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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.

In the developement process, the engineer is required to design, validate and deliver the components for manufacturing, in an as short as possible lead time. For that, the engineer may use some available tools to save not only time, but also cost. This work presents a zero prototype approach applyied to a plastic component, whose main accomplishment was the decreasing of lead time development due to the intensive use of virtual tools (CAD/CAE). As a result, the product was delivered in a short time, with no need of building physical prototypes, thus reducing development cost.

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).

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.

The United States Department of Transportation (USDOT) and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, General Motors, Honda, Mercedes-Benz, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested Vehicle-to-Vehicle (V2V) communications-based safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

Recent trends show a growing demand for improved powertrain noise and vibration quality. In particular, there is little customer acceptance of vibration and noise (“boom”) at engine idle speeds. CAE analysis is being used increasingly as an aid for reducing overall vehicle level responses. Traditionally, analytical idle response is evaluated for only one particular engine order at a time. An efficient Excel based tool called VeCTRA (Vehicle Cascade & Target Response Analysis) was developed to accurately assess the effects of multiple powertrain orders on the vehicle level idle response. VeCTRA is capable of predicting the overall vehicle level response (tactile and acoustic) as well as determining the contribution from each engine order and the specific component excitations within an order. VeCTRA is capable of using analytical or experimentally measured sensitivity and/or excitation data.

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.

Ford Motor Company’s assembly plants build vehicles in a certain sequence. The planned sequence for the plant’s trim and final assembly area is developed centrally and is sent to the plant several days in advance. In this work we present the study of two cases where the plant changes the planned sequence to cope with production constraints. In one case, a plant pulls ahead two-tone orders that require two passes through the paint shop. This is further complicated by presence in the body shop area of a unidirectional rotating tool that allows efficient build of a sequence “A-B-C” but heavily penalizes a sequence “C-B-A”. The plant changes the original planned sequence in the body shop area to the one that satisfies both pull-ahead and rotating tool requirements. In the other case, a plant runs on lean inventories. Material consumption is tightly controlled down to the hour to match with planned material deliveries.

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.

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.

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.

The previously developed power-based fuel consumption theory for Internal Combustion Engine Vehicles (ICEV) is extended to Battery Electric Vehicles (BEV). The main difference between the BEV model structure and the ICEV is the bi-directional character of traction motors and batteries. A traction motor model was developed as a bi-linear function of positive and negative traction power. Another difference is that the accessories and cabin heating are powered directly from the battery, and not from the powertrain. The resulting unified model for ICEV and BEV energy consumption has linear terms proportional to positive and negative traction power, accessory power, and overhead, in varying proportions. Compared to the ICEV, the BEV powertrain has a high marginal efficiency and low overhead. As a result, BEV energy consumption data under a wide range of driving conditions are mainly proportional to net traction power, with only a small offset.

Advanced features in automotive systems often necessitate the management of complex interactions between subsystems. Existing control strategies are designed for certain levels of robustness, however their performance can unexpectedly deteriorate in the presence of significant uncertainties, resulting in undesirable system behaviors. This limitation is further amplified in systems with complex nonlinear dynamics. Hydro-mechanical clutch actuators are among those systems whose behaviors are highly sensitive to variations in subsystem characteristics and operating environments. In a P2 hybrid propulsion system, a wet clutch is utilized for cranking the engine during an EV-HEV mode switching event. It is critical that the hydro-mechanical clutch actuator is stroked as quickly and as consistently as possible despite the existence of uncertainties. Thus, the quantification of uncertainties on clutch actuator behaviors is important for enabling smooth EV-HEV transitions.

This paper analyzes the potential benefit of a model based DPF leakage monitor over a conventional DPF leakage monitor that checks pressure drop after a complete regeneration. We analyze the most important noise factors involved in both approaches and demonstrate that the model based leakage monitor does not improve on the conventional leakage monitor in accuracy. It does improve on completion frequency, but at the expense of a great modeling effort.

The most significant challenge in emission control for compression ignited internal combustion engines is the suppression of NOx. In the US, NOx-levels have faced a progressive reduction for several years, but recently the introduction of the Real Driving Emissions legislation (RDE) in Europe has not only significantly increased the severity of the required emission reduction but now is in the advent of stretching technology to its limits. Emission control is based on engine-internal optimization to reduce the engine-out emissions in conjunction with aftertreatment technologies, that are either Selective Catalytic Reduction (SCR) or Lean NOx Trap (LNT) based systems. Due to its ability to control high amounts of NOx, SCR is widely used in heavy-duty applications and is becoming more popular in light-duty and passenger car applications as well.

Successful application of turbocharger technology to the Ford 2.3L OHC engine requires management of thermal loading. The 1979/1980 2.3L draw-thru carbureted engine was octane and spark advance limited, requiring calibration to worse case 91 RON conditions. Since no adaptive calibration control was possible relatively late ignition timing compromised engine performance. To improve performance, driveability, fuel economy and emission control, work was initiated in mid 1980 on a blow-thru electronic fuel injected engine scheduled for 1983½ production. Program assumptions were issued specifying a tuned EFI blow-thru inlet system, exhaust manifold mounted AiResearch T03 turbocharger with integral wastegate and 8.0:1 compression ratio with a dished piston. Also included were base engine revisions to accommodate increased thermal and mechanical loads.

A transient nonlinear Finite Element Analysis (FEA) method has been developed to simulate the inelastic deformation and estimate the thermo-mechanical fatigue life of cast iron and cast steel exhaust manifolds under dynamometer test conditions. The FEA uses transient heat transfer analysis to simulate the thermal loads on the manifold, and includes the fasteners, gasket and portion of the cylinder head. The analysis incorporates appropriate elastic-plastic and creep material models. It is shown that the creep deformation is the most single critical component of inelastic deformation for cast iron manifold ratcheting, gasket sealing, and crack initiation. The predicted transient temperature field and manifold deformation of the FEA model compares exceptionally well with two experimental tests for a high silicon-molybdenum exhaust manifold.

Meeting EPA Tier 2 emission standards presents a great challenge to engine manufacturers. In addition to having an actively controlled aftertreatment system, engine-out NOx emission needs to be reduced significantly to achieve regulatory compliance. Using advanced combustion methods, such as low temperature combustion and/or HCCI, has been shown to reduce engine-out NOx emissions. However, all this new combustion technologies are yet to permeate down into any production system. In current practice, large amount of exhaust gas recirculation (EGR) into the cylinders is widely used to reduce emissions. However, NOx emission from transient engine operation still constitutes a very large percentage of the total NOx output during a Federal Test Procedure (FTP) cycle and has yet to be adequately addressed. Currently, the EGR flow is controlled using the intake mass airflow (MAF) measurement.

This paper presents a Short Time Fourier Transform based algorithm to identify unknown parameters in fuel dynamics system during engine cold start and warm-up. A first order system is used to model the fuel dynamics in a port fuel injection engine. The feed forward transient fuel compensation controller is designed based on the identified model. Experiments are designed and implemented to verify the proposed algorithm. Different experiment settings are compared.

Advancing intake valve timing shortly after engine crank and run-up can potentially reduce vehicle cold start hydrocarbon (HC) emissions in port fuel injected (PFI) engines equipped with intake variable cam timing (iVCT). Due to the cold metal temperatures, there can be significant accumulation of liquid fuel in the intake system and in the cylinder. This accumulation of liquid fuel provides potential sources for unburned hydrocarbons (HCs). Since the entire vehicle exhaust system is cold, the catalyst will not mitigate the release of unburned HCs. By advancing the intake valve timing and increasing valve overlap, liquid fuel vaporization in the intake system is enhanced thereby increasing the amount of burnable fuel in the cylinder. This increase in burnable HCs must be countered by a reduction in injector-delivered fuel via a compensator that reacts to cam movement.