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The worldwide drive to improved energy efficiency for engine systems is being supported by several engine R&D programs at Southwest Research Institute (SwRI). This research includes large programs in major-market engine categories, such as heavy-duty, non-road, and light-duty; and includes diesel, gasoline, and alternative fuel aspects. This presentation describes several key diesel engine programs being pursued under the SwRI Clean High Efficiency Diesel Engine consortium (CHEDE-VI), whose goal is to demonstrate future diesel technology exceeding 50% brake thermal efficiency. Additionally, SwRI?s High Efficiency Dilute Gasoline Engines consortium (HEDGE-II), is reviewed, where advanced technology for ultra-high efficiency gasoline engines is being demonstrated. The HEDGE-II program is built upon dilute gasoline engine research, where brake thermal efficiencies in excess of 42% are being obtained for engines applicable to the light-duty market. Presenter Charles E.

Gasoline turbocharged direct injection (GTDI) engines, such as EcoBoost™ from Ford, are becoming established as a high value technology solution to improve passenger car and light truck fuel economy. Due to their high specific performance and excellent low-speed torque, improved fuel economy can be realized due to downsizing and downspeeding without sacrificing performance and driveability while meeting the most stringent future emissions standards with an inexpensive three-way catalyst. A logical and synergistic extension of the EcoBoost™ strategy is the use of E85 (approximately 85% ethanol and 15% gasoline) for knock mitigation. Direct injection of E85 is very effective in suppressing knock due to ethanol's high heat of vaporization - which increases the charge cooling benefit of direct injection - and inherently high octane rating. As a result, higher boost levels can be achieved while maintaining optimal combustion phasing giving high thermal efficiency.

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).

The paper discusses the concept, design and final results from the ‘Ultra Boost for Economy’ collaborative project, which was part-funded by the Technology Strategy Board, the UK's innovation agency. The project comprised industry- and academia-wide expertise to demonstrate that it is possible to reduce engine capacity by 60% and still achieve the torque curve of a modern, large-capacity naturally-aspirated engine, while encompassing the attributes necessary to employ such a concept in premium vehicles. In addition to achieving the torque curve of the Jaguar Land Rover naturally-aspirated 5.0 litre V8 engine (which included generating 25 bar BMEP at 1000 rpm), the main project target was to show that such a downsized engine could, in itself, provide a major proportion of a route towards a 35% reduction in vehicle tailpipe CO2 on the New European Drive Cycle, together with some vehicle-based modifications and the assumption of stop-start technology being used instead of hybridization.

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.

To avoid frequent regeneration intervals leading to expeditious ageing of the catalyst and substantial fuel penalty for the owner, it is always desired to estimate the soot coming from diesel exhaust emission, the soot accumulated and burnt in the Diesel Particulate Filter (DPF). Certain applications and vehicle duty cycles cannot make use of the differential pressure sensor for estimating the soot loading in the DPF because of the limitations of the sensor tolerance and measurement accuracy. The physical soot model is always active and hence a precise and more accurate model is preferred to calibrate & optimize the regeneration interval. This paper presents the approach to estimate the engine-out soot and the accumulated soot in the DPF using a graphical calculation tool (AVL Concerto CalcGraf™).

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.

In the present study, Large Eddy Simulations (LES) have been performed with a 3D model of a step nozzle injector, using n-pentane as the injected fluid, a representative of the high-volatility components in gasoline. The influence of fuel temperature and injection pressure were investigated in conditions that shed light on engine cold-start, a phenomenon prevalent in a number of combustion applications, albeit not extensively studied. The test cases provide an impression of the in-nozzle phase change and the near-nozzle spray structure across different cavitation regimes. Results for the 20oC fuel temperature case (supercavitating regime) depict the formation of a continuous cavitation region that extends to the nozzle outlet. Collapse-induced pressure wave dynamics near the outlet cause a transient entrainment of air from the discharge chamber towards the nozzle.

Throttling loss of downsized gasoline engines is significantly smaller than that of naturally aspirated counterparts. However, even the extremely downsized gasoline engine can still suffer a relatively large throttling loss when operating under part load conditions. Various de-throttling concepts have been proposed recently, such as using a FGT or VGT turbine on the intake as a de-throttling mechanism or applying valve throttling to control the charge airflow. Although they all can adjust the mass air flow without a throttle in regular use, an extra component or complicated control strategies have to be adopted. This paper will, for the first time, propose a de-throttling concept in a twin-charged gasoline engine with minimum modification of the existing system. The research engine model which this paper is based on is a 60% downsized 2.0L four cylinder gasoline demonstrator engine with both a supercharger and turbocharger on the intake.

To reduce the fuel consumption as well as to improve the crash safety of vehicles, the usage of hot stamping parts is increasing dramatically in recent years. Aisin Takaoka has produced hot stamping parts since 2001 and has developed various technologies related to Hot Stamping. In an actual hot stamping process, parts with insufficient strength could be produced sometimes at a prototyping phase, even under the proper forming conditions. In order to understand these phenomena, in this paper, phase transformation in a boron steel 22MnB5 under various cooling rates were investigated and the effects of pre-strain conditions on the phase transformations were characterised. Uniaxial tensile specimens were stretched under isothermal conditions to different strain levels of 0-0.3, at strain rates of 0.1-5.0/s and deformation temperatures of 650-800°C.

In the Big Data era, the capability in statistical and probabilistic data characterization, data pattern identification, data modeling and analysis is critical to understand the data, to find the trends in the data, and to make better use of the data. In this paper the fundamental probability concepts and several commonly used probabilistic distribution functions, such as the Weibull for spectrum events and the Pareto for extreme/rare events, are described first. An event quadrant is subsequently established based on the commonality/rarity and impact/effect of the probabilistic events. Level of measurement, which is the key for quantitative measurement of the data, is also discussed based on the framework of probability. The damage density function, which is a measure of the relative damage contribution of each constituent is proposed. The new measure demonstrates its capability in distinguishing between the extreme/rare events and the spectrum events.

This article presents strategies for evaluating the mean, variance, and failure probability of a response variable given measurements subject to both epistemic and aleatory uncertainties. We focus on a case in which standard sensor calibration techniques cannot be used to eliminate measurement error since the uncertainties affecting the metrology system depend upon the measurement itself (e.g., the sensor bias is not constant and the measurement noise is colored). To this end, we first characterize all possible realizations of the true response that might have led to each of such measurements. This process yields a surrogate of the data for the unobservable true response taking the form of a random variable. Each of these variables, called a Random Datum Model (RDM), is manufactured according to a measurement and to the underlying structure of the uncertainty.

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, proton exchange membrane (PEM) fuel cell is widely seen as a promising energy conversion device especially for transportation application scenario because of its high efficiency, low operation temperature and nearly-zero road emission. Extensive modeling work have been done based on different dimensions during the past decades, including one-dimensional (1D), two-dimensional (2D), three-dimensional (3D) and intermediate combinations in between (e.g. “1+1D”). 1D model benefits from a rationally-chosen set of assumptions to obtain excellent calculation efficiency, yet at the cost of accuracy to some extent. In contrast, 3D model has great advantage over 1D model on acquiring more comprehensive information inside the fuel cell. For macro-scale modeling work, one compromise aiming to realize both acceptable computation speed and reasonable reflection of cell operation state is to simplify the membrane electrode assembly (MEA).

Fuel injection is a key process influencing the performance of Gasoline Direct Injection (GDI) Engines. Injecting fuel at elevated temperature can initiate flash boiling which can lead to faster breakup, reduced penetration, and increased spray-cone angle. Thus, it impacts engine efficiency in terms of combustion quality, CO2, NOx and soot emission levels. This research deals with modelling of flash boiling processes occurring in gasoline fuel injectors. The flashing mass transfer rate is modelled by the advanced Hertz-Knudsen model considering the deviation from the thermodynamic-equilibrium conditions. The effect of nucleation-site density and its variation with degree of superheat is studied. The model is validated against benchmark test cases and a substantiated comparison with experiment is achieved.

Following market demands for a niche balance between engine performance and legislation requirement, a new-concept compressor scroll has been designed for small to medium size passenger cars. The design adopts a slight deviation from the conventional method, thus resulting in broader surge margin and better efficiency at off-design region. This paper presents the performance evaluation of the new compressor scroll on the cold-flow gas-stand followed by the on-engine testing. The testing program focused on back-to-back comparison with the standard compressor scroll, as well as identifying on-engine operational regime with better brake specific fuel consumption (BSFC) and transient performance. A specially instrumented 1.6L gasoline engine was used for this study. The engine control unit configuration is kept constant in both the compressor testing.

In relation to further tightening of the emissions legislation for on-road heavy duty Diesel engines, the future potential of cooled exhaust gas recirculation (EGR) as a result of developments in the cooling systems of such engines has been evaluated. Four basic engine concepts were investigated: an engine with SCR exhaust gas aftertreatment for control of the nitrogen oxides (NOx), an engine with cooled EGR and particulate (PM) filtration, an engine with low pressure EGR and PM filtration and an engine with two stage low temperature cooled EGR also with a particulate filter. A 10.5 litre engine was calibrated and tested under conditions representative for each concept, such that 1.7 g/kWh (1.3 g/bhp-hr) NOx could be achieved over the ESC and ETC. This corresponds to emissions 15% below the Euro 5 legislation level.

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.

This paper presents a novel battery degradation model based on empirical data from the Racing Green Endurance project. Using the rainflow-counting algorithm, battery charge and discharge data from an electric vehicle has been studied in order to establish more reliable and more accurate predictions for capacity and power fade of automotive traction batteries than those currently available. It is shown that for the particular lithium-iron phosphate (LiFePO₄) batteries, capacity fade is 5.8% after 87 cycles. After 3,000 cycles it is estimated to be 32%. Both capacity and power fade strongly depend on cumulative energy throughput, maximum C-rate as well as temperature.