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The aim of the paper is the comparison of the injection process with different fuels, i.e. a standard diesel fuel and a pure biodiesel. Multiphase cavitating flows inside diesel nozzles are analyzed by means of unsteady CFD simulations using a two-fluid approach with consideration of bubble dynamics, on moving grids from needle opening to closure. Two five-hole nozzles with cylindrical and conical holes are studied and their behaviors are discussed taking into account the different properties of the two fuels. Extent of cavitation regions is not much affected by the fuel type. Biodiesel leads to significantly higher mass flow only if the nozzle design induces significant cavitation which extends up to the outlet section and if the injector needle is at high lift. If the internal hole shaping is able to suppress cavitation, the stabilized mass flows are very similar with both fuels.

The success of stratified combustion is strongly determined by the injection and ignition system used. A large temporal and spatial variation of the main parameters - mixture composition and charge motion - in the vicinity of the spark location are driving the demands for significantly improved ignition systems. Besides the requirements for conventional homogeneous combustion systems higher ignition energy and breakdown voltage capability is needed. The spark location or spark plug gap itself has to be open and well accessible for the mixture to allow a successful flame kernel formation and growth into the stratified mixture regime, while being insensitive to potential interaction with liquid fuel droplets or even fuel film. For this purpose several different ignition concepts are currently being developed. The present article will give an ignition system overview for stratified combustion within Delphi Powertrain Systems.

This paper implements a coupled approach to integrate the internal nozzle flow and the ensuing fuel spray using a Volume-of-Fluid (VOF) method in the CONVERGE CFD software. A VOF method was used to model the internal nozzle two-phase flow with a cavitation description closed by the homogeneous relaxation model of Bilicki and Kestin [1]. An Eulerian single velocity field approach by Vallet et al. [2] was implemented for near-nozzle spray modeling. This Eulerian approach considers the liquid and gas phases as a complex mixture with a highly variable density to describe near nozzle dense sprays. The mean density is obtained from the Favreaveraged liquid mass fraction. The liquid mass fraction is transported with a model for the turbulent liquid diffusion flux into the gas.

Results from a wind tunnel testing program of a cab-over truck-trailer combination vehicle are presented. The model is scaled at 1:3, and represents an accurate replica of currently available trucks and trailers in Australia. Cooling intakes have not been modelled. Reynolds number independence is established to the maximum obtainable in the wind tunnel test configuration adopted equating to a full-scale forward speed of 57 km/h. The wind tunnel is a ¾ open jet facility with a nozzle area of 10.9m2. The vehicle is mounted on a turntable to a 6 component force balance. A range of vehicle add-on devices are investigated, including boat-tails, side skirts, cab extenders, air-dams and roof fairings. Drag measurements are presented over a yaw angle range of 10 degrees.

Full scale heavy vehicle aerodynamic testing requires a very large wind tunnel test section, with few wind tunnels having this capacity worldwide. Small scale testing often requires a loss of model detail as well as introducing Reynolds Number and compressibility effects. A ¾ open jet wind tunnel set-up has been developed at Monash University Wind Tunnel that enables testing of 1:3 scale truck-trailer models, of full-scale length up to 18 metres to be tested. The measured drag on longer vehicles is more strongly affected by horizontal buoyancy and long models create additional blockage when yawed. In addition the length of the model means that special care must be taken to ensure that shear layers emanating from the nozzle at the start of the test section are sufficiently separated from the shear layers and wake at the base of the truck.

Currently, conventional spark-ignition engines are unfit to satisfy the growing customer requirements on efficiency while complying with the legislations on pollutant emissions. New ignition systems are being developed to extend the engine stable operating range towards increasing lean conditions. Among these, the Radio-Frequency corona igniters represent an interesting solution for the capability to promote the combustion in a much wider region than the one involved by the traditional spark channel. Moreover, the flame kernel development is enhanced by means of the production of non-thermal plasma, where low-temperature active radicals are ignition promoters. However, at low pressure and at high voltage the low temperature plasma benefits can be lost due to occurrences of spark-like events. Recently, RF barrier discharge igniters (BDI) have been investigated for the ability to prevent the arc formation thanks to a strong-breakdown resistance.

Nowadays internal combustion engines can operate under lean combustion conditions to maximize efficiency, as long as combustion stability is guaranteed. The robustness of combustion initiation is one of the main issues of actual spark-ignition engines, especially at high level of excess-air or dilution. The enhancement of the in-cylinder global motion and local turbulence is an effective way to increase the flame velocity. During the ignition process, the excessive charge motion can hinder the spark discharge and eventually cause a misfire. In this perspective, the interaction between the igniter and the flow field is a fundamental aspect which still needs to be explored in more detail to understand how the combustion originates and develops. In this work, a combined experimental and numerical study is carried out to investigate the flow field around the spark gap, and its effect on the spark discharge evolution.

A thermo-mechanical fatigue analysis was conducted based on a coupled Finite Element Analysis (FEA) - Computational Fluid Dynamics (CFD) method on the crack failure of the exhaust manifold for an inline 4-cylinder turbo-charged diesel engine under the durability test. In the this analysis, the temperature-dependent material properties were obtained from measurements and the model was calibrated with comparison of the predicted exhaust manifold temperatures with the on-engine measurements under the same engine load condition. Temperature and stress/strain distributions in the exhaust manifold were predicted with the calibrated model. Analysis results showed that the cracks took place at locations with high plastic deformations, suggesting that the cause of the failure be thermo-mechanical fatigue (TMF). Using the equivalent plastic strain (PEEQ) as the indicator for thermal mechanical fatigue, three exhaust manifold design revisions were carried out by CAE analysis.

The increasing automation of driving functionalities is one of the most important trends in the automotive industry. The trend is moving towards systems which allow the driver to be absent from the active driving task. During the process, on one hand, the human driver more and more relies upon the driving automation to perform the dynamic driving tasks. Therefore, the driver needs to trust the driving automation. On the other hand, even the high driving automation (e.g. SAE Level 4) can only performs its functionality within the specific operational design domain and the driving automation relies upon the human driver to handle events when the vehicle operates outside the domain. What’s more, for the lower level driving automation, the driver still needs to assume some fallback responsibility, and may be required to react promptly when the driving automation even inside the operational design domain is inadequate to operate the vehicle.

This work involves modeling internal and near-nozzle flows of a gasoline direct injection (GDI) nozzle. The Engine Combustion Network (ECN) Spray G condition has been considered for these simulations using the nominal geometry of the Spray G injector. First, best practices for numerical simulation of the two-phase flow evolution inside and the near-nozzle regions of the Spray G injector are presented for the peak needle lift. The mass flow rate prediction for peak needle lift was in reasonable agreement with experimental data available in the ECN database. Liquid plume targeting angle and liquid penetration estimates showed promising agreement with experimental observations. The capability to assess the influence of different thermodynamic conditions on the two-phase flow nature was established by predicting non-flashing and flashing phenomena.

Onboard diagnostic regulations require performance monitoring of diesel particulate filters used in vehicle aftertreatment systems. Delphi has developed a particulate matter (PM) sensor to perform this function. The objective of this sensor is to monitor the soot (PM) concentration in the exhaust downstream of the diesel particulate filter which provides a means to calculate filter efficiency. The particulate matter sensor monitors the deposition of soot on its internal sensing element by measuring the resistance of the deposit. Correlations are established between the soot resistance and soot mass deposited on the sensing element. Currently, the sensor provides the time interval between sensor regeneration cycles, which, with the knowledge of the exhaust gas flow parameters, is correlated to the average soot concentration.

Selective Catalytic Reduction (SCR) diesel exhaust aftertreatment systems are virtually indispensable to meet NOx emissions limits worldwide. These systems generate the NH3 reductant by injecting aqueous urea solution (AUS-32/AdBlue®/DEF) into the exhaust for the SCR NOx reduction reactions. Understanding the AUS-32 injector spray performance is critical to proper optimization of the SCR system. Specifically, better knowledge is required of urea sprays under operating conditions including those where fluid temperatures exceed the atmospheric fluid boiling point. Results were previously presented from imaging of an AUS-32 injector spray which showed substantial structural differences in the spray between room temperature fluid conditions, and conditions where the fluid temperature approached and exceeded 104° C and “flash boiling” of the fluid was initiated.

Among plasma-assisted ignition technologies, the Radio-Frequency (RF) corona family represents an interesting solution for the ability to extend the engine operating range. These systems generate transient, non-thermal plasma, which is able to enhance the combustion onset by means of thermal, kinetic and transport effects. Streamer-type RF corona discharge, at about 1 MHz, ignites the air-fuel mixture in multiple filaments, resulting in many different flame kernels. The main issue of this system is that at high electrode voltage and low combustion chamber pressure a transition between streamer and arc easily occurs: in this case transient plasma benefits are lost. A barrier discharge igniter (BDI), supplied with the same RF energy input, instead, is more breakdown-resistant, so that voltage can be raised to higher levels. In this work, a streamer-type RF corona igniter and a BDI were tested in a single-cylinder optical engine fueled with gasoline.

The complexity of automotive software and the needs for shorter development time and software portability require the development of new approaches and standards for software architectures. The AUTOSAR project is one of the most comprehensive and promising solutions for defining a methodology supporting a function-driven development process. Furthermore, it manifests itself as a standard for expressing compatible software interfaces at the Application Layer. This paper discusses the implementation of AUTOSAR requirements for the component structure, as well as interfaces to the Application Layer in a model-based development environment. The paper outlines the major AUTOSAR requirements for software components, provides examples of their implementation in a Simulink/Stateflow model, and describes the modelbased implementation of an operating system for running AUTOSAR software executables (“runnables”).

In the present paper the results of an experimental and numerical analysis of a common-rail, high pressure Diesel spray evolving in high counter pressure conditions is reported. The experimental study was carried out mainly in terms of spray momentum flux indirect measurement by the spray impact method; the measurement of the impact force time-histories, along with the CFD analysis of the same phenomenon, gave interesting insight in the internal spray structure. As well known, the overall spray structure momentum flux along with the injection rate measurements can be used to derive significant details about the in-nozzle flow and cavitation phenomena intensity. The same global spray momentum and momentum flux measurement can be useful in determining the jet-to-jet un-uniformities also in transient, engine-typical injection conditions which can assist in the matching process between the injection system and the combustion chamber design.

While the potential emissions and efficiency benefits of HCCI combustion are well known, realizing the potentials on a production intent engine presents numerous challenges. In this study we focus on identifying challenges and opportunities associated with a production intent cam-based variable valve actuation (VVA) system on a multi-cylinder engine in comparison to a fully flexible, naturally aspirated, hydraulic valve actuation (HVA) system on a single-cylinder engine, with both platforms sharing the same GDI fueling system and engine geometry. The multi-cylinder production intent VVA system uses a 2-step cam technology with wide authority cam phasing, allowing adjustments to be made to the negative valve overlap (NVO) duration but not the valve opening durations. On the single-cylinder HVA engine, the valve opening duration and lift are variable in addition to the NVO duration. The content of this paper is limited to the low-medium operating load region at 2000 rpm.

Fuel economy has become an important consideration in forklift truck design, particularly in Europe. A simulation of the fuel consumption and performance of a forklift truck has been developed, validated and subsequently used to determine the energy consumed by individual powertrain components during drive cycles. The truck used in this study has a rated lifting capacity of 2500kg, and is powered by a 2.6 litre naturally aspirated diesel engine with a fuel pump containing a mechanical variable-speed governor. The drivetrain consisted of a torque convertor, hydraulic clutch and single speed transmission. AVL Cruise was used to simulate the vehicle powertrain, with coupled Mathworks Simulink models used to simulate the hydraulic and control systems and governor. The vehicle has been simulated on several performance and fuel consumption drive cycles with the main focus being the VDI 2198 fuel consumption drive cycle.

A new fuel injection strategy is proposed for DME engines. Under this strategy, a pre-injection up to 40% demand is conducted after intake valves closing. Due to high volatility of DME, a lean homogeneous mixture can be formed during the compression stroke. Near TDC, a pilot injection is conducted. Combined fuel mass for the pre-injection and pilot injection is under the lean combustion limit of DME. Thus, the mixture is enriched and combustion can take place only in the neighborhood of sprays of the pilot injection. The main injection is conducted after TDC. Because only about half of the demand needs to be injected and DME evaporates almost immediately, combustion duration for the main injection plus the unburnt fuel in the cylinder should not be long because a large portion of the fuel has been premixed with air. With a high EGR rate and proper timing for the main injection, low temperature combustion could be realized.

Artificial Intelligence is becoming very important and useful in several scientific fields. Machine learning methods, such as neural networks and decision trees, are often proposed in applications for internal combustion engines as virtual sensors, faults diagnosis systems and engine performance optimization. The high pressure of the intake air coupled with the demand of lean conditions, in order to reduce emissions, have often close relationship with the knock events. Fuels autoignition characteristics and flame front speed have a significant impact on knock phenomenon, producing high internal cylinder pressures and engine faults. The limitations in using pressure sensors in the racing field and the challenge to reduce the costs of commercial cars, push the replacement of a hardware redundancy with a software redundancy.

Battery packs for plug-in hybrid electrical vehicle (PHEV) applications can be characterized as high-capacity and high-power packs. For PHEV battery packs, their power and electrical-energy capacities are determined by the range of the electrical-energy-driven operation and the required vehicle drive power. PHEV packs often employ high-power lithium-ion (Li-ion) pouch cells with large cell capacity in order to achieve high packing efficiency. Lithium-ion battery packs for PHEV applications generally have a 96SnP configuration, where S is for cells in series, P is for cells in parallel, and n = 1, 2 or 3. Two PHEV battery packs with 355V nominal voltage and 25-kWh nominal energy capacity are studied. The first pack is assembled with 96 70Ah high-power Li-ion pouch cells in 96S1P configuration. The second pack is assembled with 192 35Ah high-power Li-ion pouch cells in 96S2P configuration.