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Although computer models for vehicle and sub-system performance simulations have been developed and used extensively in the past several decades, there is currently a need to enhance the overall availability of these types of tools. Increasing demands on vehicle performance targets have intensified the need to obtain rapid feedback on the effects of vehicle modifications throughout the entire development cycle. At the same time, evolution of the PC and development of Web-based applications have contributed to the availability, accessibility, and user-friendliness of sophisticated computer analysis. Web engineering is an ideal approach in supporting globalization and is a cost-effective design-analysis integration business strategy. There is little doubt that this new approach will have positive impacts on product cost, quality, and development cycle time. This paper will show how Microsoft Excel and the Web can be powerful and effective tools in the development process.

Warpage is the distortion induced by inhomogeneous shrinkage during injection molding of plastic parts. Uncontrolled warpage will result in dimensional instability and bring a lot of challenges to the mold design and part assembly. Current commercial simulation software for injection molding cannot provide consistently accurate warpage prediction, especially for semi-crystalline thermoplastics. In this study, the root cause of inconsistency in warpage prediction has been investigated by using injection molded polypropylene plaques with a wide range of process conditions. The warpage of injection molded plaques are measured and compared to the numerical predictions from Moldex3D. The study shows that with considering cooling rate effect on crystallization kinetics and using of the improved material model for residual stress calculations, good agreements are obtained between experiment and simulation results.

The engine operating point (EOP), which is determined by the engine speed and torque, is an important part of a vehicle's powertrain performance and it impacts FC, available propulsion power, and emissions. Predicting instantaneous EOP in real-time subject to dynamic driver behaviour and environmental conditions is a challenging problem, and in existing literature, engine performance is predicted based on internal powertrain parameters. However, a driver cannot directly influence these internal parameters in real-time and can only accommodate changes in driving behaviour and cabin temperature. It would be beneficial to develop a direct relationship between the vehicle-level parameters that a driver could influence in real-time, and the instantaneous EOP. Such a relationship can be exploited to dynamically optimize engine performance.

The automotive interior suppliers are challenged to develop materials, that not only perform functionally, but also provide the right combination sensory experience (e.g. visual appeal, tactile feeling) and brand differentiation at very competitive costs. Therefore, the objective of this research presented in this paper is to develop a methodology that can be used to measure customer perception of interior materials and to come up with a unique system for assessing value of different interior materials. The overall methodology involves the application of a number of psychophysical measurement methods (e.g. Semantic Differential Scaling) and statistical methods to assess: 1) overall customer perceived quality of materials, 2) elements (or attributes) of perception, and 3) value of materials from OEM's viewpoint in terms of the measurement of perception of quality divided by a measure of cost.

Automotive exhaust system experiences vibratory and thermal loads. Bogey test had been the major validation method until recent years when the strain-life approach was adopted to evaluate component's fatigue life. In practice, when using the strain-life model to evaluate a component subjected to elevated temperature, temperature effect on component fatigue life is considered by introducing a temperature scale factor KC that is used to scale up the measured nominal strain, hence the mechanical load. This paper intends to propose a method to estimate KC by designing component bench tests at room temperature and at elevated temperature, respectively. Two major failure modes in the exhaust system are investigated and different temperature effects on the base metal fatigue and on the weld or heat-affected zone are analyzed.

In the Big Data era, the capability in statistical and probabilistic data characterization, data pattern identification, data modeling and analysis is critical to understand the data, to find the trends in the data, and to make better use of the data. In this paper the fundamental probability concepts and several commonly used probabilistic distribution functions, such as the Weibull for spectrum events and the Pareto for extreme/rare events, are described first. An event quadrant is subsequently established based on the commonality/rarity and impact/effect of the probabilistic events. Level of measurement, which is the key for quantitative measurement of the data, is also discussed based on the framework of probability. The damage density function, which is a measure of the relative damage contribution of each constituent is proposed. The new measure demonstrates its capability in distinguishing between the extreme/rare events and the spectrum events.

Spot friction welding is considered a cost-effective method for joining lightweight automotive alloys, such as magnesium and aluminum alloys. An experimental study was conducted to investigate the strength of spot friction welded joints of magnesium to magnesium, aluminum to aluminum, magnesium to aluminum and aluminum to magnesium. The joint structures and failure modes were also studied.

A novel Spatially Optimized Diffusion Alloy (SODA) material has been developed and applied to exhaust systems, which are an aggressive environment subject to high temperatures and loads, as well as excessive corrosion. Traditional stainless steels disperse chromium homogeneously throughout the material, with varying amounts ranging from 10% to 20% dependent upon its grade (e.g. 409, 436, 439, 441, and 304). SODA steels, however, offer layered concentrations of chromium, enabling an increased amount along the outer surface for much needed corrosion resistance and aesthetics. This outer layer, typically about 70μm thick, exceeds 20% of chromium concentration locally, but is less than 3% in bulk, offering selective placement of the chromium to minimize its overall usage. Since this layer is metallurgically bonded, it cannot delaminate or separate from its core, enabling durable protection throughout manufacturing processes and full useful life.

This paper describes the design and application of a business simulation to help train employees about the new business model and culture that for an automotive supplier company that designs connected vehicle and other advanced electronic products for the automotive industry. The simulation, called SIM-i-TRI, is a three to four day collaborative learning activity that simulates the executive, administrative, engineering, manufacturing, and marketing functions in three divisions of a manufacturer that supplies parts and systems to customers in industries similar to the automotive industry. It was originally designed to support the new employee orientation at the Tier 1 supplier and to provide the participants a safe environment to practice the lessons from the orientation. The simulation has been used several times a month in the US, England, and Germany for over four years.

Nowadays, the automotive industry is experiencing the advent of unprecedented applications with connected devices, such as identifying safe users for insurance companies or assessing vehicle health. To enable such applications, driving behavior data are collected from vehicles and provided to third parties (e.g., insurance firms, car sharing businesses, healthcare providers). In the new wave of IoT (Internet of Things), driving statistics and users’ data generated from wearable devices can be exploited to better assess driving behaviors and construct driver models. We propose a framework for securely collecting data from multiple sources (e.g., vehicles and brought-in devices) and integrating them in the cloud to enable next-generation services with guaranteed user privacy protection.

A modern definition of quality control and improvement is the reduction of variability in processes and products. The reduced variability can be directly translated into lower costs, better functions and fewer repairs. However, the final quality of processes and products is sometimes derived from other measured variables through some implicit or explicit functional relationships. Sometimes, a tiny uncertainty in a variable can produce a huge uncertainty in a derived quantity. Therefore, the propagation of uncertainty needs to be understood and the individual variables need to be well controlled. More importantly, the critical factors that affect quality the most should be identified and thoroughly investigated. Design of experiments and statistical control plays central roles in finding root cause of failure, reduction of variability and quality improvement.

Fatigue life assessment is an integral part of the durability and reliability evaluation process of vehicle exhaust components and systems. The probabilistic life assessment approaches, including analytical, experimental, and simulation, CAE implementation in particular, are attracting significant attentions in recent years. In this paper, the state-of-the-art probabilistic life assessment methods for vehicle exhausts under combined thermal and mechanical loadings are reviewed and investigated. The loading cases as experienced by the vehicle exhausts are first categorized into isothermal fatigue, anisothermal fatigue, and high-temperature thermomechanical fatigue (TMF) based on the failure mechanisms. Subsequently, the probabilistic life assessment procedures for each category are delineated, with emphasis on product validation.

The component being formed experiences some type of prestrain that may have an effect on its fatigue strength. This study investigated the forming effects on material fatigue strength of dual phase sheet steel (DP600) subjected to various uniaxial prestrains. In the as-received condition, DP600 specimens were tested for tensile properties to determine the prestraining level based on the uniform elongation corresponding to the maximum strength of DP600 on the stress-strain curve. Three different levels of prestrain at 90%, 70% and 50% of the uniform elongation were applied to uniaxial prestrain specimens for tensile tests and fatigue tests. Fatigue tests were conducted with strain controlled to obtain fatigue properties and compare them with the as-received DP600. The fatigue test results were presented with strain amplitude and Neuber's factor.

In this paper, a predictive method is developed to determine the forming limit strain and fracture limit strain in a stamped automotive component subjected to a complex strain history that would be experienced during an actual forming operation. The method of analysis is based on a damage mechanics model developed recently by the authors and extended to take into account the hysteretic effects of the principal strain and damage planes. The forming limit and fracture limit strains are then predicted using the modified damage model. Satisfactory predictions have been achieved for a practical case where the complex strain history is prescribed based an actual stamping operation.

Based on the theory of damage mechanics, an orthotropic damage model for the prediction of forming limit diagram (FLD) is developed. The conventional method of FLD used to predict localized necking adopts two fundamentally different approaches. Under biaxial loading, the Hill's plasticity method is often chosen when α (= ε2/ε1) < 0. On the other hand, the M-K method is adopted for the prediction of localized necking when α > 0 or the biaxial stretching of sheet metal is pronounced. The M-K method however suffers from the arbitrary selection of the imperfection size, thus resulting in inconsistent predictions. The orthotropic damage model developed for predicting the FLD is based on the anisotropic damage model recently proposed by Chow et al (1993). The model is extended to take into account, during the sheet forming process, orthotropic plasticity and damage. The orthotropic FLD model consists of the constitutive equations of elasticity and plasticity coupled with damage.

Strains in most stamped parts are produced under non-proportional loading. Limit strains induced during forming are, therefore, path dependent. Experimental Forming Limit Diagrams (FLDs) are usually determined under proportional loading and are not applicable to most forming operations. Experimental results have shown that path dependent FLDs are different from those determined under proportional loading. A number of analytical methods have been used to predict FLDs under proportional loading. The authors have recently introduced a new method for predicting FLDs based on the theory of damage mechanics. The damage model was used successfully to predict proportional FLDs for VDIF steel and Al6111-T4. In this paper, the anisotropic damage model was used to predict non-proportional FLDs for VDIF steel. Experiments were conducted to validate model predictions by applying pre-stretch in plane strain followed by uniaxial and balanced biaxial tension.

Based on findings from micromechanical studies, a Ductile Failure Criterion (DFC) was proposed. The proposed DFC treats localized necking as failure and critical damage as a function of strain path and initial sheet thickness. Under linear strain path assumption, a method to predict Forming Limit Curve (FLC) is derived from this DFC. With the help of predetermined effect functions, the method only needs a calibration at uniaxial tension. The approach was validated by predicting FLCs for sixteen different aluminum and steel sheet metal materials. Comparison shows that the prediction matches quite well with experimental observations in most cases.

Driven by diesel engine emission regulation, more emission aftertretment products have been under development by Tenneco to address the Particular Matter (PM) and NOx reduction needs. The T.R.U.E. (Thermal Regeneration Unit for Exhaust) Clean active thermal management system is one of the examples to reduce PM. The system is designed to increase exhaust temperatures for DPF (Diesel Particulate Filter) regeneration. This product is exposed to high temperature and high oxidation. Therefore, thermal fatigue, creep, oxidation and the interaction become critical mechanism to be considered for its durability. One of the key challenges to validate this product is to find a way of accelerated testing for thermal, creep, and oxidation as well as for vibration. In this paper, accelerated durability test strategy for high temperature device like T.R.U.E Clean is addressed.

This paper presents a design and development approach for automotive bucket seat frame using a parametric modeling and a finite element analysis methodology. This approach is expected to help build a lightweight seat structure quickly and efficiently. This approach is general, and it can be applied in designing and developing any mechanical structural component. The design process involves, first parametric modeling of the front bucket seat frame using Pro E. This CAD model was then optimized using optimization software called Optistruct, for two cases of load case and boundary condition. The optimized design was then tested for FMVSS seat requirements using LS-DYNA. The dynamic nature of the design approach helps in changing design parameters during different stages of the design process, until the seat structure satisfies the design criteria and the strength requirements. The construction and testing of this design and the design model are still under progress.

The typical paint bake cycle includes multiple ramps and dwells of temperature through e-coat, paint, and clear coat with exposure equivalent to approximately 190°C for up to 60 minutes. 7xxx-series aluminum alloys are heat treatable, additional thermal exposure such as a paint bake cycle could alter the material properties. Therefore, this study investigates the response of three 7xxx-series aluminum alloys with respect to conductivity, hardness, and yield strength when exposed to three oven curing cycles of a typical automotive paint operation. The results have indicated that alloy composition and artificial aging practice influence the material response to the various paint bake cycles.