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Plug-in Hybrid Electric Vehicles (PHEVs) use electric energy from the grid rather than fuel energy for most short trips, therefore drastically reducing fuel consumption. Different configurations can be used for PHEVs. In this study, the parallel pre-transmission, series, and power-split configurations were compared by using global optimization. The latter allows a fair comparison among different powertrains. Each vehicle was operated optimally to ensure that the results would not be biased by non-optimally tuned or designed controllers. All vehicles were sized to have a similar all-electric range (AER), performance, and towing capacity. Several driving cycles and distances were used. The advantages of each powertrain are discussed.

The extensive use of rotative machines in the diverse branches of the modern world has made the rising undesirable mechanical and acoustic vibration levels to be a problem of special importance for the machines normal operation as for the communities that are each time more affected by the problem. It makes the study of vibration and acoustic phenomena also to be even more important and the applications of its concepts more sophisticated. Several are the concepts used for decreasing vibration levels, like common dampers, hydraulic dampers, active dampers, natural frequencies changes and others. The choice of use of one or another depends greatly on the engineering possibilities (weight, energy, physical space, other components functional interference, vibration levels, etc.) as well as the cost of implementation of each one.

Dimethyl ether (DME) is an alternative to diesel fuel for use in compression-ignition engines with modified fuel systems and offers potential advantages of efficiency improvements and emission reductions. DME can be produced from natural gas (NG) or from renewable feedstocks such as landfill gas (LFG) or renewable natural gas from manure waste streams (MANR) or any other biomass. This study investigates the well-to-wheels (WTW) energy use and emissions of five DME production pathways as compared with those of petroleum gasoline and diesel using the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model developed at Argonne National Laboratory (ANL).

A wavelet-based technique for reducing the impulsive character of sound recordings is presented. The amount of impulsive content removed may be adjusted by varying a statistical threshold. The technique is validated for a diesel idle sound-quality application. The wavelet-based modification produces a substantial decrease in impulsive character as verified by an objective sound-quality metric for engine “ticking”. Informal subjective assessment of the modified results found them to be realistic and free from artifacts. The procedure is expected to be useful for sound-quality simulation and target-setting for diesel powertrain noise and other automotive sounds containing both impulsive and non-impulsive content.

Recent applied mathematics research on the properties of the invertible shift-invariant discrete wavelet transform has produced new ways to visualize, separate, and synthesize impulsive sounds, such as thuds, slaps, taps, knocks, and rattles. These new methods can be used to examine the joint time-frequency characteristics of a sound, to select individual components based on their time-frequency localization, to quantify the components, and to synthesize new sounds from the selected components. The new tools will be presented in a non-mathematical way illustrated by two real-life sound quality problems, extracting the impulsive components of a windshield wiper sound, and analyzing a door closing-induced rattle.

Under various real-world scenarios, vehicles can become disabled and require towing. OEMs allow a few options for vehicle wrecker towing that include wheel lift tow using a stinger or towing on a flatbed. These methods entail multiple loading events that need to be assessed for damage to the towed vehicle. OEMs have several testing and evaluation methods in place for those scenarios with majority requiring physical vehicle prototypes. Recent focus to reduce product development time and cost has replaced the need for prototype testing with analytical verification methods. In this paper, the CAE method involving multibody dynamic simulation (MBDS) as well as finite element analysis (FEA) of vehicle flatbed operation, winching onto a flatbed, and stinger-pull towing are discussed.

The increasing use of aluminum in the design of Body In White (BIW) structures created the need to develop and verify repair methodologies specific to this substrate. Over the past century, steel has been used as the primary material in the production of automotive BIW systems. While repair methods and techniques in steel have been evolving for decades, aluminum structural repair requires special attention for such common practices as welding, mechanical fastening, and the use of adhesives. This paper outlines some of the advanced verification and testing methodologies used to develop collision repair procedures for the aluminum 2003 Jaguar XJ sedan. It includes the identification of potential failure modes found in production and customer applications, the formulation of testing methodologies, CAE verification testing and component subsystem prove-out. The objective of the testing was to develop repair methodologies that meet or exceed production system performance characteristics.

Knock in the Camshaft Torque Actuated (CTA) in the Variable Cam Timing (VCT) engine can be a NVH issue and a source of customer complaint. The knock noise usually occurs during hot idle when the VCT phaser is in the locked position and the locking pin is engaged. During a V8 engine development at Ford, the VCT knock noise was observed during hot idle run. In this paper investigation leading to the identification of the root cause through both test and the CAE simulation is presented. The key knock contributors involving torque and its rate of change in addition to the backlash level are discussed. A CAE metric to assess knock occurrence potential for this NVH failure mode is presented. Finally a new design feature in terms of locking pinhole positioning to mitigate or eliminate the knock is discussed.

Valvetrain ticking noise is one of the key failure modes in noise vibration harshness (NVH) evaluation at idle. It affects customer satisfaction inversely. In this paper, the root cause of the valvetrain ticking noise and key parameters that impact ticking noise will be presented. A physics based math model has been developed and integrated into a parameterized multi-body dynamic model. The analytical prediction has been correlated with testing data. Valvetrain ticking noise control is discussed.

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.

The first commercially available Plug-In Hybrid Electric Vehicle (PHEV), the General Motors (GM) Volt, was introduced into the market in December 2010. The Volt's powertrain architecture provides four modes of operation, including two that are unique and maximize the Volt's efficiency and performance. The electric transaxle has been specially designed to enable patented operating modes both to improve the electric driving range when operating as a battery electric vehicle and to reduce fuel consumption when extending the range by operating with an internal combustion engine (ICE). However, details on the vehicle control strategy are not widely available because the supervisory control algorithm is proprietary. Since it is not possible to analyze the control without vehicle test data obtained from a well-designed Design-of-Experiment (DoE), a highly instrumented GM Volt, including thermal sensors, was tested at Argonne National Laboratory's Advanced Powertrain Research Facility (APRF).

Connectivity and automation provide the potential to use information about the environment and future driving to minimize energy consumption. Aerodynamic drag can also be reduced by close-gap platooning using information from vehicle-to-vehicle communications. In order to achieve these goals, the designers of control strategies need to simulate a wide range of driving situations in which vehicles interact with other vehicles and the infrastructure in a closed-loop fashion. RoadRunner is a new model-based system engineering platform based on Autonomie software, which can collectively provide the necessary tools to predict energy consumption for various driving decisions and scenarios such as car-following, free-flow, or eco-approach driving, and thereby can help in developing control algorithms.

Realistic vehicle fuel economy studies require real-world vehicle driving behavior data along with various factors affecting the fuel consumption. Such studies require data with various vehicles usages for prolonged periods of time. A project dedicated to collecting such data is an enormous and costly undertaking. Alternatively, we propose to utilize two publicly available vehicle travel survey data sets. One is Puget Sound Travel Survey collected using GPS devices in 484 vehicles between 2004 and 2006. Over 750,000 trips were recorded with a 10-second time resolution. The data were obtained to study travel behavior changes in response to time-and-location-variable road tolling. The other is Atlanta Regional Commission Travel Survey conducted for a comprehensive study of the demographic and travel behavior characteristics of residents within the study area.

A key ingredient in designing products that are more robust is a thorough knowledge of the physics of the ideal function of those products and the physics of the failure modes of those products. We refer to the mathematical functions describing this physics as the transfer functions for that product. Dimensional analysis (DA) is a well known, but often overlooked, tool for reducing the number of experiments needed to characterize a physical system. In this paper, we demonstrate how the application of DA can be used to reduce the size of a DOE needed to estimate transfer functions experimentally. Furthermore, the transfer function generated using DOEs with DA tend to be more general than those generated using larger DOEs directly on the design parameters. With ever-increasing competitive pressure and reduced product development time, a tool such as DA, which can dramatically reduce experimental cost, is an incredibly valuable addition to an engineers toolbox.

The paradigm for utilizing computer-aided engineering (CAE) to analyze automotive steering and suspension designs is rapidly changing. CAE's role has expanded beyond mere analysis to designing and improving product reliability and robustness. This paper presents an approach for avoiding the steering wheel nibble failure mode by improving robustness and therefore reliability through the use of CAE. For this paper, reliability is the ability of the system to avoid failure modes. A failure mode is any customer perceived deviation from ideal and avoiding failure modes naturally improves reliability. [1]

Gasoline particulate filters (GPF) with high filtration efficiency (>80%) at zero mileage are in growing demand to meet increasingly tight vehicle emission standards for particulate matter being implemented in US, EU, China and elsewhere. Current efforts to achieve high filter performance mainly focus on fine-tuning the filter structure, such as the pore size distribution and porosity of the bare substrate, or the washcoat loading and location of catalyzed substrates. However, high filtration efficiency may have a cost in high backpressure that negatively affects engine power. On the other hand, it has been recognized in a few reports that very low amounts of ash deposits (from non-combustible residue in the exhaust) can significantly increase filtration efficiency with only a mild backpressure increase.

Statistical Energy Analysis (SEA) is used to predict high-frequency acoustic and vibration response in vehicle NVH design. Early in the design cycle prototype hardware is not yet available for testing and the geometry is still too poorly defined and changing too quickly for Finite Element Analysis or Boundary Element Analysis to be an effective NVH analysis tool. For most of the concept phase and early design phase, SEA uniquely offers the ability to virtually predict the main noise transfer paths and to support target setting for component and full vehicle NVH design. At later stages of the design process, SEA combines with NVH testing to provide more accurate predictions and to provide guidance for more efficient testing. This paper describes the established uses of SEA in the vehicle industry and presents an overview of the NVH design cycle and how SEA is used to support NVH development at different stages.

Compressible plastic foams are used throughout the interior and bumper systems of modern automobiles for safety enhancement and damage prevention. Consequently, modeling of foams has become very important for automobile engineers. To date, most work has focused on predicting foam performance up to approximately 80% compression. However, in certain cases, it is important to predict the foam under maximum compression, or ‘bottoming-out.’ This paper uses one such case-a thin low-density bumper foam impacted by a pedestrian leg-form at 11.1 m/s-to investigate the ‘bottoming-out’ phenomenon. Multiple material models in three different explicit Finite Element Method (FEM) packages (RADIOSS, FCRASH, and LS-DYNA) were used to predict the performance. The finite element models consisted of a foam covered leg-form impacting a fixed bumper beam with a foam energy absorber.

For many years, the use of in-mold fasteners has been avoided for various reasons including: not fully understanding the load cases in the part, the fear of quality issues occurring, the need for servicing, or the lack of understanding the complexity of all failure modes. The most common solution has been the use of secondary operations to provide attachments, such as, screws, metal clips, heat staking, sonic welding or other methods which are ultimately a waste in the process and an increase in manufacturing costs. The purpose of this paper is to take the reader through the design process followed to design an in-molded attachment clip on plastic parts. The paper explores the design process for in-molded attachment clips beginning with a design concept idea, followed by basic concept testing using a desktop 3D printer, optimizing the design with physical tests and CAE analysis, and finally producing high resolution 3D prototypes for validation and tuning.

Previously fuel consumption on a drive cycle has been shown to be proportional to traction work, with an offset for powertrain losses. This model had different transfer functions for different drive cycles, performance levels, and applied powertrain technologies. Following Soltic it is shown that if fuel usage and traction work are both expressed in terms of cycle average power, a wide range of drive cycles collapse to a single transfer function, where cycle average traction power captures the drive cycle and the vehicle size. If this transfer function is then normalized by weight, i.e. by working in cycle average power/weight (P/W), a linear model is obtained where the offset is mainly a function of rated performance and applied technology. A final normalization by rated power/weight as the primary performance metric further collapses the data to express the cycle average fuel power/rated power ratio as a function of cycle average traction power/rated power ratio.