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In recent years, there has been a sustained effort by the automotive OEMs and suppliers to improve the vehicle driveline efficiency. This has been in response to customer demands for greater vehicle fuel economy and increasingly stringent government regulations. The automotive rear axle is one of the major sources of power loss in the driveline, and hence represents an area where power loss improvements can have a significant impact on overall vehicle fuel economy. Both the friction induced mechanical losses and the spin losses vary significantly with the operating temperature of the lubricant. Also, the preloads in the bearings can vary due to temperature fluctuations. The temperatures of the lubricant, the gear tooth contacting surfaces, and the bearing contact surfaces are critical to the overall axle performance in terms of power losses, fatigue life, and wear.

A detailed study of the effects of shim stack assemblies on performance of hydraulic mono-tube vehicle shock absorbers is presented. Currently, shim stacks are modeled as blow-off valves in hydraulic models of shock absorbers. Using this simplification, important material and geometrical properties of shim stacks cannot be studied and their effects cannot be understood on overall damper performance. In this paper, shim stack deflection is investigated and a mathematical model is presented for shim stack deflection. This model is then incorporated into the mathematical model of a hydraulic damper and various properties of shim stack and their effects on damper characteristics are studied. Energy and variational methods were used to develop the mathematical model of the shim stack. The mathematical model also takes into account the sliding effects of the shims on each other when the shim stack is deflected.

As applications in aerospace, transportation and data centers are faced with increased electric power consumption, their dc operating voltages have increased to reduce cable weight and to improve efficiency. Electric arcs in these systems still cause dangerous fault conditions and have garnered more attention in recent years. Arcs can be classified as either low impedance or high impedance arcs and both can cause insulation damage and fires. Low impedance arcs release lots of energy when high voltage becomes nearly shorted to ground. High impedance arcs can occur when two current-carrying electrodes are separated, either by vibration of a loose connection or by cables snapping. The high impedance arc decreases load current due to a higher equivalent load impedance seen by the source. This complicates the differentiation of a high impedance arc fault from normal operation.

Performance characteristics of passive, active, and broadband adaptive engine mounts are compared over a wide frequency range up to 250 Hz in the context of a quarter-vehicle heave model. The optimal damping coefficient of a rubber-metal mount is determined using random vibration theory. The small-scale active mount employs proportional-plus-integral control based on linear optimal control theory. The new adaptive hydraulic mount system implements an on-off damping control mode by using engine intake-manifold vacuum and a microprocessor-based solenoid valve controller. Through analytical methods, it is observed that this adaptive mount provides most desirable dynamic performance with regard to the engine-bounce control, shock absorption and vibration isolation performance requirements. Although technical prospects of the proposed adaptive system appear promising, in-situ performance needs to be evaluated.

A mathematical basis for predicting loaded off-line of action contact at the tips of undermodified gear teeth is discussed. Two methods of solving the contact problem, using a modified simplex algorithm, are used to predict the load distribution. The methods differ in the compliance matrix formulation and the way they search for contact. The first method uses a tapered plate model and the second method uses a finite element model. The effects of off-line of action contact on load sharing, effective contact ratio and motion curves are shown.

The automotive NVH research infrastructure at Ohio State includes the Center for Automotive Research, the Acoustics and Dynamics Laboratory, and the Gear Dynamics and Gear Noise Research Laboratory. This paper describes the facilities of these laboratories. Two unique existing facilities, namely the transmission error measurement of gears and a laboratory for the experimental measurement of engine breathing systems, will be emphasized. Also covered are the enhancements that are envisioned through a recent grant from the Ohio Board of Regents.

In this paper, we will present parametric results of performing dynamic analysis of layshaft gear trains typically used in automotive transmissions with emphasis on the vibratory response due to transmission error excitation. A three-dimensional multiple degrees of freedom lumped parameter dynamic model of a generic layshaft type geared rotor system (with three parallel rotating shafts coupled by two sets of gear pairs) has been formulated analytically. The model includes the effects of both rotational and translational displacements of each gears, and bounce and pitch motions of the counter-shaft. The natural frequencies and mode shapes are computed numerically by solving an eigenvalue problem derived from applying harmonic solutions to the equations of motion. The complete set of mode shapes are then used in forced response calculations based on the modal expansion method to predict gear accelerations, dynamic transmission errors, mesh force and bearing loads.

Structural Health Monitoring (SHM), especially in the field of rotary machinery diagnosis, plays a crucial role in determining the defect category as well as its intensity in a machine element. This paper proposes a new framework for real-time classification of structural defects in a roller bearing test rig using time domain-based classification algorithms. Along with the bearing defects, the effect of eccentric shaft loading has also been analyzed. The entire system comprises of three modules: sensor module – using accelerometers for data collection, data processing module – using time-domain based signal processing algorithms for feature extraction, and classification module – comprising of deep learning algorithms for classifying between different structural defects occurring within the inner and outer race of the bearing.

The advent of low emission regulations on fuel systems has made conventional sealing materials such as acry-lonitrile butadiene rubber (NBR) unfit for sealing most fuel systems. Therefore, it is imperative to look beyond conventional rubbers and towards more exotic materials to seal such applications. In this study, the permeation characteristics and the change in physical properties of several elastomeric materials (NBR, hydrogenated NBR (HNBR), and fluorocarbon elastomers (FKM)) as well as various poly(tetrafluoroethylene) (PTFE) composites were evaluated with four different fuel mixtures. The sealing materials were tested using vaporimeter cups. The results are discussed as a function of the materials' nature, composition, and filler content.