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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.

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.

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.

The Energy Finite Element Analysis (EFEA) has been developed for computing the structural vibration and the interior noise level of complex structural-acoustic systems by solving numerically governing differential equations with energy densities as primary variables. In this paper a complete simulation process for evaluating airborne noise in an automotive vehicle is presented and validated through extensive comparison to test data. The theoretical elements associated with the important paths of the noise transfer from the exterior of the vehicle to the interior acoustic space are discussed. The steps required for developing an EFEA model for a vehicle are presented. The model is developed based on the physical construction of the vehicle system and no test measurements are utilized for adjusting the numerical model.

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.

The Energy Finite Element Analysis(EFEA) is a recent development for high frequency vibro-acoustic analysis, and constitutes an evolution in the area of high frequency computations. The EFEA is a wave based approach, while the SEA is a modal based approach. In this paper the similarities in the theoretical development of the two methods are outlined. The main scope of this paper is to establish the validity of the EFEA by analyzing several complex structural-acoustic systems. The EFEA solutions are compared successfully to SEA results and to solutions obtained from extremely dense conventional FEA models.

This paper presents a validation case study for an Energy Finite Element Analysis (EFEA) formulation through comparison to test data. The EFEA comprises a simulation tool for computing the structural response of a complex structure and the amount of the radiated power. The EFEA formulation presented in this paper can account for periodic stiffeners, for partial fluid loading effects on the outer part of the structure, and for internal compartments filled with heavy fluid. In order to validate these modeling capabilities of the EFEA two 1/8th scale structures representing an advanced double hull design and a conventional hull design of a surface ship are analyzed. Results for the structural vibration induced on the outer bottom part of the structure are compared to available test data. The excitation is applied at two different locations of the deck structure. Good correlation is observed between the numerical results and the test data.

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.

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.

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.

The flow field contained within ten planes inside a cylinder of a 3.5 liter, 24-valve, V-6 engine was mapped using a three-dimensional Laser Doppler Velocimetry (3-D LDV) system. A total of 1,548 LDV measurement locations were used to construct the time history of the in-cylinder flow fields during the intake and compression strokes. The measurements began during the intake stroke at a crank angle of 60° ATDC and continued until approximately 280° ATDC. The ensemble averaged LDV measurements allowed for a quantitative analysis of the dynamic in-cylinder flow process in terms of tumble and swirl motions. Both of these quantities were calculated at every 1.8 crank degrees during the described measurement interval. Tumble calculations were performed about axes in multiple planes in both the Cartesian directions perpendicular to the plane of the piston top. Swirl calculations were also accomplished in multiple planes that lie parallel to the plane of the piston top.

This work investigates the potential improvements in vehicle fuel economy possible by optimizing gear shift strategies to leverage a novel boosting device, an electrically assisted variable speed supercharger (EAVS), also referred to as a power split supercharger (PSS). Realistic gear shift strategies, resembling those commercially available, have been implemented to control upshift and downshift points based on torque request and engine speed. Using a baseline strategy from a turbocharged application of a MY2015 Ford Escape, a vehicle gas mileage of 34.4 mpg was achieved for the FTP75 drive cycle before considering the best efficiency regions of the supercharged engine.

This paper provides insight into the tradeoffs between exhaust energy recovery and increased pumping losses from the flow restriction of the electric turbo-generator (eTG) assessed using thermodynamic principles and with a detailed GT-Power engine model. The GT-Power engine model with a positive displacement expander model was used to predict the influence of back pressure on in-cylinder residuals and combustion. The eTG is assessed for two boosting arrangements: a conventional turbocharger (TC) and an electrically assisted variable speed (EAVS) supercharger (SC). Both a low pressure (post-turbine) and high pressure (pre-turbine) eTG are considered for the turbocharged configuration. The reduction in fuel consumption (FC) possible over various drive cycles is estimated based on the steady-state efficiency of frequently visited operating points assuming all recovered energy can be reused at an engine efficiency of 30% with 10% losses in the electrical path.

The thermal durability of a large frontal area cordierite ceramic wall-flow filter for light-duty diesel engine is examined under various regeneration conditions. The radial temperature distribution during burner regeneration, obtained by eight different thermocouples at six different axial sections of a 75″ diameter x 8″ long filter, is used together with physical properties of the filter to compute thermal stresses via finite element analysis. The stress-time history of the filter is then compared with the strength and fatigue characteristics of extruded cordierite ceramic monolith. The successful performance of the filter over as many as 1000 regenerations is attributed to three important design parameters, namely unique filter properties, controlled regeneration conditions, and optimum packaging design. The latter induces significant radial and axial compression in the filter thereby enhancing its strength and reducing the operating stresses.

Finite element methods can be used to simulate a class of variation problems induced by build distortion in the assembly process. The FEM approach was used to study two representative assembly problems: 1) Front fender mounting and resulting distortion due to various fastening sequences; and, 2) Coupe door assembly process and resulting deformation due to clamping and welding of flexible sheet metal parts. FEM is used to generate sensitivities of various process conditions. Correlation with measured Co-ordinate Measuring Machine (CMM) data is shown. The use of FEM to simulate manufacturing/assembly processes in the automotive industry is in it's infancy. As the new methods are developed this capability can be used to study the assembly process and provide guidance in designing more robust parts and assembly processes.