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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 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.

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.

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.

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.

Shock waves have been recently observed in high-pressure diesel sprays. In this paper, three-dimensional numerical simulations of supersonic diesel spray injection have been performed to investigate the underlying dynamics of the induced shock waves and their interactions with the spray. A Volume-of-Fluid based method in the CFD software (CONVERGE) is used to model this multiphase phenomena. An adaptive Mesh Refinement (AMR) scheme is employed to capture the front of the spray and the shock waves with high fidelity. Simulation results are compared to the available experimental observations to validate the numerical procedure. Parametric studies with different injection and ambient conditions are conducted to examine the effect of these factors on the generation of shock waves and their dynamics.

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 computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty compression-ignition engine with a gasoline-like fuel that has an anti-knock index (AKI) of 58. The primary goal was to design an optimized combustion system utilizing the high volatility and low sooting tendency of the fuel for improved fuel efficiency with minimal hardware modifications to the engine. The CFD model predictions were first validated against experimental results generated using the stock engine hardware. A comprehensive design of experiments (DoE) study was performed at different operating conditions on a world-leading supercomputer, MIRA at Argonne National Laboratory, to accelerate the development of an optimized fuel-efficiency focused design while maintaining the engine-out NOx and soot emissions levels of the baseline production engine.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

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.

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 Reynolds stress turbulence model (RSM) has been developed to go beyond the Boussinesq hypothesis and to improve turbulence modeling of flows with significant mean streamline curvature and secondary flow. In this paper the RSM in commercial CFD software CONVERGE is tested for its performance and robustness when applying to complex flows. Several validation cases including flow over flat plate, vortex combustor, diesel engine spray and combustion were selected to test the RSM. The swirling flow in vortex combustor, non-reacting but vaporizing ECN Spray A (free jet) and Sandia small bore diesel engine case are used to demonstrate the benefits of the RSM over the widely used RNG k-epsilon model without model tuning. The vortex combustor case shows the RSM can provide good prediction for strong swirling flow. ECN spray A case was used to demonstrate that the RSM can accurately predict the liquid and vapor penetration lengths of a free jet under diesel engine conditions.

Many experiments have demonstrated that clutch overheating is a major cause of clutch deterioration. Clutch friction material deterioration not only leads to clutch failure, but also causes poor shift quality. Unfortunately, it is not practical to monitor each individual clutch temperature in a production vehicle due to high costs or technical challenges. This paper introduces a proposal for a virtual clutch temperature sensor to monitor the real time clutch temperature changes in Chrysler transmissions with PWM solenoid based control systems. Both vehicle and laboratory dynamometer (dyno) tests demonstrate that the model results match very closely with the thermocouple temperature measurements under many different driving conditions. The real time virtual temperature sensor provides a tool for clutch surface overheat protection and for design improvement and enhancement to shift quality.

In order to define and to optimize a thermal management system for a high voltage vehicular battery, it is essential to understand the environmental factors acting on the battery and their influence on battery life. This paper defines a calendar life aging model for a battery, and applies real world environmental and operating conditions to that model. Charge and usage scenarios are combined with various cooling/heating approaches. This set of scenarios is then applied to the calendar life model, permitting optimization of battery thermal management strategies. Real-world battery life can therefore be maximized, and trade-offs for grid energy conversion efficiency and fuel economy/vehicle range can be determined.

Proposed LEV-III emission level will require improvements in NMOG, CO and NOx emissions as measured over FTP and US06 emission cycles. Incremental improvements in washcoat technologies, cold start calibration and catalyst system design are required to develop a cost effective solution set. New catalyst technologies demonstrated both lower HC and NOx emissions with 25% less platinum group metals (PGM). FTP and US06 emissions were measured on a 4-cylinder 2.4L application which compares a close-coupled converter and close-coupled + underfloor converter systems. A PGM placement study was performed with the close-coupled converter system employing these new catalyst technologies. Emissions results suggest that the placement of PGM is critical in minimizing emissions and PGM costs.