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Main topics are the development and the build-up of an 18ton hybrid truck with a parallel hybrid drivetrain. With this truck it is possible to drive up to 3 kilometers in the pure electric driving mode. Presenter Andreas Eglseer, Engineering Center Steyr GmbH & Co. KG

There are now a wide variety of Hybrid and Electric Vehicles in or near production. They reduce or displace petroleum consumption with of various combinations of conventional IC engine, mechanical transmission, liquid fuel storage, electrical energy storage, electrical and electro-mechanical energy conversion, and vehicle-to-grid energy interface. These Electrified types of vehicles include Mild Hybrid, Full Hybrid, Plug-In Hybrid, Extended Range Electric, and Battery Electric. Some types differ in their actual usability for the real mixes of driving trips, and further that differ in their effectiveness to reduce or displace fuel in actual real world driving use. Vehicle size is also a factor in total vehicle utility in transporting people. If we may segment drivers by their driving needs, in each segment, we see a particular type of electrified vehicle that is better suited than others at minimizing fuel cost and petroleum consumption for the purposes of transporting people.

The development of PM and NOx reduction system with the combination of DOC included DPF and SCR catalyst in addition to the AOC sub-assembly for NH3 slip protection is described. DPF regeneration strategy and manual regeneration functionality are introduced with using ITH, HCI device on the EUI based EGR, VGT 12.3L diesel engine at the CVS full dilution tunnel test bench. With this system, PM and NOx emission regulation for JPNL was satisfied and DPF regeneration process under steady state condition and transient condition (JE05 mode) were successfully fulfilled. Manual regeneration process was also confirmed and HCI control strategy was validated against the heat loss during transient regeneration mode. Presenter Seung-il Moon

Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.

FlexRay is a time triggered automotive communication protocol that connects ECUs (Electronic Control Units) on which distributed automotive applications are executed. If exact agreement (e.g. on physical values measured by redundant sensors on different ECUs) must be reached in the presence of asymmetric communication faults, a byzantine agreement protocol like Signed Messages (SM) can be utilized. This paper gives examples of how byzantine faults can emerge in a FlexRay-based system and proposes optimizations for a FlexRay-specific implementation of the SM protocol. The protocol modifications allow for a reduction in the number of protocol messages under a slightly relaxed fault model, as well as for a reduction in the number of messages to be temporarily stored by the ECUs.

Quasi-static tensile properties of TRIP590 steels from three different manufacturers were investigated using digital image correlation (DIC). The focus was on the post-uniform elongation behavior which can be very different for steels of the same grade owing to different manufacturing processes. Miniature tensile specimens, cut at 0°, 45°, and 90° relative to the rolling direction, were strained to failure in an instrumented tensile stage. True stress-true strain curves were computed from digital strain gages superimposed on digital images captured from one gage section surface during tensile deformation. Microstructural phases in undeformed and fracture specimens were identified with optical microscopy using the color tint etching process. Fracture surface analyses conducted with scanning electron microscopy and energy dispersive spectroscopy were used to investigate microvoids and inclusions in all materials.

The statistical analysis of vehicle crash accident data is generally problematic. Data from commonly used sources is almost never without error and complete. Consequently, many analyses are contaminated with modeling and system identification errors. In some cases the effect of influential factors such as crash severity (the most significant component being speed) driver behavior prior to the crash, etc. on vehicle and occupant outcome is not adequately addressed. The speed that the vehicle is traveling at the initiation of a crash is a significant contributor to occupant risk. Not incorporating it may make an accident analysis irrelevant; however, despite its importance this information is not included in many of the commonly used crash data bases, such as the Fatality Analysis Reporting System (FARS). Missing speed information can result in potential errors propagating throughout the analysis, unless a method is developed to account for the missing information.

Ethanol for use in automotive fuels can be made from renewable feedstocks, which contributes to its increased use in recent years. There are many differences in physical and chemical properties between ethanol and petrochemicals refined from fossil oil. One of the differences is its energy content. The energy content, or heating value, is an important property of motor fuel, since it directly affects vehicle fuel economy. While the energy content can be measured by combustion of the fuel in a bomb, the test is time-consuming and expensive. It is generally satisfactory and more convenient to estimate that property from other commonly-measured fuel properties. Several standardized empirical methods have been developed in the past for estimating the energy content of hydrocarbon fuels such as gasoline, diesel fuel, and jet fuel.

Regenerative braking is one of the key enablers of improved energy efficiency and extension of driving range in parallel and series hybrid, and electric-only vehicles. It is still used in conjunction with friction brakes, due to the enormous amount of energy dissipated in maximum effort stops (and the lack of a competitive alternate technology to accommodate this power level), and to provide braking when on-board energy storage/dissipation devices cannot store enough energy to support braking. Although vehicles equipped with regenerative braking are becoming more and more commonly available, there is little published research on what the dramatic reduction in friction brake usage means to the function of the friction brakes themselves. This paper discusses -with supporting data from analysis and physical tests - some of the considerations for friction brakes related to usage on vehicles with regenerative braking, including corrosion, off-brake wear, and friction levels.

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.

Superior NVH performance is a key focus in the development of new powertrains. In recent years, computer simulations have gained an increasing role in the design, development, and optimization of powertrain NVH at component and system levels. This paper presents the results of a study carried out on a 4-cylinder in-line spark-ignition engine with focus on growl noise. Growl is a low frequency noise (300-700 Hz) which is primarily perceived at moderate engine speeds (2000-3000 rpm) and light to moderate throttle tip-ins. For this purpose, a coupled and fully flexible multi-body dynamics model of the powertrain was developed. Structural components were reduced using component mode synthesis and used to determine dynamics loads at various engine speeds and loading conditions. A comparative NVH assessment of various crankshaft designs, engine configurations, and in- cylinder gas pressures was carried out.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

In this paper a design methodology for automotive heat exchangers has been applied which brings robustness into the design process and helps to optimize the design goals: as to maintain an optimal coolant temperature and to limit the vehicle underhood air temperature within a tolerable limit. The most influential design factors for the heat exchangers which affect the goals have been identified with that process. The paper summarizes the optimization steps necessary to meet the optimal functional goals for the vehicle as mentioned above. Taguchi's [1] Design for Six Sigma (DFSS) methods have been employed to conduct this analysis in a robust way.

In this paper, thermal models are developed based on experimental test data, and the physics of thermal systems. If experimental data is available, the data can be fitted to mathematical models that represent the system response to changes in its input parameters. Therefore, empirical models which are based on test data are developed. The concept of time constant is presented and applied to development of transient models. Mathematical models for component temperature changes during transient vehicle driving conditions are also presented. Mathematical models for climate control system warm up and cool-down are also discussed. The results show the significance of adopting this concept in analysis of vehicle test data, and in development of analytical models. The developed models can be applied to simulate the system or component response to variety of changes in input parameters. As a result, significant testing and simulation time can be saved during the vehicle development process.

Taguchi method is a technology to prevent quality problems at early stages of product development and product design. Parameter design method is an important part in Taguchi method which selects the best control factor level combination for the optimization of the robustness of product function against noise factors. The air induction system (AIS) provides clean air to the engine for combustion. The noise radiated from the inlet of the AIS can be of significant importance in reducing vehicle interior noise and tuning the interior sound quality. The porous duct has been introduced into the AIS to reduce the snorkel noise. It helps with both the system layout and isolation by reducing transmitted vibration. A CAE simulation procedure has been developed and validated to predict the snorkel noise of the porous ducted AIS. In this paper, Taguchi's parameter design method was utilized to optimize a porous duct design in an AIS to achieve the best snorkel noise performance.

Accurate numerical prediction of an engine thermal map at a wide range of engine operating conditions can help tune engine performance parameters at an early development stage. This study documents the correlation of an engine thermal simulation using the conjugate heat transfer (CHT) methodology with thermocouple data from an engine operating in a dynamometer and a vehicle drive cell. Three different operating conditions are matched with the simulation data. Temperatures predicted by simulation at specific sections, both at the intake and the exhaust sides of the engine are compared with the measured temperatures in the same location on the operating engine.

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.