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THE PURPOSE of this experiment was to determine the role of residual stresses in fatigue strength independent of other factors usually involved when residual stresses are introduced. It consisted of an investigation of the influence of residual stresses introduced by shotpeening on the fatigue strength of steel (Rockwell C hardness 48) in unidirectional bending. Residual stresses were varied by peening under various conditions of applied strain. This process introduced substantially the same amount and kind of surface cold working with residual stresses varying over a wide range of values. It was found that shotpeening of steel of this hardness is beneficial primarily because of the nature of the macro-residual-stresses introduced by the process. There is no gain attributable to “strain-hardening” for this material. An effort was made to explain the results on the basis of three failure criteria: distortion energy, maximum shear stress, and maximum stress.*

The strain-life approach is now commonly used for fatigue life analysis and predictions in the ground vehicle industry. This approach requires the use of material properties obtained from strain-controlled uniaxial fatigue tests. These properties include fatigue strength coefficient (σf′), fatigue strength exponent (b), fatigue ductility coefficient (εf′), fatigue ductility exponent (c), cyclic strength coefficient (K′), and cyclic strain hardening exponent (n′). To obtain the aforementioned properties for the material, raw data from stable cyclic stress-strain loops are fitted in log-log scale. These data include total, elastic and plastic strain amplitudes, stress amplitude, and fatigue life. Values of the low cycle fatigue properties (σf′, b, εf′, c) determined from the raw data depend on the method of measurement and fitting. This paper examines the merits and influence of using different measurement and fitting methods on the obtained properties.

A driving simulator development project at the Systems Engineering and Technical Process Center (SE/TP) is exploring the role of driving simulation in the vehicle design process. The simulator provides two vehicle mockup testing arenas that support a wide field of view, computer-generated image of the road scene which dynamically responds to driver commands as a function of programmable vehicle model parameters. Two unique aspects of the simulator are the fast 65 ms response time and low incidence rate of simulator induced syndrome (about 5%). Preliminary model validation results and data comparing driver performance in a vehicle vs. the simulator indicate accurate handling response dynamics within the on-center handling region (<0.3g lateral acceleration). Applications have included supporting the development of new steering system concepts, as well as evaluating the usability of vehicle controls and displays.

In order to engineer Squeak & Rattle (S&R) free vehicles it is essential to develop an objective measurement method to compare and correlate with customer satisfaction and subjective S&R assessments. Three methods for exciting S&Rs -type surfaces. Excitation methods evaluated were road tests over S&R surfaces, road simulators, and direct body excitation (DBE). The principle of DBE involves using electromagnetic shakers to induce controlled, road-measured vibration into the body, bypassing the tire patch and suspension. DBE is a promising technology for making objective measurements because it is extremely quiet (test equipment noise does not mask S&Rs), while meeting other project goals. While DBE is limited in exposing S&Rs caused by body twist and suspension noises, advantages include higher frequency energy owing to electro-dynamic shakers, continuous random excitation, lower capital cost, mobility, and safety.

The work presented here builds on the practical and effective spot weld fatigue life prediction method, the structural stress method (SSM), that was developed at Stanford University. Constant amplitude loading tests for various spot weld joint configurations have been conducted and the SSM has been shown to accurately predict fatigue life. In this paper refinements to the structural stress approach are first presented, including a variable amplitude fatigue life prediction method based on the SSM and Palmgren-Miner's rule. A test matrix was designed to study the fatigue behavior of spot welds under tensile shear loading conditions. Constant amplitude tests under different R-ratios were performed first to obtain the necessary material properties. Variable amplitude tests were then performed for specimens containing single and multiple welds.

This paper describes a numerical simulation technique applicable to the FMVSS 214 side impact test through the use of the finite element method (FEM) technology. The paper outlines the development of the side impact dummy (SID), moving deformable barrier (MDB) and the test vehicle FEM models, as well as the development of new advanced constitutive models of materials and algorithms in LS-DYNA3D which are related to the topic. Presented in the paper are some initial simulation problems which were encountered and solved, as well as the correlation of the simulation data to the physical test.

Robust optimization usually requires numerous functional evaluations, which is not feasible when the functional evaluation is time-consuming. Examples in automobile industry include crash worthiness/safety and fatigue life simulations. In practice, a response surface model (RSM) is often used as a surrogate to the CAE model, so that robust optimization can be carried out. However, if the error in the RSM is significant, the solution based on the RSM can be invalid. This paper proposes a method of finding multiple candidate solutions, all of which have similar predicted performances. This approach is effective in finding the close-to-optimum solutions when the model has error, and providing design alternatives. Examples are provided to illustrate the method.

Magnesium alloys are the lightest structural metal and recently attention has been focused on using them for structural automotive components. Fatigue and durability studies are essential in the design of these load-bearing components. In 2006, a large multinational research effort, Magnesium Front End Research & Development (MFERD), was launched involving researchers from Canada, China and the US. The MFERD project is intended to investigate the applicability of Mg alloys as lightweight materials for automotive body structures. The participating institutions in fatigue and durability studies were the University of Waterloo and Ryerson University from Canada, Institute of Metal Research (IMR) from China, and Mississippi State University, Westmorland, General Motors Corporation, Ford Motor Company and Chrysler Group LLC from the United States.

The complexity of designing and implementing a vehicle electrical control system for ultra fuel-efficient hybrid vehicles is significantly greater than that of a conventional vehicle. To quickly demonstrate and iterate capabilities of these vehicles, an efficient and rapid means for developing requirements, mapping these into an electrical control and communications architecture, and developing prototype systems is needed. The General Motors Precept concept vehicle is an example of an energy- efficient vehicular control system developed using a "requirements to software'' development process and electronic controller infrastructure that demonstrates these attributes. The Precept is General Motors Corporation's technology demonstration concept vehicle developed to address General Motors Corporation's commitment to the Partnership for a New Generation (PNGV) program.

From November 1970 through August 1971 an extensive program of static and dynamic air cushion inflation tests utilizing human volunteers was conducted at Holloman Air Force Base, New Mexico, sponsored by the Department of Transportation. Forty-one full cushion deployment static firings were made, with air cushion hardware and seating buck environment designed by General Motors. The static series was followed by 35 dynamic sled firings of human volunteers, beginning at 8.6 g (15.1 mph) and culminating at 21.7 g (31.5 mph). A major objective of both the static and dynamic test series was to identify changes in air-cushion design found necessary to improve its protective capability for human beings. Because of the severity of cushion deployment, one modification was made following the initial static tests: The orifice diameter size of the bag inlet was reduced from 1.0 to 0.6 in to diminish the rapidity of bag inflation. This modification proved effective in the dynamic series.

A search for methods of switching a proposed three beam headlight system led to the evaluation of 41 possible schemes. Human factors criteria reduced the original 41 to three systems which were tested in a laboratory with a broad range of subjects. Recordings of practice trials, learning trials, and the responses to visual cues projected on a screen were analyzed. The same test procedure was also used to compare three alternative ways of switching conventional two beam headlight systems. Summary data is presented for the six systems tested grouped by test subject age, sex, and driving experience. The most pronounced difference observed was in the subjective preference rating among two beam switching systems. All systems tested resulted in remarkably few learning and practice trials. Small differences were recorded among systems in operational response time.

The transportation sector in the United States is a major contributor to global energy consumption and carbon dioxide emission. To assess the future potentials of different technologies in addressing these two issues, we used a family of simulation programs to predict fuel consumption for passenger cars in 2020. The selected technology combinations that have good market potential and could be in mass production include: advanced gasoline and diesel internal combustion engine vehicles with automatically-shifting clutched transmissions, gasoline, diesel, and compressed natural gas hybrid electric vehicles with continuously variable transmissions, direct hydrogen, gasoline and methanol reformer fuel cell hybrid electric vehicles with direct ratio drive, and battery electric vehicle with direct ratio drive.

Casting, machining and structural simulations were completed on a V8 engine block made in Compacted Graphite Iron (CGI) for use in a racing application. The casting and machining simulations generated maps of predicted tensile strength and residual stress in the block. These strength and stress maps were exported to a finite element structural model of the machined part. Assembly and operating loads were applied, and stresses due to these loads were determined. High cycle fatigue analysis was completed, and three sets of safety factors were calculated using the following conditions: uniform properties and no residual stress, predicted properties and no residual stress, and predicted properties plus residual stress.

Hybrid powertrains with multiple sources of power have generated new control challenges in the automotive industry. Purdue University's participation in EcoCAR 2, an Advanced Vehicle Technology Competition managed by the Argonne National Laboratories and sponsored by GM and DOE, has provided an exciting opportunity to create a comprehensive test-bench for the development and validation of advanced hybrid powertrain control strategies. As one of 15 competing university teams, the Purdue EcoMakers are re-engineering a donated 2013 Chevrolet Malibu into a plug-in parallel- through-the-road hybrid-electric vehicle, to reduce its environmental impact without compromising performance, safety or consumer acceptability. This paper describes the Purdue team's control development process for the EcoCAR 2 competition.

To manage the function of a vehicle's engine, transmission, and related subsystems, almost all modern vehicles make use of one or more electronic controllers running embedded software, henceforth referred to as a Powertrain Controller System or PCS. Fully validating this PCS is a necessary step of vehicle development, and the validation process requires extensive amounts of testing. Within the automotive industry, more and more of this validation testing is being performed using Hardware-in-the-Loop (HIL) simulators to automate the extensive test sequences. A HIL simulation typically mates the physical PCS to a closed-loop real time computer simulation of a powertrain. Interfacing the physical PCS hardware to a powertrain simulation requires the HIL simulator to have extensive signal input/output (I/O) electronics and simulated actuator electrical loading.

Casting technology developmentshave led to a manufacturing process that allows the casting of thin wall (2-3mm) heat resistant ferritic stainless steel exhaust manifolds which can replace stamped and tubular weldments as well as iron castings where temperature requirements are increased. This casting process combines the thin wall and clean metal benefits of the counter gravity, vacuum-assist casting process using thin, light-weight bonded sand molds supported by vacuum-ridgidized sand. This combination is called the LSVAC (Loose Sand Vacuum Assisted Casting) process, a patented process. This process will significantly contribute to the growth of near-net shape steellstainless steel castings for automotive and allied industries. For exhaust manifolds, a modified grade of ferritic stainless steel with good oxidation resistance to 950°C in high dew point synthetic exhaust gas atmospheres was developed.

This paper assesses the potential improvement of automotive powertrain technologies 25 years into the future. The powertrain types assessed include naturally-aspirated gasoline engines, turbocharged gasoline engines, diesel engines, gasoline-electric hybrids, and various advanced transmissions. Advancements in aerodynamics, vehicle weight reduction and tire rolling friction are also taken into account. The objective of the comparison is the potential of anticipated improvements in these powertrain technologies for reducing petroleum consumption and greenhouse gas emissions at the same level of performance as current vehicles in the U.S.A. The fuel consumption and performance of future vehicles was estimated using a combination of scaling laws and detailed vehicle simulations. The results indicate that there is significant potential for reduction of fuel consumption for all the powertrains examined.

As component and systems sophistication in both cars and trucks increase, improved diagnostic capabilities are required to assure proper and expedient serviceability. Replacement of electrical modules, starter motors, carburetors, fuel injectors and even whole engines or transmissions is encouraged by high labor costs and continued vehicle mobility mandates. The remanufacturing business has grown and components previously discarded now provide valuable core elements to feed the industry. To achieve efficient utilization of capital, equipment and labor, remanufacturers must estimate when this supply of core elements will be available and plan their production schedules accordingly. In order to properly service private individuals and commercial fleets, minimize vehicle downtime and reduce life cycle costs, adaptation of available analytical tools must be made.

Rare earths are a group of elements whose availability has been of concern due to monopolistic supply conditions and environmentally unsustainable mining practices. To evaluate the risks of rare earths availability to automakers, a first step is to determine raw material content and value in vehicles. This task is challenging because rare earth elements are used in small quantities, in a large number of components, and by suppliers far upstream in the supply chain. For this work, data on rare earth content reported by vehicle parts suppliers was assessed to estimate the rare earth usage of a typical conventional gasoline engine midsize sedan and a full hybrid sedan. Parts were selected from a large set of reported parts to build a hypothetical typical mid-size sedan. Estimates of rare earth content for vehicles with alternative powertrain and battery technologies were made based on the available parts' data.

Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.