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Even though the 3-way catalyst chemistry has been studied extensively in the literature, some performance aspects of practical relevance have not been fully explained. It is believed that the Oxygen Storage Capacity function of 3-way catalytic components dominates the behavior during stoichiometry transitions from lean to rich mode and vice versa whereas a number of mathematical models have been proposed to describe the dynamics of pollutant conversion. Previous studies have suggested a strong impact of Sulfur on the pollutant conversion after a lean to rich transition, which has not been adequately explained and modelled. Lean to rich transitions are highly relevant to catalyst ‘purging’ needed after exposure to high O2 levels (e.g. after fuel cut-offs). This work presents engine test measurements with an engine-aged catalyst that highlight the negative impact of Sulfur on pollutant conversion after a lean to rich transition.

The driveshafts can be an important contributor to vehicle interior noise including low-frequency (booming) noise where the vibrations, originating in the powerplant, travel to the vehicle body through the driveshafts. A suitable Key Performance Indicator (KPI) for the driveshaft performance is the transmissibility, which is an output/input acceleration ratio and can be used to describe the amount of vibration transferred from the inboard to the outboard joint of the driveshaft. This paper introduces a simple physical model of the driveshaft transmissibility able to support the development and evaluation of the driveshaft and to estimate the effectiveness of countermeasures such as a dynamic damper. The model is validated through comparison with on-vehicle measurements. The proposed approach offers ease of use, low computational cost and clear relation of the measured transmissibility with the system’s physical properties.

The use of predictive models in the study of Internal Combustion Engines (ICE) allows reducing developing cost and times. However, those models are challenging due to the complex and multi-phase phenomena occurring in the combustion chamber, but also because of the different spatial and temporal scales in different components of the injection systems. This work presents a methodology to accurately simulate the spray by Discrete Droplet Models (DDM) without experimentally measuring the injector mass flow rate and/or momentum flux. Transient nozzle flow simulations are used instead to define the injection conditions of the spray model. The methodology is applied to a multi-hole Gasoline Direct injection (GDi) injector. Firstly, the DDM constant values are calibrated comparing simulation results to Diffused Back-light Illumination (DBI) experimental technique results. Secondly, transient nozzle flow simulations are carried out.

In a previous study (Song et al. 2017), an adjustable generic simplified vehicle buck was developed; eleven PMHS were impacted by the buck representing a SUV, a van and a sedan successively; and biofidelity corridors were established. The objectives of the current study were 1) to develop the computational model of the buck, and 2) to simulate these PMHS tests with the buck model and to assess the biofidelity of the GHBMC 50th percentile male pedestrian simplified model (GHBMC M50-PS). First, coupon tensile tests and static and dynamic compression tests were performed on the steel tubes representing the bonnet leading edge (BLE), the bumper and the spoiler used in the above PMHS tests. Based on these tests, the computational models of the above components were then developed and validated. Next, the buck model was built with the component models, and used to simulate the PMHS tests with the GHBMC M50-PS model.

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.

Finite Element Human Body Models (HBM) have become powerful tools to study the response to impact. However, they are typically only developed for a limited number of sizes and ages. Various approaches driven by control points have been reported in the literature for the non-linear scaling of these HBM into models with different geometrical characteristics. The purpose of this study is to compare the performances of commonly used control points based interpolation methods in different usage scenarios. Performance metrics include the respect of target, the mesh quality and the runability. For this study, the Kriging and Moving Least square interpolation approaches were compared in three test cases. The first two cases correspond to changes of anthropometric dimensions of (1) a child model (from 6 to 1.5 years old) and (2) the GHBMC M50 model (Global Human Body Models Consortium, from 50th to 5th percentile female).

Several statistical methods are currently used to build injury risk curves in the biomechanical field. These methods include the certainty method (Mertz et al. 1996), Mertz/Weber method (Mertz and Weber 1982), logistic regression (Kuppa et al. 2003, Hosmer and Lemeshow 2000), survival analysis with Weibull distribution (Kent et al. 2004, Hosmer and Lemeshow 2000), and the consistent threshold estimate (CTE) (Nusholtz et al. 1999, Di Domenico and Nusholtz 2005). There is currently no consensus on the most accurate method to be used and no guidelines to help the user to choose the more appropriate one. Injury risk curves built for the WorldSID 50th side impact dummy with these different methods could vary significantly, depending on the sample considered (Petitjean et al. 2009). As a consequence, further investigations were needed to determine the fields of application of the different methods and to recommend the best statistical method depending on the biomechanical sample considered.

To meet future stringent emission regulations such as Euro6, the design and control of diesel exhaust after-treatment systems will become more complex in order to ensure their optimum operation over time. Moreover, because of the strong pressure for CO₂ emissions reduction, the average exhaust temperature is expected to decrease, posing significant challenges on exhaust after-treatment. Diesel Oxidation Catalysts (DOCs) are already widely used to reduce CO and hydrocarbons (HC) from diesel engine emissions. In addition, DOC is also used to control the NO₂/NOx ratio and to generate the exothermic reactions necessary for the thermal regeneration of Diesel Particulate Filter (DPF) and NOx Storage and Reduction catalysts (NSR). The expected temperature decrease of diesel exhaust will adversely affect the CO and unburned hydrocarbons (UHC) conversion efficiency of the catalysts. Therefore, the development cost for the design and control of new DOCs is increasing.

This study aims to investigate the relationship between the number of rib fractures and the thoracic deflection in side impact, and in particular its variability with respect to various loading configurations. The relevance of thoracic deflection as an injury criterion depends on the existence or not of this variability. Few studies were dedicated to this issue in the literature. First, a validation database was established, which covers different impact directions (frontal, lateral and oblique), different loading types (impactor, belt and airbag), and different injury levels (from the absence of, to presence of numerous ribs fractured). The HUMOS human body model was then modified and validated versus the database. Besides the typical validation in terms of global response, particular attention was paid to validate the model with respect to the ribcage strain profile, the occurrence of rib fractures and their locations.

Thoracic injury criteria and injury risk curves in side impact are based on impactor or sled tests, with rigid or padded surfaces while airbags are very common on current cars. Besides, the loading is generally pure lateral while real crashes or regulations can generate oblique loadings. Oblique tests were found in the literature, but no conclusion was drawn with regard to the effect of the direction on the injury outcome. In order to address these two limitations, a series of 17 side airbag tests were performed on Post Mortem Human Subjects (PMHS) at different severities and angles. The subjects were instrumented with accelerometers on the spine and strain gauges on the ribs. They were loaded by an unfolded airbag at different distances in pure lateral or 30 degrees forward. The airbag forces ranged from 1680 N to 6300 N, the injuries being up to 9 separated fractured ribs. This paper provides the test results in terms of physical parameters and injury outcome of the 17 subjects.

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.

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.

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.

Springback is a major concern in stamping of advanced high strength steels (AHSS). The existing computer simulation technology has difficulty predicting this phenomenon accurately even though it is well developed for formability simulations. Great efforts made in recent years to improve springback predictions have achieved noticeable progress in the computational capability and accuracy. In this work, springback simulation studies are conducted using FEA software LS-DYNA®. Various parametric sensitivity studies are carried out and key variables affecting the springback prediction accuracy are identified. Recently developed simulation technologies in LS-DYNA® are implemented including dynamic effect minimization, smooth tool contact and newly developed nonlinear isotropic/kinematic hardening material models. Case studies on lab-scale and full-scale industrial parts are provided and the predicted springback results are compared to the experimental data.