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PEARLITIC malleable iron crankshafts are being used in the new Pontiac engine as a result of recent developments. This paper discusses the physical properties of pearlitic malleable iron such as elastic modulus, fatigue endurance, and tensile strength. According to the author, definite machining economies result from using pearlitic malleable iron crankshafts.

A METHOD is described in this paper by which the rates of gear wear under different conditions can be determined by the use of the radioactive tracer technique. With this method one can measure the minutest amount of wear at loads and speeds much below critical destructive conditions. This method makes possible the continuous determination of rates of gear wear at all loads and speeds in actual full-scale units. In this investigation, the radioactive tracer technique has been used to determine the rates of gear wear when using a straight mineral oil and when using an extreme-pressure gear lubricant.

Meeting the California Medium-Duty truck emissions standards presents a significant challenge to automotive engineers due to the combination of sustained high temperature exhaust conditions, high flow rates and relatively high engine out emissions. A successful catalyst for an exhaust treatment system must be resistant to high temperature deactivation, maintain cold start performance and display high three-way conversion efficiencies under most operating conditions. This paper describes a catalyst technology and precious metal loading study targeting a California Medium-Duty truck LEV (MDV2) application. At the same time a direction is presented for optimizing toward the Federal Tier 1 standard through reduction of precious metal use. The paper identifies catalytic formulations for a twin substrate, 1.23 L medium-coupled converter. Two are used per vehicle, mounted 45 cm downstream of each manifold on a 5.7 L V8 engine.

This paper presents a simple method of using Voronoi partitions for estimating vehicle fuel economy from a limited set of engine operating conditions. While one of the overarching goals of engine research is to continually improve vehicle fuel economy, evaluating the impact of a change in engine operating efficiency on the resulting fuel economy is a non-trivial task and typically requires drive cycle simulations with experimental data or engine model predictions and a full suite of engine controllers over a wide range of engine speeds and loads. To avoid the cost of collecting such extensive data, proprietary methods exist to estimate fuel economy from a limited set of engine operating conditions. This study demonstrates the use of Voronoi partitions to cluster and quantize the fuel consumed along a complex trajectory in speed and load to generate fuel consumption estimates based on limited simulation or experimental results.

Four multigrade engine oils, containing the same base oil plus SE additive package but VI improvers of differing shear stability, were evaluated in 80 000 km of high-speed, high-temperature vehicle service. Bearing, piston ring and valve guide wear, as well as oil consumption, oil filter plugging and engine cleanliness were all worse for the engines operated on the low-shear stability oils. The wear differences were traced to differences in high-shear-rate viscosity, while the cleanliness, filter plugging and oil consumption differences occurred because of excessive wear or polymer shear degradation. These results suggest that engine oil viscosity should be specified under high-shear-rate conditions.

A GT-SUITE vehicle-aftertreatment model has been developed to examine the cold-start emissions reduction capabilities of a Vacuum Insulated Catalytic Converter (VICC). This converter features a thermal management system to maintain the catalyst monolith above its light-off temperature between trips so that most of a vehicle’s cold-start exhaust emissions are avoided. The VICC thermal management system uses vacuum insulation around the monoliths. To further boost its heat retention capacity, a metal phase-change material (PCM) is packaged between the monoliths and vacuum insulation. To prevent overheating of the converter during periods of long, heavy engine use, a few grams of metal hydride charged with hydrogen are attached to the hot side of the vacuum insulation. The GT-SUITE model successfully incorporated the transient heat transfer effects of the PCM using the effective heat capacity method.

An optimal energy management strategy (Optimal EMS) can yield significant fuel economy (FE) improvements without vehicle velocity modifications. Thus it has been the subject of numerous research studies spanning decades. One of the most challenging aspects of an Optimal EMS is that FE gains are typically directly related to high fidelity predictions of future vehicle operation. In this research, a comprehensive dataset is exploited which includes internal data (CAN bus) and external data (radar information and V2V) gathered over numerous instances of two highway drive cycles and one urban/highway mixed drive cycle. This dataset is used to derive a prediction model for vehicle velocity for the next 10 seconds, which is a range which has a significant FE improvement potential. This achieved 10 second vehicle velocity prediction is then compared to perfect full drive cycle prediction, perfect 10 second prediction.

There is a pressing need to develop accurate and robust approaches for predicting vehicle speed to enhance fuel economy/energy efficiency, drivability and safety of automotive vehicles. This paper details outcomes of research into various methods for the prediction of vehicle velocity. The focus is on short-term predictions over 1 to 10 second prediction horizon. Such short-term predictions can be integrated into a hybrid electric vehicle energy management strategy and have the potential to improve HEV energy efficiency. Several deterministic and stochastic models are considered in this paper for prediction of future vehicle velocity. Deterministic models include an Auto-Regressive Moving Average (ARMA) model, a Nonlinear Auto-Regressive with eXternal input (NARX) shallow neural network and a Long Short-Term Memory (LSTM) deep neural network. Stochastic models include a Markov Chain (MC) model and a Conditional Linear Gaussian (CLG) model.

CFD (Computational Fluid Dynamics) has been used to analyze vehicle air flow. In cross wind conditions an asymmetrical flow field around the vehicle is present. Under these circumstances, in addition to the forces present with symmetric air flow (drag and lift forces and pitching moment), side forces and moments (rolling and yawing) occur. Issues related to fuel economy, driveability, sealing effects (caused by suction exerted on the door), structural integrity (sun roof, spoiler), water management (rain deposit), and dirt deposit (shear stress) have been investigated. Due to the software developments and computer hardware improvements, results can be obtained within a reasonable time frame with excellent accuracy (both geometry and analytical solution). The flow velocity, streamlines, pressure field, and component forces can be extracted from the analysis results through visualization to identify potential improvement areas.

Growing environmental concerns and stringent vehicle emissions regulations has created an urge in the automotive industry to move towards electrified propulsion systems. Reducing and eliminating the emission from public transportation vehicles plays a major role in contributing towards lowering the emission level. Battery electric buses are regarded as a type of promising green mass transportation as they provide the advantage of less greenhouse gas emissions per passenger. However, the electric bus faces a problem of limited range and is not able to drive throughout the day without being recharged. This research studies a public bus transit system example which servicing the city of Ann Arbor in Michigan and investigates the impact of different electrification levels on the final CO2 reduction. Utilizing models of a conventional diesel, hybrid electric, and battery electric bus, the CO2 emission for each type of transportation bus is estimated.

THIS paper describes what the authors consider to be a simplified method of determining the vapor-locking tendencies of gasolines. The study of vapor lock was undertaken after they found the Reid vapor pressure method to be inadequate. The result of their work was the development of the General Motors vapor pressure, a single number which predicts vapor-locking tendency. The authors point out the following advantages of the new method: It allows direct comparisons of vapor-lock test results of different reference fuel systems; establishes distribution curves of volatility requirements of cars for vapor-lock free operation and of vapor-locking tendencies of gasolines; is a common reference value for both petroleum and automotive engineers. Finally, it more realistically evaluates the effects of small weathering losses on vapor-locking tendency than does Rvp.

This study is a joint development project between Chrysler Corporation and CFD Research Corporation. The objective of this investigation was to develop a 3D computational flow and heat transfer model for a vehicle windshield de-icing process. The windshield clearing process is a 3D transient, multi-medium, multi-phase heat exchange phenomenon in connection with the air flow distribution in the passenger compartment. The transient windshield de-icing analysis employed conjugate heat transfer methodology and enthalpy method to simulate the velocity distribution near the windshield inside surface, and the time progression of ice-melting pattern on the windshield outside surface. The comparison between the computed results and measured data showed very reasonable agreement, which demonstrated that the developed analysis tool is capable of simulating the vehicle cold room de-icing tests.

The purpose of this paper is to illustrate the use of Taguchi experimental methods as a development tool for designing a manufacturing process for inner door panels. Through analysis of experimental results, it was possible to identify critical manufacturing variables, as well as demonstrate inherent process capability.

The emission of excessive quantities of NOx when the automobile air conditioner is turned on has received a fair amount of attention in recent years. Since NOx is a smog precursor, it is important to understand the reasons for this jump in emissions especially on hot sunny days when air conditioner usage is at a maximum. A simple thermodynamic model is used to demonstrate how the torque from a typical air conditioner compressor is mainly related to the ambient temperature. The compressor's on-off cycling patterns are also characterized. Since the compressor significantly loads the engine, it affects fuel economy and emissions. The key independent variable that we employ to represent engine load is fuel rate. The correlations between engine-out NOx emissions and fuel rate are shown for a number of light duty vehicles and trucks. From these, a physical model for engine-out NOx emissions (with and without air conditioning) is presented.

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.

In this paper the development of statistical metamodels and statistical fast running models is presented first. They are utilized for propagating uncertainties in a multi-discipline design optimization process. Two main types of uncertainty can be considered in this manner: uncertainty due to variability in design variables or in random parameters; uncertainty due to the utilization of metamodels instead of the actual simulation models during the optimization process. The value of the new developments and their engagement in multi-discipline design optimization is demonstrated through a case study. An underwater vehicle is designed under four different disciplines, namely, noise radiation, self-noise due to TBL excitation, dynamic response due to propulsion impact loads, and response to an underwater detonation.

Developing a complete understanding of the structure and behavior of the near-wall region (NWR) in reciprocating, internal combustion (IC) engines and of its interaction with the core flow is needed to support the implementation of advanced combustion and engine operation strategies, as well as predictive computational models. The NWR in IC engines is fundamentally different from the canonical steady-state turbulent boundary layers (BL), whose structure, similarity and dynamics have been thoroughly documented in the technical literature. Motivated by this need, this paper presents results from the analysis of two-component velocity data measured with particle image velocimetry near the head of a single-cylinder, optical engine. The interaction between the NWR and the core flow was quantified via statistical moments and two-point velocity correlations, determined at multiple distances from the wall and piston positions.

Wet clutch packs are widely used in today’s automatic transmission systems for gear-ratio shifting. The frictional interfaces between the clutch plates are continuously lubricated with transmission fluid for both thermal and friction management. The open clutch packs shear transmission fluid across the rotating plates, contributing to measurable energy losses. A typical multi-speed transmission includes as many as 5 clutch packs. Of those, two to three clutches are open at any time during a typical drive cycle, presenting an opportunity for fuel economy gain. However, reducing open clutch drag is very challenging, while meeting cooling requirements and shift quality targets. In practice, clutch design adjustment is performed through trial-and-error evaluation of hardware on a test bench. The use of analytical methodologies is limited for optimizing clutch design features due to the complexity of fluid-structure interactions under rotating conditions.

Naturally aspirated HCCI operation is typically limited to medium load operation (∼ 5 bar net IMEP) by excessive pressure rise rate. Boosting can provide the means to extend the HCCI range to higher loads. Recently, it has been shown that HCCI can achieve loads of up to 16.3 bar of gross IMEP by boosting the intake pressure to more than 3 bar, using externally driven compressors. However, investigating HCCI performance over the entire speed-load range with real turbocharger systems still remains an open topic for research. A 1 - D simulation of a 4 - cylinder 2.0 liter engine model operated in HCCI mode was used to match it with off-the-shelf turbocharger systems. The engine and turbocharger system was simulated to identify maximum load limits over a range of engine speeds. Low exhaust enthalpy due to the low temperatures that are characteristic of HCCI combustion caused increased back-pressure and high pumping losses and demanded the use of a small and more efficient turbocharger.