Search Results

A fast time-scale 1-D dynamic diesel particulate filter model capable of resolving the pressure pulsations due to individual cylinder firing events is presented. The purpose of this model is to investigate changes in the firing frequency component of the pulsating exhaust flow at different particulate loadings. Experimental validation data and simulation results clearly show that the magnitude and phase of the firing frequency components are directly correlated to the mass of particulate stored in a diesel particulate filter. This dynamic pressure signal information may prove particularly useful for monitoring particulate load during vehicle operation.

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.

This paper presents the Statistical Energy Approach (SEA) method for estimating the gross response in complex interconnected structural systems. The method is intended to compensate for the difficulties present in evaluating parameters and excitation needed when attempting to use traditional methods of linear vibration analysis. The amount of information needed to apply the method is modest and the formulas are easy to use. Some limitation on application is demonstrated by a detailed example.

In order to reduce fuel consumption, companies have been looking at hybridizing vehicles. So far, two main hybridization options have been considered: electric and hydraulic hybrids. Because of light duty vehicle operating conditions and the high energy density of batteries, electric hybrids are being widely used for cars. However, companies are still evaluating both hybridization options for medium and heavy duty vehicles. Trucks generally demand very large regenerative power and frequent stop-and-go. In that situation, hydraulic systems could offer an advantage over electric drive systems because the hydraulic motor and accumulator can handle high power with small volume capacity. This study compares the fuel displacement of class 6 trucks using a hydraulic system compared to conventional and hybrid electric vehicles. The paper will describe the component technology and sizes of each powertrain as well as their overall vehicle level control strategies.

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.

Near-Field Acoustical Holography (NAH) is an inverse process in which sound pressure measurements made in the near-field of an unknown sound source are used to reconstruct the sound field so that source distributions can be clearly identified. NAH was originally based on performing spatial transforms of arrays of measured pressures and then processing the data in the wavenumber domain, a procedure that entailed the use of very large microphone arrays to avoid spatial truncation effects. Over the last twenty years, a number of different NAH methods have been proposed that can reduce or avoid spatial truncation issues: for example, Statistically Optimized Near-Field Acoustical Holography (SONAH), various Equivalent Source Methods (ESM), etc.

Driveline and suspension notched components of off-road ground vehicles often experience multiaxial fatigue failures along notch locations. Large nominal load histories may induce local elasto-plastic stress and strain responses at the critical notch locations. Fatigue life prediction of such notched components requires detailed knowledge of local stresses and strains at notch regions. The notched components that are often subject to multiaxial loadings in services, experience complex stress and strain responses. Fatigue life assessment of the components utilizing non-linear Finite Element Analysis (FEA) require unfeasibly inefficient computation times and large data. The lack of more efficient and effective methods of elasto-plastic stress-strain calculation may lead to the overdesign or earlier failures of the components or costly experiments and inefficient non-linear FEA.

The work presented here outlines the development of a robust CAO tool for optimal design of electromagnetic retarder machines. The developed EM-CAO tool is then used to perform a wide variety of CAE/CAO tasks, from automatically computing the torque versus rpm performance curves of the EM retarder to performing optimization. Two specific examples of optimal design of the EM retarder are reported. Through the use of a task manager/optimizer repetitive jobs are fully automated thereby making the analysis and optimization of electromagnetic retarders faster and user-friendlier.

Induction noise, which radiates from the open end of the engine air induction system, can be of significant importance in reducing vehicle interior noise and tuning the interior sound to meet customer expectations. This makes understanding the source noise critical to the development of the air induction system and the vehicle interior sound quality. Given the ever-decreasing development times, it is highly desirable to use computer-aided engineering (CAE) tools to accelerate this process. Many tools are available to simulate induction noise or, more generally, duct acoustics. The tools vary in degrees of complexity and inherent assumptions. Three-dimensional tools will account for the most general of geometries. However, it is also possible to model the duct acoustics with quasi-three-dimensional or one-dimensional tools, which may be faster as well.

Due the increasing concern with the acoustic environment within automotive vehicles, there is an interest in measuring the acoustical properties of automotive door seals. These systems play an important role in blocking external noise sources, such as aerodynamic noise and tire noise, from entering the passenger compartment. Thus, it is important to be able to conveniently measure their acoustic performance. Previous methods of measuring the ability of seals to block sound required the use of either a reverberation chamber, or a wind tunnel with a special purpose chamber attached to it. That is, these methods required the use of large and expensive facilities. A simpler and more economical desktop procedure is thus needed to allow easy and fast acoustic measurement of automotive door seals.

A synchronous machine model is set forth that simultaneously incorporates magnetizing path saturation, leakage saturation, and transfer function representations of the rotor circuits. A parameter identification procedure consisting of voltage step tests as well as standstill frequency response tests is described. The model's predictions are validated using the Naval Combat Survivability Generation and Propulsion test bed.

Interior compartment doors are required by Federal Motor Vehicle Safety Standard (FMVSS) 201, to stay closed during physical head impact testing, and when subjected to specific inertia loads. This paper defines interior compartment doors, and shows examples of several different latches designed to keep these doors closed. It also explores the details of the requirements that interior compartment doors and their latches must meet, including differing requirements from automobile manufacturers. It then shows the conventional static method a supplier uses to analyze a latch and door system. And, since static calculations can't always capture the complexities of a dynamic event, this paper also presents a case study of one particular latch and door system showing a way to simulate the forces experienced by a latch. The dynamic simulation is done using Finite Element Analysis and instrumentation of actual hardware in physical tests.

A dynamic computer model of automotive air conditioning systems was developed. The model uses simulation software for the coding of 1-D heat transfer, thermodynamics, fluid flow, and control valves. The same software is used to model 3-D solid dynamics associated with mechanical mechanisms of the compressor. The dynamics of the entire AC system is thus simulated within the same software environment. The results will show the models potential applications in component and system design, calibration and control.

Pumped two-phase systems using mini or microchannel heat sink evaporators are prime candidates for high heat flux applications due to relatively low pumping power requirements and efficient heat removal in compact designs. A number of challenges exist in the implementation of these systems including: ensuring subcooled liquid to the pump to avoid cavitation, avoiding dry out conditions in heat exchangers that can lead to failures of the components under cooling, and avoiding flow instabilities that can damage components in an integrated system. To reduce risk and cost, modeling and simulation can be employed in the design and development of these complex systems, but such modeling must include the relevant behavior necessary to capture the above dynamic effects.

Virtual design validation of an air induction system (AIS) requires a proper finite element (FE) assembly model for various simulation based design tasks. The effect of the urethane air filter seal within an AIS assembly, however, still poses a technical challenge to the modeling of structural dynamic behaviors of the AIS product. In this paper, a filter seal model and its modeling approach for AIS assemblies are introduced, by utilizing the feature finite elements and empiric test data. A bushing element is used to model the unique nonlinear stiffness and damping properties of the urethane seal, as a function of seal orientation, preloading, temperature and excitation frequency, which are quantified based on the test data and empiric formula. Point mobility is used to character dynamic behaviors of an AIS structure under given loadings, as a transfer function in frequency domain.

In developing a direct injection gasoline engine, the in-cylinder fuel air mixing is key to good performance and emissions. High speed visualization in an optically accessible single cylinder engine for direct injection gasoline engine applications is an effective tool to reveal the fuel spray pattern effect on mixture formation The fuel injectors in this study employ the unique multi-hole turbulence nozzles in a PFI-like (Port Fuel Injection) fuel system architecture specifically developed as a Low Pressure Direct Injection (LPDI) fuel injection system. In this study, three injector sprays with a narrow 40° spray angle, a 60°spray angle with 5°offset angle, and a wide 80° spray angle with 10° offset angle were evaluated. Image processing algorithms were developed to analyze the nature of in-cylinder fuel-air mixing and the extent of fuel spray impingement on the cylinder wall.

High surface area particles have drawn attention in the context of noise control due to their good sound absorption performance at low frequencies, which is an advantage compared with more traditional materials. That observation suggests that there is a good potential to use these particles in various scenarios, especially where low frequency noise is the main concern. To facilitate their application, composite materials are formed by dispersing particles within a fiber matrix, thus giving more flexibility in positioning those particles. In this work, a hybrid model that combines a model for limp porous materials and a model of high surface area particles is proposed to describe the acoustic performance of such composites. Two-microphone standing wave tube test results for several types of composites with different thickness, basis weight, and particle concentration are provided.

Striving for sustainable transportation solutions, hydrogen is often identified as a promising energy carrier and internal combustion engines are seen as a cost effective consumer of hydrogen to facilitate the development of a large-scale hydrogen infrastructure. Driven by efficiency and emissions targets defined by the U.S. Department of Energy, a research team at Argonne National Laboratory has worked on optimizing a spark-ignited direct injection engine for hydrogen. Using direct injection improves volumetric efficiency and provides the opportunity to properly stratify the fuel-air mixture in-cylinder. Collaborative 3D-CFD and experimental efforts have focused on optimizing the mixture stratification and have demonstrated the potential for high engine efficiency with low NOx emissions. Performance of the hydrogen engine is evaluated in this paper over a speed range from 1000 to 3000 RPM and a load range from 1.7 to 14.3 bar BMEP.

A methodology has been developed for identifying the combination of battery characteristics which lead to least-cost electric vehicles. Battery interrelationships include specific power vs, specific energy, peak power vs. specific energy and DOD, cycle life vs. DOD, cost vs. specific energy and peak power, and volumetric and battery size effects. The method is illustrated for the “second car” mission assuming lead/acid batteries. Reductions in life-cycle costs associated with future battery research breakthroughs are estimated using a sensitivity technique. A research prioritization system is described.