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Piston design is a challenging engineering problem which involves complex physics and requires satisfying multiple performance objectives. Uncertainty in piston operating conditions and variability in piston design variables are inevitable and must be accounted for. The piston assembly can be a major source of engine mechanical friction and cold start noise, if not designed properly. In this paper, an analytical piston model is used in a deterministic and probabilistic (reliability-based) multi-objective design optimization process to obtain an optimal piston design. The model predicts piston performance in terms of scuffing, friction and noise, In order to keep the computational cost low, efficient and accurate metamodels of the piston performance metrics are used. The Pareto set of all optimal solutions is calculated allowing the designer to choose the “best” solution according to trade-offs among the multiple objectives.

We propose a new metamodeling method to characterize the output (response) random process of a dynamic system with random parameters, excited by input random processes. The metamodel can be then used to efficiently estimate the time-dependent reliability of a dynamic system using analytical or simulation-based methods. The metamodel is constructed by decomposing the input random processes using principal components or wavelets and then using a few simulations to estimate the distributions of the decomposition coefficients. A similar decomposition is also performed on the output random process. A kriging model is then established between the input and output decomposition coefficients and subsequently used to quantify the output random process corresponding to a realization of the input random parameters and random processes. What distinguishes our approach from others in metamodeling is that the system input is not deterministic but random.

In this article we present an approach to identify the system topology using simulation for reliability calculations. The system topology provides how all components in a system are functionally connected. Most reliability engineering literature assumes that either the system topology is known and therefore all failure modes can be deduced or if the system topology is not known we are only interested in identifying the dominant failure modes. The authors contend that we should try to extract as much information about the system topology from failure or success information of a system as possible. This will not only identify the dominant failure modes but will also provide an understanding of how the components are functionally connected, allowing for more complicated analyses, if needed. We use an evolutionary approach where system topologies are generated at random and then tested against failure or success data. The topologies evolve based on how consistent they are with test data.

Design optimization often relies on computational models, which are subjected to a validation process to ensure their accuracy. Because validation of computer models in the entire design space can be costly, a recent approach was proposed where design optimization and model validation were concurrently performed using a sequential approach with both fixed and variable-size local domains. The variable-size approach used parametric distributions such as Gaussian to quantify the variability in test data and model predictions, and a maximum likelihood estimation to calibrate the prediction model. Also, a parametric bootstrap method was used to size each local domain. In this article, we generalize the variable-size approach, by not assuming any distribution such as Gaussian. A nonparametric bootstrap methodology is instead used to size the local domains. We expect its generality to be useful in applications where distributional assumptions are difficult to verify, or not met at all.

New methods are required for implementing the proliferation and sophistication of electronic controls and features to meet the customer's quality expectations. Vehicle electronic integration provides a potential solution for reconciling the seemingly contradictory objectives of high quality at reasonable cost. No module can be considered independently with this global approach. OEM subsystem and component suppliers' devices will need to play in concert with the overall vehicle's electrical/electronic strategy. Some new, separately packaged electronic features may eventually be assimilated within the framework of other electronic controllers.

Warranty forecasting of repairable systems is very important for manufacturers of mass produced systems. It is desired to predict the Expected Number of Failures (ENF) after a censoring time using collected failure data before the censoring time. Moreover, systems may be produced with a defective component resulting in extensive warranty costs even after the defective component is detected and replaced with a new design. In this paper, we present a forecasting method to predict the ENF of a repairable system using observed data which is used to calibrate a Generalized Renewal Processes (GRP) model. Manufacturing of products may exhibit different production patterns with different failure statistics through time. For example, vehicles produced in different months may have different failure intensities because of supply chain differences or different skills of production workers, for example.

This paper discusses the feasibility and issues associated with integrating a consumer off-the shelf product into a vehicle. For this evaluation, we selected a handheld personal computer (HPC), cellular telephone and modem to integrate with the vehicle audio, climate and system controls. Connectivity between the HPC and the vehicle is established by the use of the standard infrared serial data link that comes with the HPC. Connectivity outside the vehicle uses a cellular telephone for voice and a cellular digital packet data (CDPD) modem for data. This system is built into the Dodge ESX-2 hybrid powered concept vehicle for demonstration.

The rapid growth of information technology has the potential to affect many of the reasons why people drive. The Internet is arguably the most significant recent milestone in the growth of information technology. This paper examines the ways Internet communication might affect the travel experience by a) eliminating traditional reasons for personal travel, b) providing new reasons, c) changing the balance between personal and freight travel, and d) changing trip length distribution. Changes of the types listed could affect the product demand "mix" for electric, hybrid-electric and fuel cell vehicles being developed.

A systematic life cycle management (LCM) approach has been used by Chrysler Corporation to compare existing and alternate hydraulic fluids and lubricating oils in thirteen classifications at a manufacturing facility. The presence of restricted or regulated chemicals, recyclability, and recycled content of the various products were also compared. For ten of the thirteen types of product, an alternate product was identified as more beneficial. This LCM study provided Chrysler personnel with a practical purchasing tool to identify the most cost effective hydraulic fluid or lubricant oil product available for a chosen application on an LCM basis.

A complete probabilistic model of uncertainty in probabilistic analysis and design problems is the joint probability distribution of the random variables. Often, it is impractical to estimate this joint probability distribution because the mechanism of the dependence of the variables is not completely understood. This paper proposes modeling dependence by using copulas and demonstrates their representational power. It also compares this representation with a Monte-Carlo simulation using dispersive sampling.

Adhesive bonding has many applications in the automotive industry. The single-lapped bonded joint is the most typically used among various bonding types. This paper presents experimental research for determining the strain field of the single-lapped joint under tensile loading. The materials for the joint are epoxy-based structural adhesive and low-carbon electrolytic zinc steel plate. In the study, a DIC (digital image correlation) system was adopted to measure the strain distribution of the bonded joint during a tensile test. The bonded steel coupons in the tensile test were prepared according to the ASTM standard. During the measurement, images of the coupon joint were taken before and after the deformation process. Then the DIC system measured the strain of bonded joint by comparing two consecutive images. The measured data from the DIC was compared to data taken simultaneously from a traditional extensometer.

The automobile industry has an increasing demand for lightweight components, improve product performance, efficiency and increase safety. For optimization of design and manufacturing of these components the detail measurement of critical material properties such as strain limit, strength coefficients, anisotropy coefficients et al, are required. The most commonly used method for finding the material properties is tensile test with extensometer. But this system only provides an average strain over the specimen gauge length and is not applicable to post diffuse necking. Digital Image Correlation (DIC) technique is the latest state of art technique. Because of its capability of fast data acquisition, this technique is suited well for characterization of material properties both in the elastic and plastic ranges. It also has advantages of full field, non-contact, and considerately high precision for displacement and strain measurements.

Higher horsepower per liter engines have put more demand on the crankshaft, often requiring the use of forged steel. This paper examines cost reduction opportunities to offset the penalties associated with forged steel, with raw material and machinability being the primary factors evaluated. A cost model for crankshaft processing is utilized in this paper as a design tool to select the lowest cost material grade. This model is supported by fatigue and machinability data for various steel grades. Materials considered are medium carbon, low alloy, and microalloy steels; the effects of sulfur as a machining enhancer is also studied.

The automobile industry has been using high-density polyethylene (HDPE) as a material to fabricate fuel tanks. Because untreated HDPE is permeable to the primary constituents of gasoline, these fuel tanks are now being produced with various barrier technologies that significantly reduce this permeation rate. Four currently available barrier technologies are fluorination, sulfonation, coextrusion, and the laminar barrier technology. These technologies have successfully proven to decrease the permeation rate of pure gasoline. However, it is suspected that their effectiveness may be reduced when alcohols are introduced into the fuel blend. In this work, we determine the permeation rates of gasoline-alcohol fuel blends through HDPE by conducting tests on 22-gallon HDPE fuel tanks and on small HDPE bottles fabricated with and without these barrier technologies. The goal of this study is to provide a comprehensive evaluation of these four barrier technologies.

A running loss test procedure has been developed which integrates a point-source collection method to measure fuel evaporative running loss from vehicles during their operation on the chassis dynamometer. The point-source method is part of a complete running loss test procedure which employs the combination of site-specific collection devices on the vehicle, and a sampling pump with sampling lines. Fugitive fuel vapor is drawn into these collectors which have been matched to characteristics of the vehicle and the test cell. The composite vapor sample is routed to a collection bag through an adaptation of the ordinary constant volume dilution system typically used for vehicle exhaust gas sampling. Analysis of the contents of such bags provides an accurate measure of the mass and species of running loss collected during each of three LA-4* driving cycles. Other running loss sampling methods were considered by the Auto-Oil Air Quality Improvement Research Program (AQIRP or Program).

Seats play an important role in determining customer satisfaction and safety. They also represent three to five percent of the overall vehicle cost and weight. Therefore, automotive manufacturers are continuously seeking ways to improve the areas of comfort, safety, reliability, cost and weight within the seat system. The purpose of this paper is to review the development of an automotive front seat constructed of injection molded nylon frames and metal mechanisms. This development program was initiated for the purpose of reducing vehicle weight while increasing the reliability and safety of the front seats. This paper will review the material and process selection decision, a design overview, the performance criteria and the results of tests performed on the injection molded front seats.

An OEM Natural Gas Vehicle (NGV) has been developed to address recently enacted Clean-Fuel Vehicle legislation. The NGV incorporates advanced fuel storage and fuel metering technologies to produce very low emissions and to provide superior customer value compared to aftermarket conversion units.

A new, 1-D analytical engine thermal management tool was developed to model piston, oil and coolant temperatures in the Ford 3.5L engine family. The model includes: a detailed lubrication system, including piston oil-squirters, which accurately represents oil flow rates, pressure drops and component heat transfer rates under non-isothermal conditions; a detailed coolant system, which accurately represents coolant flow rates, pressure drops and component heat transfer rates; a turbocharger model, which includes thermal interactions with coolant, oil, intake air and exhaust gases (modeled as air), and heat transfer to the surroundings; and lumped thermal models for engine components such as block, heads, pistons, turbochargers, oil cooler and cooling tower. The model was preliminarily calibrated for the 3.5L EcoBoost™ engine, across the speed range from 1500 to 5500 rpm, using wide-open-throttle data taken from an early heat rejection study.

This study analyzes the vibration characteristics of the valve train of a 2.0L SOHC Chrysler Corp. Neon engine over a range of operating speeds to investigate and demonstrate the advantages and limitations of various dynamic measurements such as displacement, velocity, and acceleration in this application. The valve train was tested in a motoring fixture at speeds of 500 to 3500 camshaft rpm. The advantages of analyzing both time and frequency domain measurements are described. Both frequency and order analysis were done on the data. The theoretical order spectra of cam displacement and acceleration were computed and compared to the experimental data. Deconvolution was used to uncover characteristic frequencies of vibration in the system. The theoretical cam acceleration spectrum was deconvolved from measured acceleration spectra to reveal the frequency response function of the follower system.

A Methanol Concentration Smart Sensor has been developed to support the demand for alternately fueled vehicles operating on blends of methanol and gasoline in any mixture up to 85% methanol. The sensor measures concentration by exploiting the difference in dielectric properties between methanol and gasoline. The measurement is made based on the distributed capacitance of a coil of wire, contained in a reservoir through which the fuel passes. This signal, along with temperature compensation inputs, is then fed to an integral microprocessor, which provides a voltage output proportional to the methanol concentration of the fuel. The Powertrain Controller uses this information to modify injector pulse width and provide proper spark advance. This paper will explain the sensor's development methodology and function.