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This paper includes analysis results for the control strategy of the Peugeot 3008 Hybrid4, a diesel-electric hybrid vehicle, under different thermal conditions. The analysis was based on testing results obtained under the different thermal conditions in the Advanced Powertrain Research Facility (APRF) at Argonne National Laboratory (ANL). The objectives were to determine the principal concepts of the control strategy for the vehicle at a supervisory level, and to understand the overall system behavior based on the concepts. Control principles for complex systems are generally designed to maximize the performance, and it is a serious challenge to determine these principles without detailed information about the systems. By analyzing the test results obtained in various driving conditions with the Peugeot 3008 Hybrid4, we tried to figure out the supervisory control strategy.

In order to ensure the safety of a structure, adequate strength for structural elements must be provided. Moreover, catastrophic deformations such as buckling must be prevented. Using the linear finite element method, deterministic buckling analysis is completed in two main steps. First, a static analysis is performed using an arbitrary ordinate applied loading pattern. Using the obtained element axial forces, the geometric stiffness of the structure is assembled. Second, an eigenvalue problem is performed between structure's elastic and geometric stiffness matrices, yielding the structure's critical buckling loads. However, these deterministic approaches do not consider uncertainty the structure's material and geometric properties. In this work, a new method for finite element based buckling analysis of a structure with uncertainty is developed. An imprecise probability formulation is used to quantify the uncertainty present in the mechanical characteristics of the structure.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

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.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Cavitation plays an important role in fuel injection systems. It alters the nozzle's internal flow structure and discharge coefficient, and also contributes to injector wear. Quantitatively measuring and mapping the cavitation vapor distribution in a fuel injector is difficult, as cavitation occurs on very short time and length scales. Optical measurements of transparent model nozzles can indicate the morphology of large-scale cavitation, but are generally limited by the substantial amount of scattering that occurs between vapor and liquid phases. These limitations can be overcome with x-ray diagnostics, as x-rays refract, scatter and absorb much more weakly from phase interfaces. Here, we present an overview of some recent developments in quantitative x-ray diagnostics for cavitating flows. Measurements were conducted at the Advanced Photon Source at Argonne National Laboratory, using a submerged plastic test nozzle.

Advanced compression ignition (ACI) operation in gasoline direct injection (GDI) engines is a promising concept to reduce fuel consumption and emissions at part load conditions. However, combustion phasing control and the limited operating range in ACI mode are a perennial challenge. In this study the combined impact of fuel properties and engine control strategies in ACI operation are investigated. A design of experiments method was implemented using a three level orthogonal array to determine the sensitivity of engine control parameters on the engine load, combustion noise and stability under low load ACI operation for three RON 98 gasoline fuels, each exhibiting disparate chemical composition. Furthermore, the thermodynamic state of the compression histories was studied with the aid of the pressure-temperature framework.

Microstructure level inhomogeneities between the harder martensite phase and the softer ferrite phase render the dual phase (DP) steels more complicated failure mechanisms and associated failure modes compared to the conventionally used low alloy homogenous steels. This paper examines the failure mode DP780 steel under different loading conditions using finite element analyses on the microstructure levels. Micro-mechanics analyses based on the actual microstructures of DP steel are performed. The two-dimensional microstructure of DP steel was recorded by scanning electron microscopy (SEM). The plastic work hardening properties of the ferrite phase was determined by the synchrotron-based high-energy X-ray diffraction technique. The work hardening properties of the martensite phase were calibrated and determined based on the uniaxial tensile test results. Under different loading conditions, different failure modes are predicted in the form of plastic strain localization.

Previous studies and on-road driving by consumers have shown that Hybrid Electric Vehicle fuel economy is very dependent on driver demand in both vehicle speed and vehicle acceleration [1]. The emerging technology of Plug-In Hybrid Vehicles (PHEV) may prove to also be more sensitivity to aggressive driver demand as compared to conventional internal combustion engine vehicles. This is due to the exceptional ability of the PHEV to minimize fuel consumption at mid to low power levels by the significant use of electric propulsion which enables engine downsizing. As vehicle speed and acceleration increase so does the power demand on the powertrain. The fuel consumption is directly affected by this increase in power demand level. To examine the fuel consumption impact of changing driver characteristics on PHEV’s, testing is conducted on two vehicles (parallel PHEV and power-split PHEV) on a four wheel chassis dynamometer at Argonne’s Advanced Powertrain Research Facility.

Hybrid electric vehicles (HEVs) combine two sources of energy and offer a wide variety of component and drivetrain configurations. However, optimizing the blending of these two energy sources is complex. Argonne National Laboratory (ANL) working with the Partnership for a New Generation of Vehicles (PNGV), maintains hybrid vehicle simulation software, the PNGV System Analysis Toolkit (PSAT). PSAT allows users to choose the best configuration and to optimize the control strategy in simulations. The importance of component models and the complexity involved in setting up optimized control laws require validation of the models and control strategies developed in PSAT. In this paper, we first describe our capability to validate each component model with an actual component test, using test stand facilities. Once each component model has been validated, ANL can perform tests on a whole HEV by using a chassis dynamometer.

Gasoline is a complex fuel. Many of the constituents of gasoline that are beneficial for the internal combustion engine (ICE) are expected to be challenging for on-board reformers in fuel-cell vehicles. To address these issues, the autothermal reforming of gasoline and individual components of gasoline has been investigated. The results indicate that aromatic components require higher temperatures and longer contact times to reform than paraffinic components. Napthenic components require higher temperatures to reform, but can be reformed at higher space velocities than paraffinic components. The effects of sulfur are dependent on the catalyst. These results suggest that further evolution of gasoline could reduce the demands on the reformer and provide a better fuel for a fuel-cell vehicle.

Argonne National Laboratory (ANL), working with the Partnership for a New Generation of Vehicles (PNGV), maintains hybrid vehicle simulation software, the PNGV System Analysis Toolkit (PSAT). PSAT, originally proprietary, has been used by both DOE and the “Big Three” as a modeling tool. The number of PSAT users has increased recently because 15 universities participating in the 2001 FutureTruck competition were given the software for their use. PSAT allows companies to look at new types of vehicles (hybrids) and choose the best configuration according to customer expectations within a minimum of time. PSAT, a forward-looking model, allows the user to simulate a large number of different configurations (conventional, series, parallel, and power split). PSAT is well suited for development of control strategies; by using accurate dynamics component models as its code, PSAT can be implemented directly and tested at the bench scale or in a vehicle.

This paper performs a parametric analysis of the influence of numerical grid resolution and turbulence model on jet penetration and mixture formation in a DI-H2 ICE. The cylinder geometry is typical of passenger-car sized spark-ignited engines, with a centrally located single-hole injector nozzle. The simulation includes the intake and exhaust port geometry, in order to account for the actual flow field within the cylinder when injection of hydrogen starts. A reduced geometry is then used to focus on the mixture formation process. The numerically predicted hydrogen mole-fraction fields are compared to experimental data from quantitative laser-based imaging in a corresponding optically accessible engine. In general, the results show that with proper mesh and turbulence settings, remarkable agreement between numerical and experimental data in terms of fuel jet evolution and mixture formation can be achieved.

This work details two approaches for evaluating transmission warming technology: experimental dynamometer testing and development of a simplified transmission efficiency model to quantify effects under varied real world ambient and driving conditions. Two vehicles were used for this investigation: a 2013 Ford Taurus and a highly instrumented 2011 Ford Fusion (Taurus and Fusion). The Taurus included a production transmission warming system and was tested over hot and cold ambient temperatures with the transmission warming system enabled and disabled. A robot driver was used to minimize driver variability and increase repeatability. Additionally the instrumented Fusion was tested cold and with the transmission pre-heated prior to completing the test cycles. These data were used to develop a simplified thermally responsive transmission model to estimate effects of transmission warming in real world conditions.

The fuel spray behavior in the near nozzle region of a gasoline injector is challenging to predict due to existing pressure gradients and turbulences of the internal flow and in-nozzle cavitation. Therefore, statistical parameters for spray characterization through experiments must be considered. The characterization of spray velocity fields in the near-nozzle region is of particular importance as the velocity information is crucial in understanding the hydrodynamic processes which take place further downstream during fuel atomization and mixture formation. This knowledge is needed in order to optimize injector nozzles for future requirements. In this study, the results of three experimental approaches for determination of spray velocity in the near-nozzle region are presented. Two different injector nozzle types were measured through high-speed shadowgraph imaging, Laser Doppler Anemometry (LDA) and X-ray imaging.

Actual combustion strategies in internal combustion engines rely on fast and accurate injection systems to be successful. One of the injector designs that has shown good performance over the past years is the direct-acting piezoelectric. This system allows precise control of the injector needle position and hence the injected mass flow rate. Therefore, understanding how nozzle flow characteristics change as function of needle dynamics helps to choose the best lift law in terms of delivered fuel for a determined combustion strategy. Computational fluid dynamics is a useful tool for this task. In this work, nozzle flow of a prototype direct-acting piezoelectric has been simulated by using CONVERGE. Unsteady Reynolds-Averaged Navier-Stokes approach is used to take into account the turbulence. Results are compared with experiments in terms of mass flow rate. The nozzle geometry and needle lift profiles were obtained by means of X-rays in previous works.

Today’s value proposition of plug-in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV) remain expensive. While the cost of lithium batteries has significantly decreased over the past few years, more improvement is necessary for PHEV and BEV to penetrate the mass market. However, the technology and cost improvements of the primary components used in electrified vehicles such as batteries, electric machines and power electronics have far exceeded the improvements in the main components used in conventional vehicles and this trend is expected to continue for the foreseeable future. Today’s weight and cost structures of electrified vehicles differ substantially from that of conventional vehicles but that difference will shrink over time. This paper highlights how the weight and cost structures, both in absolute terms and in terms of split between glider and powertrain, converge over time.

The primary strength of large eddy simulation (LES) is in directly resolving the instantaneous large-scale flow features which can then be used to study critical flame properties such as ignition, extinction, flame propagation and lift-off. However, validation of the LES results with experimental or direct numerical simulation (DNS) datasets requires the determination of statistically-averaged quantities. This is typically done by performing multiple realizations of LES and performing a statistical averaging among this sample. In this study, LES of n-dodecane spray flame is performed using a well-mixed turbulent combustion model along with a dynamic structure subgrid model. A high-resolution mesh is employed with a cell size of 62.5 microns in the entire spray and combustion regions. The computational cost of each calculation was in the order of 3 weeks on 200 processors with a peak cell count of about 22 million at 1 ms.

Over the past couple of years, numerous Hybrid Electric Vehicle (HEV) powertrain configurations have been introduced into the marketplace. Currently, the dominant architecture is the power-split configuration, notably the input splits from Toyota Motor Sales and Ford Motor Company. This paper compares two vehicle-level control strategies that have been developed to minimize fuel consumption while maintaining acceptable performance and drive quality. The first control is rules based and was developed on the basis of test data from the Toyota Prius as provided by Argonne National Laboratory's (Argonne's) Advanced Powertrain Research Facility. The second control is based on an instantaneous optimization developed to minimize the system losses at every sample time. This paper describes the algorithms of each control and compares vehicle fuel economy (FE) on several drive cycles.

Although many simulations and analyses of three-phase insulated gate bipolar transistor (IGBT) switching devices exist in the offline and post processing arenas, real-time simulation environments require varying levels of fidelity of real-time capable models, depending on the task at hand. This paper presents a comparison between existing basic real-time modeling techniques and more advanced techniques capable of simulating complex electrical characteristics in high fidelity, while retaining the capability of real-time simulation. Model development, simulation, and analysis of results was performed at Mississippi State University in an effort to better understand the effects of multiple brushless direct current (BLDC) IGBT inverters operating on the same high-voltage bus.