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Automotive engines are regularly utilized in the material handling market where LPG is often the primary fuel used. When compared to gasoline, the use of gaseous fuels (LPG and CNG) as well as alcohol based fuels, often result in significant increases in valve seat insert (VSI) and valve face wear. This phenomenon is widely recognized and the engine manufacturer is tasked to identify and incorporate appropriate valvetrain material and design features that can meet the ever increasing life expectations of the end-user. Alternate materials are often developed based on laboratory testing – testing that may not represent real world usage. The ultimate goal of the product engineer is to utilize accelerated lab test procedures that can be correlated to field life and field failure mechanisms, and then select appropriate materials/design features that meet the targeted life requirements.

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.

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.

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.

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.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

An optimum combustion chamber was designed for a reverse-tumble wall-controlled gasoline direct-injection engine by systematically optimizing each design element of the combustion system. The optimization was based on fuel-economy, hydrocarbon, combustion-stability and smoke measurements at a 2000 rev/min test-point representation of road-load operating condition. The combustion-chamber design parameters that were optimized in this study included: piston-bowl depth, piston-bowl opening width, piston-bowl-volume ratio, exhaust-side squish height, bowl-lip draft angle, distance between spark-plug electrode and piston-bowl lip, spark-plug-electrode length, and injector spray-cone angle. No attempt was made to optimize the gross engine parameters such as bore and stroke or the intake system, since this study focused on optimizing a reverse-tumble wall-controlled gasoline direct-injection variant of an existing port-fueled injection engine.

Superior fuel economy was achieved for a small-displacement spark-ignition direct-injection (SIDI) engine by optimizing the stratified combustion operation. The optimization was performed using computational analyses and subsequently testing the most promising configurations experimentally. The fuel economy savings are achieved by the use of a multihole injector with novel spray shape, which allows ultra-lean stratification for a wide range of part-load operating conditions without compromising smoke and hydrocarbon emissions. In this regard, a key challenge for wall-controlled SIDI engines is the minimization of wall wetting to prevent smoke, which may require advanced injection timings, while at the same time minimizing hydrocarbon emissions, which may require retarding injection and thereby preventing over-mixing of the fuel vapor.

Full-load operation of a small-displacement spark-ignition direct-injection (SIDI) engine was thoroughly investigated by means of computational analysis and engine measurements. The performance is affected by many different factors, which can be grouped as those pertaining to volumetric efficiency, to mixing and stratification, and to system issues, respectively. Volumetric efficiency is affected by flow losses, tuning and charge cooling. Charge cooling due to spray vaporization is often touted as the most significant benefit of direct-injection on full-load performance. However, if wall wetting occurs, this benefit may be completely negated or even reversed. The fuel-air mixing is strongly affected by the injection timing and characteristics at lower engine speeds, while at higher engine speeds the intake flow dominates the transport of fuel particles and resultant vapor distribution. A higher injector flow rate enhances mixing especially at higher engine speeds.

The equipment for collecting dilute exhaust samples involves the use of bag materials (i.e., Tedlar®) that emit hydrocarbons that contaminate samples. This study identifies a list of materials and treatments to produce bags that reduce contamination. Based on the average emission rates, baked Tedlar®, Capran® treated with alumina deposition, supercritical CO2 extracted Kynar® and supercritical CO2 extracted Teflon NXT are capable of achieving the target hydrocarbon emission rate of less than 15 ppbC per 30 minutes. CO2 permeation tests were also performed. Tedlar, Capran, Kynar and Teflon NXT showed comparable average permeation rates. Based on the criteria of HC emission performance, changes in measured CO2 concentration, ease of sealing, and ease of surface treatment, none of the four materials could be distinguished from one another.

With the revolutionary advances in computing power and software technology, the future trend of integrating design and CFD analysis software package to realize an automated design optimization has been explored in this study. The integrated process of UG, ICEMCFD, and FLUENT was accomplished using iSIGHT for vehicle Aero/Thermal applications. Process integration, CFD solution strategy, optimization algorithm and the practicality for real world problem of this process have been studied, and will be discussed in this paper. As an example of this application, the results of an underhood thermal design will be presented. The advantage of systematical and rapid design exploration is demonstrated by using this integrated process. It also shows the great potential of computer based design automation in vehicle Aero/Thermal development.