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Urea-selective catalytic reduction (SCR) catalysts are the leading aftertreatment technology for diesel engines, but there are major challenges associated with meeting future NOx emission standards, especially under transient drive cycle conditions that include large swings in exhaust temperatures. Here we present a simplified, transient, one-dimensional integral model of NOx reduction by NH₃ on a commercial small-pore Cu-zeolite urea-SCR catalyst for which detailed kinetic parameters have not been published. The model was developed and validated using data acquired from bench reactor experiments on a monolith core, following a transient SCR reactor protocol. The protocol incorporates NH₃ storage, NH₃ oxidation, NO oxidation and three global SCR reactions under isothermal conditions, at three space velocities and at three NH₃/NOx ratios.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

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.

While gasoline surrogate development has progressed in the areas of more complex surrogate mixtures and in kinetic modeling tools and mechanism development, it is generally recognized that further development is still needed. This paper represents a small step in supporting this development by providing comparisons between experimental engine data and surrogate-based kinetic models. In our case, the HCCI engine data comes from a port-injected, single-cylinder research engine with intake-air heating for combustion phasing control. Timing sweeps were run at constant fuel rate for three market gasolines and five surrogate mixtures. Modeling was done using the CHEMKIN software with a gasoline mechanism set containing 1440 species and 6572 reactions. Five pure compounds were selected for the surrogate blends and include iso-octane, n-heptane, toluene, methylcyclohexane, and 1-hexene.

A two-stage PPCI-diffusion combustion process recently showed good potential to enable clean and fuel-efficient gasoline compression ignition (GCI) combustion at medium-to-high loads. By conducting closed-cycle 3-D CFD combustion analysis, a further step was undertaken in this work to evaluate and optimize the PPCI-diffusion combustion strategy at a full load operating point (2000rpm-23.5 bar IMEPcc) while keeping engine-out NOx below 1 g/kWh. The light-duty GCI engine used in this investigation featured a custom-designed piston bowl geometry at a 17.0 compression ratio (CR), a high pressure diesel fuel injection system, and advanced single-stage turbocharging. A split fuel injection strategy was used to enable the two-stage PPCI-diffusion combustion process. First, the injector spray pattern and swirl ratio effects were evaluated. In-cylinder air utilization and the PPCI-diffusion combustion process were notably influenced by the closed-cycle combustion system design.

With deflected-disc dampers, digressive force-velocity shapes are achieved via the combined effects of disc stack stiffness and hub-offset. The degree of digressiveness can be adjusted to alter vehicle performance by changing the proportion of these parameters. Optimizing this relationship can yield substantial vehicle performance improvements, but the time consuming iterative process of developing a new disc stack for each hub-offset discourages experimentation. To enable more efficient digressiveness comparisons, a regression-based computational method has been developed which converts disc stack stiffness from one hub-offset to other offsets directly, without iteration. Once an initial disc stack for one offset has been tuned by traditional methods, stacks for other offsets can be calculated that maintain overall damper control.

A simulation methodology is developed for the Constant Radius Constant Speed (CRCS) analysis to predict the ISO4138 [1] road test performance. The CRCS analysis can be used to predict the vehicle steady-state handling characteristics such as understeer, rear cornering compliance, and roll gradient, etc. The Yaw-Rate Control methodology is applied to replace the traditional driver-in-the-loop path-following approaches. Comparing to the path-following approaches, the proposed method is simpler to use, more efficient, accurate, and robust.

A displacement-based CAE analysis is applied to liftgate chucking noise problems. A CAE simulation model of a small-size sport utility vehicle (SUV) is simulated with a set of realistic road loads as a time transient simulation. The model contains a trimmed vehicle, a liftgate and structural body-liftgate interface components such as the latch-striker wire, contact wedges and slam bumpers. Simulation design of experiments (DOE) is carried out with the model. As performance measures, the relative displacements at the contact points of the interface components are selected, since they are considered the direct cause of liftgate chucking. As design variables, body structure stiffness, liftgate stiffness, liftgate opening stiffness, stiffness characteristics of the interface components and additional liftgate mass are selected. Results of the simulation DOE is post-processed, and response surface models (RSM) are fit for the performance measures.

This paper presents an alternative launch device for layshaft dual clutch transmissions (DCT's). The launch device incorporates a hydrodynamic torque converter, a lockup clutch with controlled slip capability and two wet multi-plate clutches to engage the input shafts of the transmission. The device is intended to overcome the deficiencies associated with using conventional dry or wet launch clutches in DCT's, such as limited torque capacity at vehicle launch, clutch thermal capacity and cooling, launch shudder, lubricant quality and requirement for interval oil changes. The alternative device enhances drive quality and performance at vehicle launch and adds the capability of controlled capacity slip to attenuate gear rattle without early downshifting. Parasitic torque loss will increase but is shown not to drastically influence fuel consumption compared to a dry clutch system, however synchronizer engagement can become a concern at cold operating temperatures.

Generally linear finite element analysis (FEA) is used to predict fatigue life of spot welded joints in a vehicle body structure. Therefore, the effect of plastic deformation at the vicinity of the spot welded joints is not included on fatigue prediction. This study introduces a simple technique to include the plastic deformation effect without performing elastic-plastic finite element analysis. The S-N curve obtained from fatigue test results is modified to consider this effect. Tensile strength test results of spot welded joint specimens were utilized to find the load range for FEA equivalent to the applied load range for fatigue tests. To demonstrate the proposed approach, fatigue test results of advanced high strength steels (AHSS) for lap-shear and coach peel specimens were used. Both the specimen types were tested at various constant amplitudes with the load ratios of R=0.1 and 0.3.

This project team conducted a life-cycle-based environmental evaluation of new, lightweight materials (e.g., titanium, magnesium) used in two concept 3XVs -- i.e., automobiles that are three times more fuel efficient than today's automobiles -- that are being designed and developed in support of the Partnership for a New Generation of Vehicles (PNGV) program. The two concept vehicles studied were the DaimlerChrysler ESX2 and the Ford P2000. Data for this research were drawn from a wide range of sources, including: the two automobile manufacturers; automobile industry reports; government and proprietary databases; past life-cycle assessments; interviews with industry experts; and models.

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).

The ability to make accurate decisions concerning early body-in-white architectures is critical to an automaker since these decisions often have long term cost and weight impacts. We address this need with a methodology which can be used to assist in body architecture decisions using process-based technical cost modeling (TCM) as a filter to evaluate alternate designs. Despite the data limitations of early design concepts, TCM can be used to identify key trends for cost-effectiveness between design variants. A compact body-in-white architecture will be used as a case study to illustrate this technique. The baseline steel structure will be compared to several alternate aluminum intensive structures in the context of production volume.

This paper presents a unified modeling environment to simulate vehicle driving and powertrain operations within the context of the surrounding environment, including interactions between vehicles and between vehicles and the road. The goal of this framework is to facilitate the analysis of the energy impacts of vehicle connectivity and automation, as well as the development of eco-driving algorithms. Connectivity and automation indeed provide the potential to use information about the environment and future driving to minimize energy consumption. To achieve this goal, the designers of eco-driving control strategies need to simulate a wide range of driving situations, including the interactions with other vehicles and the infrastructure in a closed-loop fashion.

In order to further characterize and optimize the performance of Selective Catalytic Reduction (SCR) aftertreatment systems used on heavy-duty diesel engines, an accurately calibrated high-fidelity multi-step global kinetic SCR model and a reduced order estimator for on-board diagnostic (OBD) and control are desirable. In this study, a Cu-zeolite SCR catalyst from a 2010 Cummins ISB engine was experimentally studied in a flow reactor using carefully designed protocols. A 2-site SCR model describing mass transfer and the SCR chemical reaction mechanisms is described in the paper. The model was calibrated to the reactor test data sets collected under temperatures from 200 to 425 °C and SCR space velocities of 60000, 90000, and 120000 hr-1. The model parameters were calibrated using an optimization code to minimize the error between measured and simulated NO, NO₂, N₂O, and NH₃ gas concentration time histories.

A multidisciplinary toolset integrating ANSYS FLUENT CFD solver and GM in-house thermal system design tool - e-Thermal has been developed to design automotive HVAC systems. This toolset utilizes COM software interface standard of MS Windows for inter-process communication at simulation run-time to synchronize the two applications and to exchange data. In this report, first, the implementation of this fully transient, coupled method between FLUENT CFD and e-Thermal is introduced. We then apply this integrated tool to simulate a transient A/C operating cycle including hot-soak and cool-down of a cabin. The coupled simulation consists of an A/C and an Air-Handling (HVAC module) system models, and a cabin CFD model. It demonstrates that the coupled method can simulate fully transient HVAC system operations in a vehicle.

The crush performance of lightweight composite automotive structures varies significantly between static and dynamic test conditions. This paper discusses the development of a new dynamic testing facility that can be used to characterize crash performance at high loads and constant speed. Previous research results from the Energy Management Working Group (EMWG) of the Automotive Composites Consortium (ACC) showed that the static crush resistance of composite tubes can be significantly greater than dynamic crush results at speeds greater than 2 m/s. The new testing facility will provide the unique capability to crush structures at high loads in the intermediate velocity range. A novel machine control system was designed and projections of the machine performance indicate its compliance with the desired test tolerances. The test machine will be part of a national user facility at the Oak Ridge National Laboratory (ORNL) and will be available for use in the summer of 2002.

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

There are many challenges in implementing grid aware plug-in electric vehicle (PEV) charging systems with local load control. New opportunities for innovative load control were created as a result of changes to the 2014 National Electric Code (NEC) about automatic load control definitions for EV charging infrastructure. Stakeholders in optimized dispatch of EV charging assets include the end users (EV drivers), site owner/operators, facility managers and utilities. NEC definition changes allow for ‘over subscription’ of more potential EV charging station load than can be continuously supported if the total load at any time is within the supply system safety limit. Local load control can be implemented via compact submeter(s) with locally hosted control algorithms using direct communication to the managed electric vehicle supply equipment (EVSE).