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A fully flexible valve actuation (FFVA) system was developed for a single cylinder research engine to investigate high efficiency clean combustion (HECC) in a diesel engine. The main objectives of the study were to examine the emissions, performance, and combustion characteristics of the engine using late intake valve closing (LIVC) to determine the benefits and limitations of this strategy to meet Tier 2 Bin 5 NOx requirements without after-treatment. The most significant benefit of LIVC is a reduction in particulates due to the longer ignition delay time and a subsequent reduction in local fuel rich combustion zones. More than a 95% reduction in particulates was observed at some operating conditions. Combustion noise was also reduced at low and medium loads due to slower heat release. Although it is difficult to assess the fuel economy benefits of LIVC using a single cylinder engine, LIVC shows the potential to improve the fuel economy through several approaches.

The GREEN-MAC-LCCP© [Global Refrigerants Energy & Environmental - Mobile Air Condition - Life Cycle Climate Performance] model described here is an evolution of a previous GM model that assesses the lifecycle energy and GHG emissions associated with the production, use and disposal of alternative refrigerants and MAC components. This new model reduces the complexity of inputs and provides a consistent output analysis. This model includes Microsoft Excel Visual Basic© code to automatically make the calculations once inputs are complete.

The purpose of this paper is to present the results of hot surface ignition (HSI) testing and American Society for Testing and Materials (ASTM) auto-ignition testing (AIT) performed on gasoline fuel mixtures containing varying levels of ethanol. With the increased consumer interest in ethanol-based fuels as a measure of reducing the United States dependence on foreign oil, the use of E85 and other ethanol/petroleum fuel blends is on the increase. While some autoignition data for summer and winter blends of gasoline on hot surfaces exist beyond the standard ASTM E659-78 test procedure [1], there is little data on ethanol-based fuels and their HSI characteristics.

A numerical investigation of automobile sunroof buffeting on a prototype sport utility vehicle (SUV) is presented, including experimental validation. Buffeting is an unpleasant low frequency booming caused by flow-excited Helmholtz resonance of the interior cabin. Accurate prediction of this phenomenon requires accounting for the bi-directional coupling between the transient shear layer aerodynamics (vortex shedding) and the acoustic response of the cabin. Numerical simulations were performed using the PowerFLOW code, a CFD/CAA software package from Exa Corporation based on the Lattice Boltzmann Method (LBM). The well established LBM approach provides the time-dependent solution to the compressible Navier-Stokes equations, and directly captures both turbulent and acoustic pressure fluctuations over a wide range of scales given adequate computational grid resolution.

This paper presents an innovative automobile application of Computational Fluid Dynamics (CFD) as a complement to wind tunnel experimentation for the evaluation of rain water and wiper wash flow on the exterior of a moving vehicle. In addition to calculating the air flow around a car, a multi-phase CFD code was used to simulate rain drops in the air stream, rain drops impinging on the vehicle, and the transport of the “thin liquid film” of water on the vehicle surfaces. Time-dependent results for the location, velocity, and height of the water film on the windshield, A-pillar, and side glass were obtained. The CFD results compared favorably with a wind tunnel procedure. The variation of the calculated water film corresponded with observed patterns of water streaks on test vehicles. Design iterations performed on the computational model also agreed with similar test configurations.

The new regulations to reduce emissions have resulted in the development of new techniques to maintain or enhance competitive performance. A requirement for the manifold is to help meet the reduction in cold start emissions, particularly during the transient conditions from start to 100 seconds following the Federal Test Procedures for vehicle emissions. Finite element computer models were developed to predict inner and outer wall temperatures, and to determine structural soundness. Tests were performed to assure that noise levels were minimized. Dynamometer lab and field tests were performed to verify that the manifold would meet the design requirements. From the results of these tests and analyses, modifications were made to the weld and manufacturing techniques to improve product life and reduce noise. Dual wall manifolds have proven durability to meet high exhaust gas temperatures up to 1650°F (900°C), while meeting the performance, noise, and weight reduction goals.

Development and integration of the cooling system for an automotive vehicle requires a balancing act between several performance and styling objectives. The cooling system needs to provide sufficient air for heat rejection with minimal impact on the aerodynamic drag, styling requirements and other criteria. An optimization of various design parameters is needed to develop a design to meet these objectives in a short amount of time. Increase in the accuracy of the numerical predictions and reduction in the turn-around time has made it possible for Computational Fluid Dynamics (CFD) to be used early in the design phase of the vehicle development. This study shows application of the CFD for robust design of the engine cooling system.

Tensile measurements and fracture surface analysis of low carbon heat-treated boron steel are reported. Tensile coupons were quasi-statically deformed to fracture in a miniature tensile testing stage with custom data acquisition software. Strain contours were computed via a digital image correlation method that allowed placement of a digital strain gage in the necking region. True stress-true strain data corresponding to the standard tensile testing method are presented for comparison with previous measurements. Fracture surfaces were examined using scanning electron microscopy and the deformation mechanisms were identified.

In an endeavor to improve upon historically subjective and hardware-based steering tuning development, a team was formed to find an optimal and objective solution using Design For Six Sigma (DFSS). The goal was to determine the best valve assembly design within a hydraulic power-steering assist system to yield improved steering effort and feel robustness for all vehicle models in a future truck program. The methodology utilized was not only multifaceted with several Design of Experiments (DOEs), but also took advantage of a CAE-based approach leveraging modeling capabilities in ADAMS for simulating full-vehicle, On-Center Handling behavior. The team investigated thirteen control factors to determine which minimized a realistic, compounded noise strategy while also considering the ideal steering effort function (SEF) desired by the customer. In the end, it was found that response-dependent variability dominated the physics of our valve assembly design concept.

Simultaneously obtaining a linear temperature control curve along with the correct temperature stratification at module outlets is one of the most difficult tasks in developing an automotive HVAC module. Traditionally, Computational Fluid Dynamics (CFD) development of temperature control linearity has been accomplished by iteratively adjusting the location, size and orientation of baffles which redirect warm and cold airstreams. This approach demands considerable interaction from the engineer in building the computational mesh, defining boundary and operating conditions and post processing the simulation results. The present study was conducted to investigate the optimization of HVAC temperature regulation curves using the multi-objective optimization code modeFrontier (1, 3) in conjunction with CFD code, Fluent (2). An auxiliary HVAC module was selected for the present study.

Well-to-Wheels analyses are important tools that provide a rigorous examination and quantify the environmental burdens associated with fuel production and fuel consumption during the vehicle use phase. Such assessments integrate the results obtained from the Well-to-Tank (WtT) and the Tank-to-Wheels (TtW) analysis components. The purpose of this study is to provide a preliminary Tank-to-Wheels assessment of the benefits associated with the introduction of alternative powertrains and fuels in the Chinese market by the year 2015 as compared to the results obtained with conventional internal combustion engine vehicles (ICEVs). An emphasis is given on the vehicles powered by those fuels that have the potential to play a major role in the Chinese auto-sector, such as: M10, M85, E10, E85, Di-methyl Ether (DME) and Coal-to-Liquids (CTL). An important conclusion of this report is that hybridization reduces fuel consumption in all propulsion systems.

Managing (minimizing and optimizing) the total mass of a vehicle is recognized as a critical task during the development of a new vehicle, as well as throughout its production lifecycle. This paper summarizes a literature review of, and investigation into, the strategies, methods and best practices for achieving low total mass in new vehicle programs, and/or mass reductions in existing production vehicle programs. Empirical and quantitative data and examples from the automotive manufacturers and suppliers are also provided in support of the material presented.

This study involves an application of Principal Component Analysis (PCA) conducted in support of a Design for Six Sigma (DFSS) project. Primary focus of the project is to optimize seat parameters that influence Low Speed Rear Impact (LSRI) whiplash performance. During the DFSS study, the project team identified a need to rank order critical design factors statistically and establish their contribution to LSRI performance. It is also required to develop a transfer function for the LSRI rating in terms of test response parameters that can be used for optimization. This statistical approach resulted in a reliable transfer function that can applied across all seat designs and enabled us to separate vital few parameters from several many.

In today’s highly competitive automotive environment people are always looking to develop processes that are fast, efficient, and effective. Moving testing from expensive prototype vehicles into the laboratory is an approach being implemented for many different vehicle subsystems. Specifically a process has recently been developed at General Motors that predicts exhaust back pressure performance for a running vehicle using laboratory testing and spreadsheet calculations. This paper describes the laboratory facility and procedure, the theory behind the calculations, and the correlation between vehicle test and laboratory based results. It also comments on the benefits of the process with respect to reduction in design iterations, quicker availability of results, and money savings.

Reducing Carbon Dioxide (CO2) emissions is one of the major challenges for automobile manufacturers. This is driven by environmental, consumer, and regulatory demands in all major regions worldwide. For conventional vehicles, a host of technologies have been applied that improve the overall efficiency of the vehicle. This reduces CO2 contributions by directly reducing the amount of energy consumed to power a vehicle. The hybrid electric vehicle (HEV) continues this trend. However, there are limits to CO2 reduction due to improvements in efficiency alone. Other major improvements are realized when the CO2 content of the energy used to motivate vehicles is reduced. With the introduction of Extended Range Electric Vehicles (E-REVs) and Plug-in HEVs (PHEVs), electric grid energy displaces petroleum. This enables the potential for significant CO2 reductions as the CO2 per unit of electrical energy is reduced over time with the improving mix of energy sources for the electrical grid.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

Diesel engines offer better fuel economy compared to their gasoline counterpart, but simultaneous control of NOx and particulates is very challenging. The blended 2-way SCR/DPF is recently emerging as a compact and cost-effective technology to reduce NOx and particulates from diesel exhaust using a single aftertreatment device. By coating SCR catalysts on and inside the walls of the conventional wall-flow filter, the 2-way SCR/DPF eliminates the volume and mass of the conventional SCR device. Compared with the conventional diesel aftertreatment system with a SCR and a DPF, the 2-way SCR/DPF technology offers the potential of significant cost saving and packaging flexibility. In this study, an engine dynamometer test cell was set up to repeatedly load and regenerate the SCR/DPF devices to mimic catalyst aging experienced during periodic high-temperature soot regenerations in the real world.

This paper demonstrates the benefit of using simulation and robust optimization for the problem of balancing vehicle noise, vibration, and ride performance over road impacts. The psychophysics associated with perception of vehicle performance on an impact is complex because the occupants encounter both tactile and audible stimuli. Tactile impact vibration has multiple dimensions, such as impact hardness and memory shake. Audible impact sound also affects occupant perception of the vehicle quality. This paper uses multiple approaches to produce the similar, robust, optimized tuning strategies for impact performance. A Design for Six Sigma (DFSS) project was established to help identify a balanced, optimized solution. The CAE simulations were combined with software tools such as iSIGHT and internally developed Kriging software to identify response surfaces and find optimal tuning.

In this article, the authors illustrate the benefits of axiomatic design (AD) for robust optimization and how to integrate axiomatic design into a total robust design process. Similar to traditional robust design, the purpose of axiomatic design is to improve the probability of a design in meeting its functional targets at early concept generation stage. However, axiomatic design is not a standalone method or tool and it needs to be integrated with other tools to be effective in a total robust development process. A total robust development process includes: system design, parameter design, tolerance design, and tolerance specifications [1]. The authors developed a step-by-step procedure for axiomatic design practices in industrial applications for consistent and efficient deliverables. The authors also integrated axiomatic design with the CAD/CAE/statistical/visualization tools and methods to enhance the efficiency of a total robust development process.

A DFSS study identified a new mechanism for clamp load loss in aluminum threads due to thermal cycling. In bolted joints tightened to yield, the difference in thermal expansion between the aluminum and steel threads can result in a loss of clamp load with each thermal cycle. This clamp load loss is significantly greater than the loss that can be explained by creep alone. A math model was created and used to conduct a robust analysis. This analysis led to an understanding of the design factors necessary to reduce the cyclic clamp load loss in the aluminum threads. This understanding was then used to create optimized design solutions that satisfy constraints common to powertrain applications. Estimations of clamp load loss due to thermal cycling from the math model will be presented. The estimates of the model will be compared to observed physical test data. A robust analysis, including S/N and mean effect summary will be presented.