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The focus of this research is to perform a detailed investigation of the tradeoffs between mass, efficiency, service factor (SF), power factor (PF), and cost of commercially available induction machines (IMs). To support this effort, data from a large number of IMs is used to establish Pareto-optimal fronts between these competing objectives. From the Pareto-optimal fronts, relatively straightforward models are formulated for the mass versus loss, cost versus loss, SF versus mass, PF versus cost. Parameters of the models are obtained using a genetic algorithm (GA).

Flexible polyurethane foam is the main cushioning element used in car seats. Optimization of an occupied seat's static and dynamic behavior requires models of foam that are accurate over a wide range of excitation and pre-compression conditions. In this research, a method is described to estimate the parameters of a global model of the foam behavior from data gathered in a series of impulse tests at different settling points. The estimated model is capable of describing the responses gathered from all the impulse tests using a unique set of parameters. The global model structure includes a nonlinear elastic term and a hereditary viscoelastic term. The model can be used to predict the settling point for each mass used and, by expanding the model about that settling point, local linear models of the response to impulsive excitation can be derived. From this analysis the relationship between the local linear model parameters and the global model parameters is defined.

Magnetic Resonance Velocimetry (MRV) measurements are performed in 1:1 scale models of a single-cylinder optical engine to investigate the differences in the inlet flow due to geometrical changes of the cylinder head. The models are steady flow water-analogue of the optical IC engine with a fixed valve lift of 9.21 mm to simulate the induction flow at 270° bTDC. The applicability of MRV to engine flows despite the differences in experimental operating parameters between the steady flow model and the optical IC engine are demonstrated and well addressed in this manuscript and in a previous work [1]. To provide trust into the MRV measurements, the data is validated with phase-averaged particle image velocimetry (PIV) measurements performed within the optical engine. The main geometrical changes between the cylinder heads include a variation of intake valve diameter and slight modifications to the exit of the intake port.

The interaction of fuel sprays and in-cylinder flow in direct-injection engines is expected to alter kinetic energy and integral length scales at least during some portions of the engine cycle. High-speed particle image velocimetry was implemented in an optical four-valve, pent-roof spark-ignition direct-injection single-cylinder engine to quantify this effect. Non-firing motored engine tests were performed at 1300 RPM with and without fuel injection. Two fuel injection timings were investigated: injection in early intake stroke represents quasi-homogenous engine condition; and injection in mid compression stroke mimics the stratified combustion strategy. Two-dimensional crank angle resolved velocity fields were measured to examine the kinetic energy and integral length scale through critical portions of the engine cycle. Reynolds decomposition was applied on the obtained engine flow fields to extract the fluctuations as an indicator for the turbulent flow.

Driving cycles play a fundamental role in the design of components, in the optimization of control strategies for drivetrain topologies, and in the identification of vehicle properties. The focus on a single or a few test cycles results in a risk of non-optimal or even poor design regarding the real usage profiles. Ideally, multiple different driving cycles that are representative of the real and scattering operating conditions are used. Therefore, tools for the stochastic generation of representative driving cycles are required, and many works have addressed this issue with different approaches. Until now, the stochastic generation of representative testing cycles has been limited to low dimensionality, and only a few works have studied higher dimensionality using Markov chain theory. However, it is mandatory to create tools that can stochastically generate multidimensional cycles incorporating all relevant operating conditions and maintaining signal dependency at the same time.

The thorough understanding of the effects due to the fuel direct injection process in modern gasoline direct injection engines has become a mandatory task to meet the most demanding regulations in terms of pollutant emissions. Within this context, computational fluid dynamics proves to be a powerful tool to investigate how the in-cylinder spray evolution influences the mixture distribution, the soot formation and the wall impingement. In this work, the authors proposed a comprehensive methodology to simulate the air-fuel mixture formation into a gasoline direct injection engine under multiple operating conditions. At first, a suitable set of spray sub-models, implemented into an open-source code, was tested on the Engine Combustion Network Spray G injector operating into a static vessel chamber. Such configuration was chosen as it represents a typical gasoline multi-hole injector, extensively used in modern gasoline direct injection engines.

In the present study, a model experiment is performed in order to clarify the ventilation characteristics of car cabin. This study also provides high precision data for benchmark test. As a first step, the ventilation mode is tested, which is one of the representative air-distribution modes. Part 1 describes the properties of the flow field in the cabin obtained by the experiment. Part 2 describes the ventilation efficiencies such as the age of air by using trace gas method. The properties of flow field are measured using particle image velocimetry (PIV). The mean velocity profiles, the standard deviation distribution, and the turbulence intensity distribution are discussed. The brief comparison between experiments and predictions of computational fluid dynamics (CFD) is also presented. In the comparison between experiment and CFD, the results showed similar flow field.

Numerical simulations are performed to investigate noise generated by flow in automotive HVAC ducts. A hybrid computational method for analyzing flow noise is applied: Large Eddy Simulation (LES) for predicting flow fields and Multi-domain boundary element method for predicting acoustic propagation. LES gives time-resolved solutions of flow velocity and pressure fields. By applying the acoustic analogy theory, the unsteady flow parameters are translated into sound source in evaluating the acoustic propagation. The computational result shows the noise caused by the HVAC ducts is strong. The noise is of broadband with a peak value at 370Hz. A major contribution of the noise generation is from the center ducts. Two design modifications of the center ducts are explored to regulate the flow structures with the ducts for reducing noise generation. Test results demonstrate the effectiveness of the modifications.

A unique concept for a multi-body test rig enabling the simulation of longitudinal, steering and vertical dynamics was developed at the Institute for Mechatronic Systems (IMS) at TU Darmstadt. A prototype of this IMS test rig is currently being built. In conjunction with the IMS test rig, the Vehicle Terrain Performance Laboratory (VTPL) at Virginia Tech further developed a full car, seven degree of freedom (7 DOF) simulation model capable of accurately reproducing measured displacement, pitch, and roll of the vehicle body due to terrain excitation. The results of the 7 DOF car model were used as the reference input to the multi-body IMS test rig model. The goal of the IMS/VTPL joint effort was to determine whether or not a controller for the IMS test rig vertical actuator could accurately reproduce wheel displacements due to different measured terrain constraints.

A mixed time-scale subgrid large eddy simulation was used to simulate mixture formation, combustion and soot formation under the influence of turbulence during diesel engine combustion. To account for the effects of engine wall heat transfer on combustion, the KIVA code's standard wall model was replaced to accommodate more realistic boundary conditions. This were carried out by implementing the non-isothermal wall model of Angelberger et al. with modifications and incorporating the log law from Pope's method to account for the wall surface roughness. Soot and NOx emissions predicted with the new model are compared to experimental data acquired under various EGR conditions.

Low frequency torsional vibrations can be a significant source of objectionable vehicle vibrations and in-vehicle boom, especially with changes in engine operation required for improved fuel economy. These changes include lower torque converter lock-up speeds and cylinder deactivation. This paper has two objectives: 1) Examine the effect of increased torsional vibrations on vehicle NVH performance and ways to improve this performance early in the program using test and simulation techniques. The important design parameters affecting vehicle NVH performance will be identified, and the trade-offs required to produce an optimized design will be examined. Also, the relationship between torsional vibrations and mount excursions, will be examined. 2) Investigate the ability of simulation techniques to predict and improve torsional vibration NVH performance. Evaluate the accuracy of the analytical models by comparison to test results.

When performing vibration analysis of complex vehicle structures, it is often important to be able to evaluate the effects of design changes in one or more substructures (e.g., for design optimization). It may also be convenient to allow different components to be modeled independently by different groups or organizations. For both cases, it is inevitable that some substructures will have non-matching finite element meshes at the interface where they are physically connected. Thus, a key challenge is to be able to handle the dynamic assembly of components with non-matching meshes and the subsequent global vibration analysis in a systematic and efficient manner. To tackle this problem, the enhancement of component mode synthesis methods for handling finite element models partitioned into non-matching substructures is considered in this paper. Some existing methods are reviewed, and new methods are developed.

NVH refinement of passenger vehicles is crucial to customer acceptance of contemporary vehicles. This paper describes the vehicle NVH development process, with specific examples from a Diesel sedan application that was derived from gasoline engine-based vehicle architecture. Using an early prototype Diesel vehicle as a starting point, this paper examines the application of a Vehicle Interior Noise Simulation (VINS) technique in the development process. Accordingly, structureborne and airborne noise shares are analyzed in the time-domain under both steady-state and transient test conditions. The results are used to drive countermeasure development to address structureborne and airborne noise refinement. Examples are provided to highlight the refinement process for “Diesel knocking” under idle as well as transient test conditions. Specifically, the application of VINS to understanding the influence of high frequency dynamic stiffness of hydro-mounts on Diesel clatter noise is examined.

This paper investigates the aerodynamic simulation accuracy of several types of wind tunnel test sections. Computational simulations were performed with a closed wheel race car in an 11.0 m2 adaptive wall, a 16.8 m2 open jet, and a 29.7 m2 slotted wall test section, corresponding to model blockage ratios of 20.9%, 13.7%, and 7.7%, respectively. These are compared to a simulation performed in a nearly interference-free condition having a blockage ratio of 0.05%, which for practical purposes of comparison, is considered a free air condition. The results demonstrate that the adaptive wall most closely simulates the free air condition without the need for interference corrections. In addition to this advantage, the significantly smaller size of the adaptive wall test section offers lower capital and operating costs.

Near-term energy policy for ground transportation is likely to have a strong focus on both gains in efficiency as well as the use of alternate fuels; as both can reduce crude oil dependence and carbon loading on the environment. Stratified-charge spark-ignition direct-injection (SIDI) engines are capable of achieving significant gains in efficiency. In addition, these engines are likely to be run on alternative fuels. Specifically, lower alcohols such as ethanol and iso-butanol, which can be produced from renewable sources. SIDI engines, particularly the spray-guided variant, tend to be very sensitive to mixture preparation since fuel injection and ignition occur within a short time of each other. This close spacing is necessary to form a flammable mixture near the spark plug while maintaining an overall lean state in the combustion chamber. As a result, the physical properties of the fuel have a large effect on this process.

Direct injection of natural gas under high pressure conditions has emerged as a promising option for improving engine fuel economy and emissions. However, since the gaseous injection technology is new, limited experience exists as to the optimum configuration of the injection system and associated combustion chamber design. The present study uses KIVA-3 based, multidimensional modeling to improve the understanding and assist the optimization of the gaseous injection process. Compared to standard k-ε models, a Renormalization Group Theory (RNG) based k-ε model [1] has been found to be in better agreement with experiments in predicting gaseous penetration histories for both free and confined jet configurations. Hence, this validated RNG model is adopted here to perform computations in realistic engine geometries.

An experimental and numerical study was conducted on the spray and mixture properties of a hole-type injector for direct injection (D. I.) gasoline engines. The Laser Absorption Scattering (LAS) technique was adopted to simultaneously measure the spatial concentration distributions and the mass of the liquid and vapor phases in the fuel spray injected into a high-pressure and high-temperature constant volume vessel. The experimental results were compared to the numerical calculation results using three-dimensional CFD and the multi-objective optimization. In the numerical simulation, the design variable of the spray model was optimized by choosing spray tip penetration, and mass of liquid and vapor phases as objective functions.

The hybrid Finite Element Analysis (hybrid FEA) has been developed for performing structure-borne computations in automotive vehicle structures [1, 2 and 3]. The hybrid FEA method combines conventional FEA with Energy FEA (EFEA). Conventional FEA models are employed for modeling the behavior of the stiff members in a system. Appropriate damping and spring or mass elements are introduced in the connections between stiff and flexible members in order to capture the presence of the flexible members during the analyses of the stiff ones. The component mode synthesis method is combined with analytical solutions for determining the driving point conductance at joints between stiff and flexible members and for defining the properties of the concentrated elements which represent the flexible members when analyzing the stiff components.

A naturally-aspirated, Miller cycle, Spark-Ignition (SI) engine that controls output with variable intake valve closure is compared to a conventionally-throttled engine using computer simulation. Based on First and Second Law analyses, the two load control strategies are compared in detail through one thermodynamic cycle at light load conditions and over a wide range of loads at 2000 rpm. The Miller Cycle engine can use late intake valve closure (LIVC) to control indicated output down to 35% of the maximum, but requires supplemental throttling at lighter loads. The First Law analysis shows that the Miller cycle increases indicated thermal efficiency at light loads by as much as 6.3%, primarily due to reductions in pumping and compression work while heat transfer losses are comparable.

One of the primary reasons that FMVSS 111 currently requires flat rearview mirrors as original equipment on the driver's side of passenger cars is a concern that convex mirrors might reduce safety by causing drivers to overestimate the distances to following vehicles. Several previous studies of the effects of convex rearview mirrors have indicated that they do cause overestimations of distance, but of much lower magnitude than would be expected based on the mirrors' levels of image minification and the resulting visual angles experienced by drivers. Previous studies have investigated mirrors with radiuses of curvature up to 2000 mm. The present empirical study was designed to investigate the effects of mirrors with larger radiuses (up to 8900 mm). Such results are of interest because of the possible use of large radiuses in some aspheric mirror designs, and because of the information they provide about the basic mechanisms by which convex mirrors affect distance perception.