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The need for improved axle NVH integration has increased significantly in recent years with industry trends toward full-time and automatic four wheel drive (4wd) systems. Along with seamless 4wd operation, quiet performance has become a universal expectation. Axle gear-mesh noise can be transmitted to the vehicle passenger compartment through airborne paths (not discussed in this paper) and structure-borne paths (the focus of this paper.) A variety of mounting configurations are used in an attempt to provide improved axle isolation and reduce structure-borne transmission of gear-mesh noise. The configuration discussed in this paper is a 4-point vertical mount design for an Independent Front Drive Axle (IFDA). A significant benefit of this configuration is improved isolation in the range of drive torques where axle-related NVH issues typically exist.

The objective of this paper is to propose a new model in the identification of a contributing factor to the generation of Radio Frequency Interference (RFI) due to the operation of a spark-ignited engine. This model incorporates parameters in the electrical operation of the ignition system components and their interaction with the engine mechanical structure, which is also used as a circuit component (the ignition system “ground”). T he model was developed as a result of analysis of numerous studies that have been conducted over the years in an attempt to identify why RFI characteristics can differ when using identical components on different engines, or locating the components in different locations on identical engines. This situation is a problem due to the resulting uncertainty with respect to the determination of what is the optimum vehicle ignition system configuration to meet all electrical and RFI or electromagnetic compatibility (EMC) requirements.

This paper attempts to integrate a derivative-free probability analysis method to Reliability-Based Robust Design Optimization (RBRDO). The Eigenvector Dimension Reduction (EDR) method is used for the probability analysis method. It has been demonstrated that the EDR method is more accurate and efficient than the Second-Order Reliability Method (SORM) for reliability and quality assessment. Moreover, it can simultaneously evaluate both reliability and quality without any extra expense. Two practical engineering problems (vehicle side impact and layered bonding plates) are used to demonstrate the effectiveness of the EDR method.

In the last decade, considerable advances have been made in reliability-based design optimization (RBDO). One assumption in RBDO is that the complete information of input uncertainties are known. However, this assumption is not valid in practical engineering applications, due to the lack of sufficient data. In practical engineering design, information concerning uncertainty parameters is usually in the form of finite samples. Existing methods in uncertainty based design optimization cannot handle design problems involving epistemic uncertainty with a shortage of information. Recently, a novel method referred to as Bayesian Reliability-Based Design Optimization (BRBDO) was proposed to properly handle design problems when engaging both epistemic and aleatory uncertainties [1]. However, when a design problem involves a large number of epistemic variables, the computation task for BRBDO becomes extremely expensive.

Researchers desire to evaluate system reliability uniquely and efficiently. Despite its strong technical demand, little progress has been made on system reliability analysis in the last two decades. Up to now, bound methods for system reliability prediction have been dominant. For system reliability bounds, the second order bound method gives fairly accurate prediction for system reliability assuming that the probabilities of second-order joint events are accurately obtained. Two primary challenges in system reliability analysis are evaluation of the probabilities of second-order joint events and no unique system reliability for design optimization. Firstly, the greatest technical demand is found in an accurate and efficient method to numerically evaluate the probability of a second-order joint event.

This paper presents an innovative approach for quality engineering using the Eigenvector Dimension Reduction (EDR) Method. Currently industry relies heavily upon the use of the Taguchi method and Signal to Noise (S/N) ratios as quality indices. However, some disadvantages of the Taguchi method exist such as, its reliance upon samples occurring at specified levels, results to be valid at only the current design point, and its expensiveness to maintain a certain level of confidence. Recently, it has been shown that the EDR method can accurately provide an analysis of variance, similar to that of the Taguchi method, but is not hindered by the aforementioned drawbacks of the Taguchi method. This is evident because the EDR method is based upon fundamental statistics, where the statistical information for each design parameter is used to estimate the uncertainty propagation through engineering systems.

The need for accurate virtual prototyping prediction is well documented in the literature. For welded body structures one notable shortcoming has been the ability for finite element analysis (FEA) to accurately predict the failure of welded joints due to cyclic loading. A new approach to representing spot-welds for durability evaluation in automotive sheet metal structures is presented here. Excellent correlation with spot-weld failures in actual tests have been observed through this modeling approach. We present a method of representing spot-welds using the finite element method. This method has shown to be able of predicting the behavior of spot-welds prior to the build of any prototypes or testing. Further, for spot-weld failures we present evidence that reveals which radial quadrant of the spot-weld will contain the failure. This method also allows engineers to determine the mechanism of failure. This paper describes in detail the spot-weld modeling method.

A correlation of aerodynamic wind tunnels was initiated between Chrysler, Ford and General Motors under the umbrella of the United States Council for Automotive Research (USCAR). The wind tunnels used in this correlation were the open jet tunnel at Chrysler's Aero Acoustic Wind Tunnel (AAWT), the open jet tunnel at the Jacobs Drivability Test Facility (DTF) that Ford uses, and the closed jet tunnel at General Motors Aerodynamics Laboratory (GMAL). Initially, existing non-competitive aerodynamic data was compared to determine the feasibility of facility correlation. Once feasibility was established, a series of standardized tests with six vehicles were conducted at the three wind tunnels. The size and body styles of the six vehicles were selected to cover the spectrum of production vehicles produced by the three companies. All vehicles were tested at EPA loading conditions. Despite the significant differences between the three facilities, the correlation results were very good.

With the current increase in concern and awareness regarding sustainability and energy, a new focus has been placed on the field of engineering. In this realm of focus, how to educate engineers, more specifically how to continually educate engineers to keep up with technology and the changing workforce has become a very important topic of interest. There exists a gap between graduate studies and professional implementation of technology which the Energy Systems Engineering [ESE] program currently in deployment and development between the University of Michigan and General Motors seeks to address. This work outlines current efforts in encouraging new engineers to enter the field, but focuses primarily on continuing and re-educating the workforce to meet the needs of new technologies. Examples of academic-industry cooperation will be discussed, with some focus on the benefit and experience of the student.

Elastomers are traditionally designed for use in applications that require specific mechanical properties. Unfortunately, these properties change with respect to many different variables including heat, light, fatigue, oxygen, ozone, and the catalytic effects of trace elements. When elastomeric mounts are designed for NVH use in vehicles, they are designed to isolate specific unwanted frequencies. As the elastomers age however, the desired elastomeric properties may have changed with time. This study looks at the variability seen in new vehicle engine mounts and how the dynamic properties change with respect to miles accumulated on fleet and durability test vehicles.

The methodology of predicting analytical fatigue life of automotive body structures using two commercially available computer codes, NASTRAN and NCODE is described. Modal transient durability simulations are improved with use of residual vectors incorporating inertia relief basis functions. Simulations consisting of hundreds of thousand finite elements and hours of road loads are routine.

The so-called Modified Martempering discussed in this work differs from the standard martempering by that the temperature of the quenching bath is below the Ms point. In spite of the fact the lower temperature increases the severity of quenching, this also usually avoids the bainite formation, and by this reason, it is possible to make a fair comparison between different processes, which result in different microstructures. The present study shows the results in terms of mechanical properties, impact resistance in special of a cold work tool steel class, after being heat treated by the isothermal modified martempering process, as well as a comparison with the conventional quenching and tempering process and the austempering as well.

The innovation term has been so widely misused that the confusion observed among the companies trying to get themselves into the innovation realm is a common and natural consequence. The lack of understanding of the innovation dynamics, flow and metrics generally culminate in a non-well-thought implementation of innovation processes and policies that are usually tragic in the short term. The most common consequences are the loss of credibility of the innovation process in general among leaders and employees, and the loss of credibility of the company as an innovative company among suppliers, partners and customers, causing these companies to abandon this powerful tool and, as consequence, to limit their capabilities to compete in the future. In order to prevent this from happening, companies that were not built upon innovation will need to grow capability and change cultural priorities to match the demands of the innovation process.

As the automobile industry is moving towards Electrical vehicles, it becomes very important to have low cost and robust solution to seal all the internal Battery sub systems. It’s a known fact that various IC engine Vehicles are already using Room temperature vulcanized rubber (RTV) for many metal and composite sealing interfaces. Nevertheless, it always needs a good structural design to have good sealing performance. For designing a robust RTV joint for composite structures, it becomes important to have standard RTV chamfers. Sometimes even with these standards, it becomes very costly in having warranty issues when we have weak structure around RTV chamfers. Any joint structure involves multiple design parameters which might impact the sealing performance. Some of the joint structural parameters should be well designed at the early phase of product development cycle, which otherwise will later add lot of cost in modifying the product with its integrated components.

The concept of product or system function is considered as described in the Taguchi System of Quality Engineering. The importance of transfer functions is also discussed and a review of conventional value analysis techniques is given. This paper proposes a combination of the principles of robust design and value methodology to enable on-target functionality and direct cost allocation early in the product development process. The discussion on integration of value analysis principles in robust design methodology is provided considering the six sigma environment.

This paper presents real-world driving energy and fuel consumption results for the second-generation Chevrolet Volt plug-in hybrid electric vehicle (PHEV). A drive cycle, local to Michigan Technological University, was designed to mimic urban and highway driving test cycles in terms of distance, transients and average velocity, but with significant elevation changes to establish an energy intensive real-world driving cycle for assessing potential energy savings for connected and automated vehicle (CAV) control. The investigation began by establishing baseline and repeatability of energy consumption at various battery states of charge. It was determined that drive cycle energy consumption under a randomized set of boundary conditions varied within 3.6% of mean energy consumption regardless of initial battery state of charge.

Multiple automotive applications exist for small electric motors that are activated by vehicle occupants for various functions such as window lifts and seat adjusters. For such a motor to be described as high quality, not only should the sound it produces be low in amplitude, but it also needs to be free from pulsations and variations that might occur during its (otherwise) steady-state operation. If a motor’s sound contains pulsations or variations between 2 and 8 cycles per second, the variation is described as warble. To establish performance targets for warble noise at both the vehicle and component level a way to measure and quantify the warble noise must be established. Building on existing sound quality metrics such as loudness and pitch variation, a method is established by which processed sound data is put through a secondary operation of Fourier analysis.

Planetary gear set is one of the most commonly used gear systems in automotive industry as they cater to high power density requirements. A simple planetary gear set consists of a sun gear, ring gear, planets and carrier which houses planet gears. Efficiency of a transmission is dependent upon performance of gear sets involved in power transfer to a great extent. Structural rigidity of a planetary carrier is critical in a planetary gear set as its deflection may alter the load distribution of gears in mesh causing durability and noise issues. Limited studies exist based on geometrical parameters of a carrier which would help a designer in selecting the dimensions at an early stage. In this study, an end to end automated FEA process based on DOE and optimization in Isight is developed. The method incorporates a workflow allowing for an update of carrier geometry, FE model setup, analysis job submission and post-processing of results.