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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.

Manufacturing processes often produce a large amount of heat, which needs to be pumped out of the factory to maintain thermal stability and comfort. Thermal comfort is essential to maintain a suitable working environment in a factory. It has a strong impact on the health and productivity of workers. In addition, it is mandatory to keep the working environment within specified thermal and relative humidity ranges. Periodic assessments of these thermal parameters is routine in most factories. Inclusion of additional manufacturing equipment or processes can lead to a significant change in the working environment and consequent comfort, this needs to be addressed quickly. Rather than wait to measure these effects it is preferable to develop a reliable simulation method for the proactive study and improvement of thermal comfort levels. A reliable simulation approach is developed in this study for the prediction of thermal comfort in an automotive manufacturing plant.

In many fields of technology, examinations of the past can provide insights into the future. This paper reviews the last 20 years of automotive seat comfort development and research as chronicled by SAE’s session titled “Human Factors in Seating Comfort”. Records suggest that “Human Factors in Seating Comfort” has existed as a separate session at SAE’s World Congress since 1999. In that time there have been 148 unique contributions (131 publications). The history is fascinating because it reflects interests of the time that are driven by technology trends, customer wants and needs, and new theories. The list of contributors, in terms of authors and their affiliations, is also telling. It shows shifts in business models and strategies around collaboration. The paper ends with a discussion of what can be learned from this historical review and the major issues to be addressed. One of the more significant contributions of this paper is the reference list.

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.

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.

The thermal efficiency of an internal combustion engine at steady state temperatures is typically in the region of 25-35%[1]. In a cold start situation, this reduces to be between 10% and 20% [2]. A significant contributor to the reduced efficiency is poor performance by the engine lubricant. Sub optimal viscosity resulting from cold temperatures leads to poor lubrication and a subsequent increase in friction and fuel consumption. Typically, the engine lubricant takes approximately twenty minutes [3] to reach steady state temperatures. Therefore, if the lubricant can reach its steady state operating temperature sooner, the engine's thermal efficiency will be improved. It is hypothesised that, by decoupling the lubricant from the thermal mass of the surrounding engine architecture, it is possible to reduce the thermal energy loss from the lubricant to the surrounding metal structure in the initial stages of warm-up.

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.

A CAE simulation methodology was developed to predict the warpage and shape deviation from nominal in finished plastic sub-assemblies that are joined using Infra-Red (IR), hot-plate or vibration welding processes. An automotive glove box bin and door sub-assembly was used to develop the methodology. It was seen that part warpage from injection molding and welding causes warpage in final assembled product which results in gaps and the consequent loss in quality of appearance. The CAE simulation methodology included prediction of the part warpage with residual stress from the injection molding process, use the post-molded shape as an initial part condition for the welding process, and simulation of the welding process itself.

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.

The automotive industry is heading towards the path of autonomy with the development of autonomous vehicles. An autonomous vehicle consists of two main components. The first is the software which is responsible for the decision-making capabilities of the system. The second is the hardware which encompasses all aspects of the physical vehicle which are responsible for vehicle motion such as the engine, brakes and steering subsystems along with their corresponding controls. This component forms the basis of the autonomous vehicle platform. For SAE Level 4 autonomous vehicles, where an automated driving system is responsible for all the dynamics driving tasks including the fallback driving performance in case of system faults, redundant mechanical systems and controls are required as part of the autonomous vehicle platform since the driver is completely out of the loop with respect to driving.

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.

With the recent advancements in sensing and processing capabilities of consumer mobile devices (e.g., smartphone, tablet, etc.), they are becoming attractive choices for pervasive computing applications. Always-on monitoring of human movement patterns is one of those applications that has gained a lot of importance in the field of mobility and transportation research. Automatic detection of the current transportation mode (e.g., walking, biking, riding a shuttle, etc.) of a consumer using data from their smartphone sensors enables delivering of a number of customized services for multi-modal journey planning. Most accurate models for automatic mode detection are trained with supervised learning algorithms. In order to achieve high accuracy, the training datasets need to be sufficiently large, diverse, and correctly labeled.

A ductile failure criterion (DFC), which defines the stretching failure at localized necking (LN) and treats the critical damage as a function of strain path and initial sheet thickness, was proposed in a previous study. In this study, the DFC is revisited to extend the model to the low stress triaxiality domain and demonstrates on modeling forming limit curve (FLC) of TRIP 690. Then, the model is used to predict stretching failure in a finite element method (FEM) simulation on a TRIP 690 steel rectangular cup draw process at room temperature. Comparison shows that the results from this criterion match quite well with experimental observations.

Recommender systems guide a user to useful objects in a large space of possible options in a personalized way. In this paper, we study recommender systems for vehicles. Compared to previous research on recommender systems in other domains (e.g., movies or music), there are two major challenges associated with recommending vehicles. First, typical customers purchase fewer cars than movies or pieces of music. Thus, it is difficult to obtain rich information about a customer’s vehicle purchase history. Second, content information obtained about a customer (e.g., demographics, vehicle preferences, etc.) is also difficult to acquire during a relatively short stay in a dealership. To address these two challenges, we propose an interactive vehicle recommender system based a novel machine learning method that integrates decision trees and multi-armed bandits. Decision tree learning effectively selects important questions to ask the customer and encodes the customer's key preferences.

LS-DYNA3D has been widely used to perform computer simulation of sheet metal forming. In the material library of LS-DYNA3D there are a number of user defined material models. In order to take full advantage of the material subroutines, it is important for the users to be able to display user defined history variables in the post processing and to establish user-defined failure criterion. In this report, the development of a damage coupled plastic model is firstly described. The damage model is then programmed in a user defined material subroutine. This is followed by performing finite element simulation of sheet metal forming with the LS-DYNA3D that has incorporated the damage coupled plastic model. The way to display the user defined history variables and how to deal with the failure criterion during the postprocessing of ETA/DYNAFORM are described. History variable distributions at several time steps are displayed and discussed in this paper.