluating the new designs' performances. To shorten the cycle time of product design, a data mining-based strategy is developed to improve the efficiency of heuristic optimization algorithms. Based on the historical information of the optimization process, clustering and classification techniques are employed to identify and eliminate the low quality and repetitive designs before operating the time-consuming design evaluations. The proposed method improves design performances within the same computation budget. Two case studies, one mathematical benchmark problem and one vehicle side impact design problem, are conducted as demonstration.

Ultrasonic fatigue tests (testing frequency around 20 kHz) have been conducted on four different cast aluminum alloys each with a distinct composition, heat treatment, and microstructure. Tests were performed in dry air, laboratory air and submerged in water. For some alloys, the ultrasonic fatigue lives were dramatically affected by the environment humidity. The effects of different factors like material composition, yield strength, secondary dendrite arm spacing and porosity were investigated; it was concluded that the material strength may be the key factor influencing the environmental humidity effect in ultrasonic fatigue testing. Further investigation on the effect of chemical composition, especially copper content, is needed.

Regulated emissions, CO2-values, comfort, good driveability, high reliability and costs, this is the main frame for all future powertrain developments. In this frame, the diesel powertrain, not only for passenger cars, but also for commercial vehicle applications, faces some challenges in order to fulfil the future European and current US emission legislations while keeping the fuel consumption benefit, good driveability and an acceptable cost frame. One of these challenges is the varying fuel qualities of diesel fuel in different countries including different cetane number, volatility, sulphur content and different molecular composition. In addition to that in the future, more and more alternative fuels with various fuel qualities and properties will be launched into the market for economical and environmental reasons. At present, the control algorithms of the injection system applied in most diesel engines is open loop control.

Torque and performance requirements of Diesel engines are continually increasing while lower emissions and fuel consumption are demanded, thus increasing thermal and mechanical loads of the main components. The level of peak firing pressure is approaching 200 bar (even higher in Heavy Duty Diesel engines), consequently, a structural optimization of crankcase, crank train components and in particular of the cylinder head is required to cope with the increasing demands. This report discusses design features of cylinder head concepts which have the capability for increasing thermal and mechanical loads in modern Diesel engines

Within a public founded project test cell investigations were undertaken to identify parameters which predominantly influence the development of critical deposits in injection nozzles. A medium-duty diesel engine was operated in two different coking cycles with a zinc-free lubricant. One of the cycles is dominated by rated power, while the second includes a wide area of the operation range. During the experiments the temperatures at the nozzle tip, the geometries of the nozzle orifice and fuel properties were varied. For a detailed analysis of the deposits methods of electron microscopy were deployed. In the course of the project optical access to all areas in the nozzle was achieved. The experiments were evaluated by means of the monitoring of power output and fuel flow at rated power. The usage of a SEM (scanning electron microscope) and a TEM (transmission electron microscope) revealed images of the deposits with a magnification of up to 160 000.

This study demonstrates the use of pressure sensing technology to predict the crash severity of frontal impacts. It presents an investigation of the pressure change in the front structural elements (bumper, crush cans, rails) during crash events. A series of subsystem tests were conducted in the laboratory that represent a typical frontal crash development series and provided empirical data to support the analysis of the concept. The pressure signal energy at different sensor mounting locations was studied and design concepts were developed for amplifying the pressure signal. In addition, a pressure signal processing methodology was developed that relies on the analysis of the air flow behavior by normalizing and integrating the pressure changes. The processed signal from the pressure sensor is combined with the restraint control module (RCM) signals to define the crash severity, discriminate between the frontal crash modes and deploy the required restraint devices.

Gas Metal Arc Welding (GMAW) is widely employed for joining relatively thick sheet steels in automotive body-in-white structures and frames. The GMAW process is very flexible for various joint geometries and has relatively high welding speed. However, fatigue failures can occur at welded joints subjected to various types of loads. Thus, vehicle design engineers need to understand the fatigue characteristics of welded joints produced by GMAW. Currently, automotive structures employ various advanced high strength steels (AHSS) such as dual-phase (DP) and transformation-induced plasticity (TRIP) steels to produce lighter vehicle structures with improved safety performance and fuel economy, and reduced harmful emissions. Relatively thick gages of AHSS are commonly joined to conventional high strength steels and/or mild steels using GMAW in current body-in-white structures and frames.

The r-value is a very important parameter in the forming simulations of high strength steels, especially for steels with prominent anisotropy. R-values for sheet steels conventionally measured by extensometers were found neither consistent nor accurate due to difficulties in measuring the width strain. In this study, the Digital Image Correlation (DIC) technique was applied to determine r-values in Longitudinal (L), Transverse (T) and Diagonal (D) directions for cold rolled DP980 GI, DP780 GI, DP600 GI and BH250 GI sheet steels. The r-values measured from DIC were validated by finite element analysis (FEA) of a uniaxial tensile test for BH250. The simulation results of the load-displacement for two plasticity models were compared to experimental data, with one being the isotropic yield (von-Mises) and the other being an anisotropic model (Hill-48) using the r-value measured from DIC.

Current progress in the development of diesel engines substantially contributes to the reduction of NOx and Particulate Matter (PM) emissions but will not succeed to eliminate the application of Diesel Particulate Filters (DPFs) in the future. In the past we have introduced a Multi-Functional Reactor (MFR) prototype, suitable for the abatement of the gaseous and PM emissions of the Low Temperature Combustion (LTC) engine operation. In this work the performance of MFR prototypes under both conventional and advanced combustion engine operating conditions is presented. The effect of the MFR on the fuel penalty associated to the filter regeneration is assessed via simulation. Special focus is placed on presenting the performance assessment in combination with the existing differences in the morphology and reactivity of the soot particles between the different modes of diesel engine operation (conventional and advanced). The effect of aging on the MFR performance is also presented.

High cycle fatigue tests at a constant positive mean stress have been performed on a Al-Si-Cu cast aluminum alloy. The Random Fatigue Limit (RFL) model was employed to fit the probabilistic S-N curves based on Maximum Likelihood Estimate (MLE). Fractographic studies indicated that fatigue cracks in most specimens initiate from oxide films located at or very close to specimen surface. The RFL model was proved to be able to accurately capture the scatter in fatigue life. The cumulative density function (CDF) of fatigue life determined by RFL fit is found to be approximately equal to the complementary value of the CDF of the near-surface fatigue initiator size.

Rare earths are a group of elements whose availability has been of concern due to monopolistic supply conditions and environmentally unsustainable mining practices. To evaluate the risks of rare earths availability to automakers, a first step is to determine raw material content and value in vehicles. This task is challenging because rare earth elements are used in small quantities, in a large number of components, and by suppliers far upstream in the supply chain. For this work, data on rare earth content reported by vehicle parts suppliers was assessed to estimate the rare earth usage of a typical conventional gasoline engine midsize sedan and a full hybrid sedan. Parts were selected from a large set of reported parts to build a hypothetical typical mid-size sedan. Estimates of rare earth content for vehicles with alternative powertrain and battery technologies were made based on the available parts' data.