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Ammonia adsorption on the catalyst surface is a crucial step in the selective catalytic reduction of nitrogen oxides over zeolites with NH3 as the reducing agent. In this study, two small pore zeolites with chabazite frameworks, H-SSZ-13 and Cu exchanged SSZ-13, are examined. Adsorption of NH3 on the zeolite causes changing electrical properties of the material. They can be detected by a radio frequency based technique. We have found that with this method it is possible to determine the amount of adsorbed NH3 on these catalysts, examining both the influences of temperature and NH3/NO feed gas ratio. At constant temperature, a fairly linear correlation between the resonance frequency and the amount of adsorbed ammonia was observed. Furthermore, this method also allows differentiation between some of the NH3 adsorption sites.

Woven fabric carbon fiber/epoxy composites made through compression molding are one of the promising choices of material for the vehicle light-weighting strategy. Previous studies have shown that the processing conditions can have substantial influence on the performance of this type of the material. Therefore the optimization of the compression molding process is of great importance to the manufacturing practice. An efficient way to achieve the optimized design of this process would be through conducting finite element (FE) simulations of compression molding for woven fabric carbon fiber/epoxy composites. However, performing such simulation remains a challenging task for FE as multiple types of physics are involved during the compression molding process, including the epoxy resin curing and the complex mechanical behavior of woven fabric structure.

Atmospheric modelers and development engineers need accurate measures of NO2 emissions from motor vehicles. Due to the oxidative reaction of oxygen with NO, these measurements (typically taken from a bag sample) can be inaccurate if care is not taken to minimize the sample residence time in the bags. This reaction occurs slowly at low NO concentrations, however, at higher NO concentrations the reaction can rapidly speed up (for example, 50 ppm NO will experience a 10% concentration reduction in 6.5 minutes). This report explores the factors contributing to this artifact for emissions test cells. Estimates of the error in NO2 emission rate measurements for several scenarios are presented. Additionally, kinetic expressions of the reaction rate are shown to be fairly accurate for our test conditions, but should not be used in general without verification of the non-existence of competing, hindering or accelerating species within the sample bag.

The use of Selective Catalytic Reduction (SCR) for NOx emissions control has resulted in a new challenge for the emissions measurement community. Most SCR systems require injection of urea or ammonia into the exhaust stream. Residual ammonia present in vehicle exhaust can have deleterious effects on NOx analyzers using chemiluminescent detectors (CLD). Ammonia can poison converter catalysts in CLD NOx analyzers and may react with NO2 across the converter. Both of these issues lead to erroneous NOx measurements, as well as increased maintenance costs and downtime. This paper will describe the development and use of a low-cost, simple ammonia scrubber that can easily be integrated into sampling systems and requires little change in test cell maintenance procedures. Validation results show the scrubber to have capacity sufficient to last for a full day of testing of typical vehicles.

Diesel vehicle applications are being tasked with increasingly stringent particulate emissions regulations. These regulations will require the use of Diesel Particulate Filters (DPFs). Prior to on-vehicle studies, DPF qualification studies are performed in laboratory bench reactors. In order to provide representative performance data, these studies require the testing of samples loaded with carbonaceous soot particles. A new soot generator, utilizing a pressure controlled propane flame, has been designed and built for this purpose. Soot production rates are on the order of approximately 8 mg/min at a concentration of 180 mg/m3. This allows 8 inch long cores to be loaded in 1 hour to soot concentrations encountered in typical vehicle operation. The soot generator allows for the selection of two distinct size distributions similar to typical diesel exhaust: a 57 nm peak and a 76 nm peak.

Urea-based Selective Catalytic Reduction (SCR) has the potential to meet U.S. Diesel Tier 2 Bin 5 emission standards for NOx in 2010. The operating and driving conditions of light-duty and heavy-duty vehicles make it necessary to customize catalyst features to the application. This paper reviews the selection of SCR catalyst technology for the U.S. and the appropriate aging and poisoning protocols for current supplier SCR catalysts. Generally, light-duty applications require SCR catalysts to function well at low temperature whereas heavy-duty applications require functionality at high temperature and high space velocity. One main durability requirement of SCR formulations involves withstanding the high temperature process of regenerating particulate filters from accumulated soot. Unrefined engine exhaust temperature control coupled with the inexact temperature measurement may also expose SCR catalysts to additional over-temperature conditions.

Superplastic forming (SPF) is a manufacturing process that can facilitate increased use of aluminum in automobile body structures. Despite considerable advantages with regards to formability and tooling costs, the process has been mostly limited to low volume production due to relatively long cycle times. This paper focuses on the development of a simulation capability to model a novel double-action mechanical pre-forming SPF process which can enhance formability as well as improve production efficiency by combining technology of hot stamping and conventional superplastic forming. A commercial explicit finite element analysis (FEA) code was adopted to establish feasibility of the forming process. The predictive accuracy of the FEA code was established in terms of thickness distribution and material drawn-in by correlating simulation results with experiments conducted with a deep draw die.

Electric vehicles have a strong potential to reduce a continued dependence on fossil fuels and help the environment by reducing pollution. Despite the desirable advantage, the introduction of electrified vehicles into the market place continues to be a challenge due to cost, safety, and life of the batteries. General Motors continues to bring vehicles to market with varying level of hybrid functionality. Since the introduction of Li-ion batteries by Sony Corporation in 1991 for the consumer market, significant progress has been made over the past 25 years. Due to market pull for consumer electronic products, power and energy densities have significantly increased, while costs have dropped. As a result, Li-ion batteries have become the technology of choice for automotive applications considering space and mass is very critical for the vehicles.

Semi-active suspension systems have traditionally used accelerometers mounted on the wheel and body to sense vehicle motion. However, the cost and weight of these sensors and their associated bracketry and wiring must be considered when deciding to adopt a semi-active suspension system on a particular vehicle. In previous report [1], Authors have described a Bi-Linear Optimal control algorithm [2] by which sprung mass motion is estimated using height sensor signals and a Kalman filter. Such an algorithm would eliminate the need for additional accelerometers and their associated hardware, resulting in a cheaper and lighter system. In this report, the Authors propose a method of improved ride comfort and reducing tuning time of this algorithm by improving the sprung mass motion estimation method.

Digital Image Correlation (DIC) technology is a powerful tool in the field of experimental mechanics to obtain the full-field deformation/strain information of an object. It has been rapidly applied in industry in recent years. However, for the large-angle full-field strain measurement of small-sized cylindrical objects, it’s still a challenge to the DIC accurate measurement due to its small size and curved surface. In this paper, a measurement method based on the multi-camera DIC system is proposed to study the compressive performance of small-sized cylindrical materials. Three cameras form two stereo DIC measurement systems (1 and 2 cameras, and 2 and 3 cameras), each of which measures a part of the object. By calibrating three cameras at the same time, two stereos DIC coordinate systems can be unified to one coordinate system. Then match the two sets of DIC measurement data together to achieve large-angle measurement of the cylindrical surface.

With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.

Polymer plastics are widely used in automotive light weight design. Tensile tests are generally used to obtain material stress-strain curves. Due to the natural of the plastic materials, it could be elongated more than several hundred percent of its original length before breaking. Digital Image Correlation (DIC) Analysis is a precise, full field, optical measurement method. It has been accepted as a practical in-field testing method by the industry. However, with the traditional single-camera or dual-camera DIC system, it is nearly impossible to measure the extreme large strain. This paper introduces a unique experimental procedure for large elongation measurement. By utilization of quad-camera DIC system and data stitch technique, the strain history for plastic material under hundreds percent of elongation can be measured. With a quad-camera DIC system, the correlation was conducted between two adjacent cameras.

Camera data generated in a 3D virtual environment has been used to train object detection and identification algorithms. 40 common US road traffic signs were used as the objects of interest during the investigation of these methods. Traffic signs were placed randomly alongside the road in front of a camera in a virtual driving environment, after the camera itself was randomly placed along the road at an appropriate height for a camera located on a vehicle’s rear view mirror. In order to best represent the real world, effects such as shadows, occlusions, washout/fade, skew, rotations, reflections, fog, rain, snow and varied illumination were randomly included in the generated data. Images were generated at a rate of approximately one thousand per minute, and the image data was automatically annotated with the true location of each sign within each image, to facilitate supervised learning as well as testing of the trained algorithms.

Numerous studies describe the fuel consumption benefits of changing the powertrain temperature based on vehicle operating conditions. Actuators such as electric water pumps and active thermostats now provide more flexibility to change powertrain operating temperature than traditional mechanical-only systems did. Various control strategies have been proposed for powertrain temperature set-point regulation. A characteristic of powertrain thermal management systems is that the operating conditions (speed, load etc) change continuously to meet the driver demand and in most cases, the optimal conditions lie on the edge of the constraint envelope. Control strategies for set-point regulation which rely purely on feedback for disturbance rejection, without knowledge of future disturbances, might not provide the full fuel consumption benefits due to the slow thermal inertia of the system.

Exhaust temperatures are some of the hardest parameters to measure and estimate based on the range of the signal and the environment that an engine exhaust system creates. Accurate exhaust temperature inputs in vehicle and engine control systems are important for performance, fuel economy, emissions and aftertreatment control. A turbine inlet exhaust temperature observer model based on isentropic expansion and heat transfer across a turbocharger turbine was developed and investigated in this paper. There are 4 main components used to model the exhaust temperature; an open loop exhaust manifold gas temperature mass/energy model, an isentropic expansion across the turbine, a turbine heat transfer model and an observer using the downstream turbine outlet temperature. Another method using only a reverse isentropic expansion model and heat transfer parts of the observer model was analyzed and compared to the observer model.

The fatigue strength and failure behavior of A5754-O adhesively bonded single lap joints by a hot-curing epoxy adhesive were investigated in this paper. The single lap joints tested include balanced substrate joints (meaning same thickness) and unbalanced substrate joints, involving combinations of different substrate thicknesses. Cyclic fatigue test results show that the fatigue strength of bonded joints increase with the increasing substrate thickness. SEM and Energy Dispersive X-ray (EDX) were employed to investigate the failure mode of the joints. Two fatigue failure modes, substrate failure and failure within the adhesive were found in the testing. The failure mode of the joint changes from cohesive failure to substrate failure as the axial load is decreased, which reveals a fatigue resistance competition between the adhesive layer and the aluminum substrate.

We have developed a cooperative simulation environment for multiple electronic control units (ECUs) including a parallel executions mechanism to improve the test efficiency of a system, which was designed with multiple ECUs for autonomous driving. And we have applied it to a power window system for multiple ECUs with a controller area network (CAN). The power window model consists of an electronic-mechanical model and a CPU model. Each simulator with a different executions speed operates in parallel using a synchronization mechanism that exchanges data outputted from each simulator at a constant cycle. A virtual ECU simulated microcontroller hardware operations and executed its control program step-by-step in binary code to test software for the product version. As co-simulation technology, a mechanism that synchronously executes heterogeneous simulators and a model of an in-vehicle communication CAN connecting each ECU were developed.

In a previous study, a wide range of gasolines with RON∼90 were tested in a single cylinder engine operated in HCCI mode using negative valve overlap, and all were found to have very similar behavior near the low-load limit. Here we broaden the range of gasolines to include PRF90 and PRF60. At high engine speed, both PRF60 and PRF90 behave similarly to all the other gasolines tested. However, at 1000 RPM, PRF90 is very different from all the other gasolines: it ignites very late, and the engine cannot be operated at low load. Simulations using a popular fuel chemistry model cannot distinguish PRF60 and PRF90 under these conditions. However, a new fuel chemistry model correctly shows the onset of fuel sensitivity at low engine speed. Sensitivity analyses indicate the low-load limit at low engine speed strongly depend on both the chemistry parameters and on the heat-transfer parameters.

Multidisciplinary Design Optimization (MDO) is often required in aircraft design to address the multidisciplinary feasibility issues due to the disciplines, for example, aerodynamics, propulsion, and structures, are heavily coupled. However, in automobile designs, can we apply different type of MDO decomposition originated from aircraft design, to some MDO problem, for example, a vehicle weight reduction example? Also, to effectively and efficiently accommodate design changes, multi-party collaboration between discipline specialists, and fast decision making, a web-based MDO platform with knowledge-based repository for resource sharing, capability of version control, and enhancing data security, is very much needed. Two types of MDO decomposition: All-at-Once (AAO) and Collaborative Optimization (CO) are formulated for the weight reduction example. A typical six-step MDO process, from building single discipline work flow to comparing optimization results, is illustrated step-by-step.