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Injury Risk Curves are developed from cadaver data for sternal deflections produced by anterior, distributed chest loads for a 25, 45, 55, 65 and 75 year-old Small Female, Mid-Size Male and Large Male based on the variations of bone strengths with age. These curves show that the risk of AIS ≥ 3 thoracic injury increases with the age of the person. This observation is consistent with NASS data of frontal accidents which shows that older unbelted drivers have a higher risk of AIS ≥ 3 chest injury than younger drivers.

For higher mileage vehicles, noise from contaminant ingress is one of the largest durability issues for wheel bearings. The mileage that wheel bearing sealing issues increase can vary due to multiple factors, such as the level of corrosion for the vehicle and the mating components around the wheel bearing. In general, sealing issues increase after 20,000 to 30,000 km. Protecting the seals from splash is a key step in extending bearing life. Benchmarking has shown a variety of different brake corner designs to protect the bearing from splash. This report examines the effect of factors from different designs, such as the radial gap between constant velocity joint (CVJ) slinger and the knuckle, knuckle labyrinth height and varying slinger designs to minimize the amount of splash to the bearing inboard seal. This report reviews some of the bearing seal failure modes caused by splash.

The human thermal comfort, which has been a subject of extensive research, is a principal objective of the automotive climate control system. Applying the results of research studies to the practical problems require quantitative information of the thermal environment in the passenger compartment of a vehicle. The exposure to solar radiation is known to alter the thermal environment in the passenger compartment. A photovoltaic-cell based sensor is commonly used in the automotive climate control system to measure the solar radiation exposure of the passenger compartment of a vehicle. The erroneous information from a sensor however can cause thermal discomfort to the occupants. The erroneous measurement can be due to physical or environmental parameters. Shading of a solar sensor due to the opaque vehicle body elements is one such environmental parameter that is known to give incorrect measurement.

The vehicle air-conditioning system has significant impact on fuel economy and range of electric vehicles. Improving the fuel economy of vehicles therefore demand for energy efficient climate control systems. Also the emissions regulations motivate the reduced use of fuel for vehicle's cabin climate control. Solar heat gain of the passenger compartment by greenhouse effect is generally treated as the peak thermal load of the climate control system. Although the use of advanced glazing is considered first to reduce solar heat gain other means such as ventilation of parked car and recirculation of cabin air also have impetus for reducing the climate control loads.

In addition to the thermal comfort of the vehicle occupants, their safety by ensuring adequate visibility is an objective of the automotive climate control system. An integrated dew point and glass temperature sensor is widely used among several other technologies to detect risk of fog formation on the cabin side (or inner) surface of the windshield. The erroneous information from a sensor such as the measurement lag can cause imperfect visibility due to the delayed response of the climate control system. Also the high value, low cost vehicles may not have this sensor due to its high cost. A differential equation based model of the cabin air humidity is proposed to calculate in real-time specific humidity of the passenger compartment air. The specific humidity is used along with the windshield surface temperature to determine relative humidity of air and therefore, the risk of fog formation on the interior surface of a windshield.

An indirect method to determine friction coefficient under punch stretching conditions has been developed. The methodology involves correlation of experimental draw-in measurements to FEA predictions for a range of assumed friction coefficients. Initial evaluation with a ferritic stainless steel (SS 439) shows that the proposed indirect method to determine the effective friction coefficient during punch stretching is feasible. Friction coefficient (μ) estimate based on the indirect method was 0.15 for the sample with residual mill oil (dry), 0.12 with excess mill oil (wet), and 0.03 with polyethylene sheets between the sample blank and tooling. The importance of prescribing accurate material hardening behavior beyond uniform elongation to obtain good correlation between simulation and experimental punch loads and to better tune the model is highlighted in the paper.

Over the past several years a task group within the SAE Automotive Corrosion and Protection (ACAP) Committee has conducted extensive on-vehicle field testing and numerous accelerated lab tests with the goal of establishing a standard accelerated test method for cosmetic corrosion evaluations of finished aluminum auto body panels. This project has been a cooperative effort with OEM, supplier, and consultant participation and was also supported in part by DOE through USAMP (AMD 309). The focus of this project has been the identification of a standardized accelerated cosmetic corrosion test that exhibits the same appearance, severity, and type of corrosion products that are exhibited on identical painted aluminum panels exposed to service relevant environments. Multi-year service relevant exposures were conducted by mounting panels on-vehicles in multiple locations in the US and Canada.

Automotive engines are regularly utilized in the material handling market where LPG is often the primary fuel used. When compared to gasoline, the use of gaseous fuels (LPG and CNG) as well as alcohol based fuels, often result in significant increases in valve seat insert (VSI) and valve face wear. This phenomenon is widely recognized and the engine manufacturer is tasked to identify and incorporate appropriate valvetrain material and design features that can meet the ever increasing life expectations of the end-user. Alternate materials are often developed based on laboratory testing – testing that may not represent real world usage. The ultimate goal of the product engineer is to utilize accelerated lab test procedures that can be correlated to field life and field failure mechanisms, and then select appropriate materials/design features that meet the targeted life requirements.

The auto industry has had decades of experience with designing safe vehicles. The introduction of highly integrated features brings new challenges that require innovative adaptations of existing safety methodologies and perhaps even some completely new concepts. In this paper, we describe some of the new challenges that will be faced by all OEMs and suppliers. We also describe a set of generic top-level potential hazards that can be used as a starting point for the Preliminary Hazard Analysis (PHA) of a vehicle software-intensive motion control system. Based on our experience with the safety analysis of a system of this kind, we describe some general categories of hazard causes that are considered for software-intensive systems and can be used systematically in developing the PHA.

This study involves an application of Principal Component Analysis (PCA) conducted in support of a Design for Six Sigma (DFSS) project. Primary focus of the project is to optimize seat parameters that influence Low Speed Rear Impact (LSRI) whiplash performance. During the DFSS study, the project team identified a need to rank order critical design factors statistically and establish their contribution to LSRI performance. It is also required to develop a transfer function for the LSRI rating in terms of test response parameters that can be used for optimization. This statistical approach resulted in a reliable transfer function that can applied across all seat designs and enabled us to separate vital few parameters from several many.

In today’s highly competitive automotive environment people are always looking to develop processes that are fast, efficient, and effective. Moving testing from expensive prototype vehicles into the laboratory is an approach being implemented for many different vehicle subsystems. Specifically a process has recently been developed at General Motors that predicts exhaust back pressure performance for a running vehicle using laboratory testing and spreadsheet calculations. This paper describes the laboratory facility and procedure, the theory behind the calculations, and the correlation between vehicle test and laboratory based results. It also comments on the benefits of the process with respect to reduction in design iterations, quicker availability of results, and money savings.

By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

We start our study with a survey of existing variable valve actuation (VVA) devices. We then describe our work, taken place over a time period from 2001 to 2007, on several VVA concepts. All of our projects described include pre-design modeling and simulation. Also, for each one of the proposed designs, a bench-top motorized test fixture was built and ran for proof of concept. Our projects represent a mixture of exploratory research and production-related development work. They can be classified in four broad categories: discrete-step systems; mechanical continuously-variable systems; active stationary-hydraulic lash adjusters; cam-driven hydraulic-lost-motion mechanism. These devices differ in their complexity and versatility but offer a spectrum of design solutions applicable to a range of products. Specific attributes of these different approaches are analyzed and discussed, and some test results are presented.

The Advanced Engineering (AE) group within General Motors Powertrain (GMPT) develops next generation engines and transmissions for automotive and marine products. As a research organization, AE needs to prototype design ideas quickly and inexpensively. To this end, AE has embraced model-based development techniques and is currently investigating the benefits of software in-the-loop (SIL) testing. The underlying obstacle faced in developing a practical SIL system lays in the ability to integrate a plant model with sufficient fidelity together with target application software. ChiasTek worked with AE utilizing their CosiMate tool chain to eliminate these barriers and delivered a flexible SIL system simulation solution.

This paper demonstrates the benefit of using simulation and robust optimization for the problem of balancing vehicle noise, vibration, and ride performance over road impacts. The psychophysics associated with perception of vehicle performance on an impact is complex because the occupants encounter both tactile and audible stimuli. Tactile impact vibration has multiple dimensions, such as impact hardness and memory shake. Audible impact sound also affects occupant perception of the vehicle quality. This paper uses multiple approaches to produce the similar, robust, optimized tuning strategies for impact performance. A Design for Six Sigma (DFSS) project was established to help identify a balanced, optimized solution. The CAE simulations were combined with software tools such as iSIGHT and internally developed Kriging software to identify response surfaces and find optimal tuning.

In this article, the authors illustrate the benefits of axiomatic design (AD) for robust optimization and how to integrate axiomatic design into a total robust design process. Similar to traditional robust design, the purpose of axiomatic design is to improve the probability of a design in meeting its functional targets at early concept generation stage. However, axiomatic design is not a standalone method or tool and it needs to be integrated with other tools to be effective in a total robust development process. A total robust development process includes: system design, parameter design, tolerance design, and tolerance specifications [1]. The authors developed a step-by-step procedure for axiomatic design practices in industrial applications for consistent and efficient deliverables. The authors also integrated axiomatic design with the CAD/CAE/statistical/visualization tools and methods to enhance the efficiency of a total robust development process.

Exhaust gas recirculation (EGR) is one of the key approaches applied to reduce emissions for an internal combustion engine. Recirculating a desired amount of EGR requires accurately estimating EGR mass flow. This can be calculated either from the gas flow equation of an orifice, or from the difference between charge air mass flow and fresh air mass flow. Both calculations need engine exhaust pressure as an input variable. This paper presents a method to estimate exhaust pressure for a variable geometry turbo charged diesel engine. The method is accurate and simple to fit production ECU application, therefore, saves cost of using a physical sensor.

A DFSS study identified a new mechanism for clamp load loss in aluminum threads due to thermal cycling. In bolted joints tightened to yield, the difference in thermal expansion between the aluminum and steel threads can result in a loss of clamp load with each thermal cycle. This clamp load loss is significantly greater than the loss that can be explained by creep alone. A math model was created and used to conduct a robust analysis. This analysis led to an understanding of the design factors necessary to reduce the cyclic clamp load loss in the aluminum threads. This understanding was then used to create optimized design solutions that satisfy constraints common to powertrain applications. Estimations of clamp load loss due to thermal cycling from the math model will be presented. The estimates of the model will be compared to observed physical test data. A robust analysis, including S/N and mean effect summary will be presented.

A common occurrence in computer aided design is the need to make changes to an existing CAD model to compensate for shape changes which occur during a manufacturing process. For instance, finite element analysis of die forming or die tryout results may indicate that a stamped panel springs back after the press line operation so that the final shape is different from nominal shape. Springback may be corrected by redesigning the die face so that the stamped panel springs back to the nominal shape. When done manually, this redesign process is often time consuming and expensive. This article presents a computer program, FESHAPE, that reshapes the CAD or finite element mesh models automatically. The method is based on the technique of volume morphing pioneered by Sederberg and Parry [Sederberg 1986] and refined in [Sarraga 2004]. Volume morphing reshapes regions of surfaces or meshes by reshaping volumes containing those regions.