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Interference assessments of a stepped-radius power-train component moving within a deformed stepped bore often arise during engine and transmission development activities. For example, when loads are applied to an engine block, the block distorts. This distortion may cause a cam or crankshaft to bind or wear prematurely in its journals as the part rotates within them. Within an automatic transmission valve body, care must be taken to ensure valve body distortion under oil pressure, assembly, and thermal load does not cause spool valves to stick as they translate within the valve body. In both examples, the mechanical scenario to be assessed involves a uniform or stepped radius cylindrical part maintaining a designated clearance through a correspondingly shaped but distorted bore. These distortions can occur in cross-sections (“out-of-round”) or along the bore (in an “s” or “banana” shaped distortions).

Growing concerns about the environment, energy dependency, and unstable fuel prices have increased the market share of electric vehicles. This has led to an increased demand for energy efficient routing algorithms that are optimized for electric vehicles. Traditional routing algorithms are focused on finding the shortest distance or the least time route between two points. These approaches have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power and capacity limits, as well as vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present a simulated solution to the energy efficient routing for electric vehicles using Particle Swarm Optimization. Simulation results show improvements in the energy consumption of the electric vehicle when applied to a start-to-destination routing problem.

Cab mounts and suspension bushings are crucial for ride and handling characteristics and must be durable under highly variable loading. Such elastomeric bushings exhibit non-linear behavior, depending on excitation frequency, amplitude and the level of preload. To calculate realistic loads for durability analysis of cars and trucks multi-body simulation (MBS) software is used, but standard bushing models for MBS neglect the amplitude dependent characteristics of elastomers and therefore lead to a trade-off in simulation accuracy. On the other hand, some non-linear model approaches lack an easy to use parameter identification process or need too much input data from experiments. Others exhibit severe drawbacks in computing time, accuracy or even numerical stability under realistic transient or superimposed sinusoidal excitation.

This paper describes a comprehensive methodology for the simulation of vehicle body panel buckling in an electrophoretic coat (electro-coat or e-coat) and/or paint oven environment. The simulation couples computational heat transfer analysis and structural analysis. Heat transfer analysis is used to predict temperature distribution throughout a vehicle body in curing ovens. The vehicle body temperature profile from the heat transfer analysis is applied as an input for a structural analysis to predict buckling. This study is focused on the radiant section of the curing ovens. The radiant section of the oven has the largest temperature gradients within the body structure. This methodology couples a fully transient thermal analysis to simulate the structure through the electro-coat and paint curing environments with a structural, buckling analysis.

Automotive vehicle body electrophoretic (e-coat) and paint application has a high degree of complexity and expense in vehicle assembly. These steps involve coating and painting the vehicle body. Each step has multiple coatings and a curing process of the body in an oven. Two types of heating methods, radiation and convection, are used in the ovens to cure coatings and paints during the process. During heating stage in the oven, the vehicle body has large thermal stresses due to thermal expansion. These stresses may cause permanent deformation and weld/joint failure. Body panel deformation and joint failure can be predicted by using structural analysis with component surface temperature distribution. The prediction will avoid late and costly changes to the vehicle design. The temperature profiles on the vehicle components are the key boundary conditions used to perform structure analysis.

In today's light-weight vehicles, the strength of spot welds plays an important role in overall product integrity, reliability and customer satisfaction. Naturally, there is a need for a quick and reliable technique to inspect the quality of the welds. In the past, the primary quality control tests for detecting weld defects are the destructive chisel test and peel test [1]. The non-destructive evaluation (NDE) method currently used in industry is based on ultrasonic inspection [2, 3, 4]. The technique is not always successful in evaluating the nugget size, nor is it effective in detecting the so-called “cold” or “stick” welds. Therefore, it is necessary to develop a precise and reliable noncontact NDE method for spot welds. There have been numerous studies in predicting the weld nugget size by considering the spot-weld process [5, 6].

Corrosion tendency is one of the major inhibitors for increased use of magnesium alloys in automotive structural applications. Moreover, systematic or standardized methods for evaluation of both general and galvanic corrosion of magnesium alloys, either as individual components or eventually as entire subassemblies, remains elusive, and receives little attention from professional and standardization bodies. This work reports outcomes from an effort underway within the U.S. Automotive Materials Partnership - ‘USAMP’ (Chrysler, Ford and GM) directed toward enabling technologies and knowledge base for the design and fabrication of magnesium-intensive subassemblies intended for automotive “front end” applications. In particular, subassemblies consisting of three different grades of magnesium (die cast, sheet and extrusion) and receiving a typical corrosion protective coating were subjected to cyclic corrosion tests as employed by each OEM in the consortium.

An accurate representation of proving ground loading is essential for nonlinear Finite Element analysis and component fatigue test. In this paper, a rainflow counting based multiple blocks loading development procedure is described. The procedure includes: (1) Rainflow counting analysis to obtain the relationship between load range and cumulative repeats and the statistical relationship between load range and mean load; (2) Formation of preliminary multiple loading blocks with specified load range, mean load, and the approximate cycle repeats, and construction of the preliminary multiple loading blocks; (3) Calibration and finalization of the repeats for preliminary multiple loading blocks according to the equivalent damage rule, meaning that the damage value due to the block loads is equivalent to that from a PG loading.

Traditional warm forming of aluminum refers to sheet forming in the temperature range of 200°C to 350°C using heated, matched die sets similar to conventional stamping. While the benefits of this process can include design freedom, improved dimensional capability and potentially reduced cycle times, the process is complex and requires expensive, heated dies. The objective of this work was to develop a warm forming process that both retains the benefits of traditional warm forming while allowing for the use of lower-cost tooling. Enhanced formability characteristics of aluminum sheet have been observed when there is a prescribed temperature difference between the die and the sheet; often referred to as a non-isothermal condition. This work, which was supported by the USCAR-AMD initiative, demonstrated the benefits of the non-isothermal warm forming approach on a full-scale door inner panel. Finite element analysis was used to guide the design of the die face and blank shape.

During component development of multiple fastener bolted joints, it was observed that one or two fasteners had a higher potential to slip when compared to other fasteners in the same joint. This condition indicated that uneven distribution of the service loads was occurring in the bolted joints. The need for an optimization tool was identified that would take into account various objectives and constraints based on real world design conditions. The objective of this paper is to present a method developed to determine optimized multiple fastener locations within a bolted joint for achieving evenly distributed loads across the fasteners during multiple load events. The method integrates finite element analysis (FEA) with optimization software using multi-objective optimization algorithms. Multiple constraints were also considered for the optimization analysis. In use, each bolted joint is subjected to multiple service load conditions (load cases).

Most manufacturing and assembly processes like stamping, clamping, interference fits introduce a pre-stress condition in components or assemblies. Very often these stresses are high enough and alter the mean stress state resulting in significant effect on fatigue life performance and thus cannot be ignored. If the pre-stress is compressive, it will increase the allowable stress range and improve fatigue life performance; on the other hand if these stresses are tensile, they will decrease the allowable stress range resulting in a degradation of fatigue life. At times it becomes critical to effectively introduce the pre-stress condition in order to accurately represent the stress state in an FEA based durability simulation. Accounting for the pre-stress state in FEA based constant amplitude loading fatigue life simulation is relatively straight forward, but when it comes to random variable amplitude multi-channel loads simulation, the problem becomes more complicated.

Due to their high energy density and low self-discharge rates, lithium-ion batteries are becoming the favored solution for portable electronic devices and electric vehicles. Lithium-Ion batteries require special charging methods that must conform to the battery cells' power limits. Many different charging methods are currently used, some of these methods yield shorter charging times while others yield more charge capacity. This paper compares the constant-current constant-voltage charging method against the time pulsed charging method. Charge capacity, charge time, and cell temperature variations are contrasted. The results allow designers to choose between these two methods and select their parameters to meet the charging needs of various applications.

Contacts or interactions commonly exist between adjacent components in automotive structures, and most of the time they dominate stress status of the components. However, when the routine pseudo stress approach is employed in fatigue life estimations, simulating contacts present special challenges. This may result in coarse stress status and corresponding coarser fatigue life estimations at the contact locations. In this paper, concept, development and procedures of two techniques to consider contacts in fatigue life estimations of automotive structures are described in detail. One is still pseudo stress approach based, but employs additional 1-D connection elements to simulate contacts. The other is nonlinear stress approach based, but equivalent constantly repeating cyclic critical load cases are introduced and utilized. The contacts are simulated by interface setup provided in the software.

The performance of door assembly is very significant for the vehicle design and door sag/set is one of the important attribute for design of door assembly. This paper provides an overview of conventional approach for door sag/set study based on door-hinge-BIW assembly (system level approach) and its limitation over new approach based on subassembly (subsystem level approach). The door sag/set simulation at system level is the most common approach adopted across auto industry. This approach evaluates only structural adequacy of door assembly system for sag load. To find key contributor for door sagging is always been time consuming task with conventional approach thus there is a delay in providing design enablers to meet the design target. New approach of door sag/set at “subsystem level” evaluates the structural stiffness contribution of individual subsystem. It support for setting up the target at subsystem level, which integrate and regulate the system level performance.

With the increased market share of electric vehicles, the demand for energy-efficient routing algorithms specifically optimized for electric vehicles has increased. Traditional routing algorithms are focused on optimizing the shortest distance or the shortest time in finding a path from point A to point B. These traditional methods have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power limits, battery capacity limits, and vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present an ant colony based, energy-efficient routing algorithm that is optimized and designed for electric vehicles. Simulation results show improvements in the energy consumption of electric vehicles when applied to a start-to-destination routing problem.

Chrysler, Ford, General Motors, the U.S. Environmental Protection Agency (EPA) and the California Air Resources Board (CARB) have collaborated over the past two years to develop an efficiency test for mobile air conditioner (MAC) systems. Because the effect of efficiency differences between different MAC systems and different technologies is relatively small compared to overall vehicle fuel consumption, quantifying these differences has been challenging. The objective of this program was to develop a single dynamic test procedure that is capable of discerning small efficiency differences, and is generally representative of mobile air conditioner usage in the United States. The test was designed to be conducted in existing test facilities, using existing equipment, and within a sufficiently short time to fit standard test facility scheduling. Representative ambient climate conditions for the U.S. were chosen, as well as other test parameters, and a solar load was included.

This paper reports a study undertaken by the Crash Safety Working Group (CSWG) of the United States Council for Automotive Research (USCAR) to determine generic acceleration pulses for testing and evaluating advanced batteries subjected to inertial loading for application in electric passenger vehicles. These pulses were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used in this study. Crash test data, in terms of acceleration time histories, were collected from various crash modes conducted by the National Highway Traffic Safety Administration (NHTSA) during their New Car Assessment Program (NCAP) and Federal Motor Vehicle Safety Standards (FMVSS) evaluations, and the Insurance Institute for Highway Safety (IIHS).

This paper is the fourth in the series of documents designed to identify the progress on the SAE Plug-in Electric Vehicle (PEV) communication task force. - The initial paper (2010-01-0837) introduced utility communications (J2836/1™ & J2847/1) and how the SAE task force interfaced with other organizations. - The second paper (2011-01-0866) focused on the next steps of the utility requirements and added DC charging (J2836/2™ & J2847/2) along with initial effort for Reverse Power Flow (J2836/3™ & J2847/3). - The third paper (2012-01-1036) summarized the task force documents and interaction. It also included the continued testing of PowerLine Carrier (PLC) products for Utility and DC charging messages using Electric Power Research Institutes (EPRI) test plan and schedule that were used at EPRI and Argonne National Labs (ANL).

Regression models are used to understand the relative fatality risk for drivers in front-front and front-left crashes. The field accident data used for the regressions were extracted by NHTSA from the FARS database for model years 2000-2007 vehicles in calendar years 2002-2008. Multiple logistic regressions are structured and carried out to model a log-linear relationship between risk ratio and the independent vehicle and driver parameters. For front-front crashes, the regression identifies mass ratio, belt use, and driver age as statistically significant parameters (p-values less than 1%) associated with the risk ratio. The vehicle type and presence of the ESC are found to be related with less statistical significance (p-values between 1% and 5%). For front-left crashes the driver risk ratio is also found to have a log-log linear relationship with vehicle mass ratio.

This paper reports a 2010 study undertaken to determine generic acceleration pulses for testing and evaluating advanced batteries for application in electric passenger vehicles. These were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used. The crash test data were gathered from the following test modes and sources: 1 Frontal rigid flat barrier test at 35 mph (NHTSA NCAP) 2 Frontal 40% offset deformable barrier test at 40 mph (IIHS) 3 Side moving deformable barrier test at 38 mph (NHTSA side NCAP) 4 Side oblique pole test at 20 mph (US FMVSS 214/NHTSA side NCAP) 5 Rear 70% offset moving deformable barrier impact at 50 mph (US FMVSS 301). The accelerometers used were from locations in the vehicle where deformation is minor or non-existent, so that the acceleration represents the “rigid-body” motion of the vehicle.