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This work analyzes a cantilevered piezoelectric beam device for harvesting energy from the simultaneous rotation and translational vibration of vehicle wheels. The device attaches to the wheel rim so that it displaces tangentially during operation. A lumped-parameter analytical model for the coupled electromechanical system is derived. The device has one natural frequency that is speed-dependent because of centripetal acceleration affecting the total stiffness of the device. Even though the device has one natural frequency, it experiences three resonances as the rotation speed varies. One resonance occurs when the rotation speed coincides with the speed-dependent natural frequency of the device. The other two resonances are associated with excitations from the vibration of the vehicle wheel. The device’s parameters are chosen so that these three resonances occur when the wheel travels near 30 mph, 55 mph, and 70 mph.

A nonlinear finite element passenger car radial-ply tire model was developed to investigate a tire's three-dimensional transmissibility in the X, Y, and Z directions. The reaction forces of the tire axle in longitudinal (X axis), lateral (Y axis), and vertical (Z axis) directions were recorded when the tire encountered a cleat, and then the FFT (Fast Fourier Transform) algorithm was applied to extract tire's transient response information in the frequency domain. The result showed that this passenger car tire has clear peaks at 47-51 and 91-92 Hz longitudinal, 41-45 Hz lateral, and 80-83Hz vertical. An analytical rigid ring model was also formulated, based on the dynamic equations of the rigid ring tire model. The characteristic equations were obtained and solved for eigenvalues and eigenvectors, which represent tire's free vibration natural frequencies and mode shapes.

Shearography has been proved to be highly effective for nondestructive testing (NDT), especially for NDT of composite materials used in the automotive and aerospace engineering. While its application in material testing and material research has already achieved more and more acceptance in research and industry, its applications are mainly limited to the inspection and testing of an object surface which can directly be observed by a shearographic camera. Its application is mainly limited to inspect and test an object surface which can directly be observed by a shearographic camera. It is impossible to inspect an internal surface of a container. If the reflected light of the surface, which has to be examined, can’t reach the shearographic camera there is still no inspection possible. This paper presents the development of a rigid shearographic endoscope. The development enabled shearographic inspection on both external and internal surfaces of objects.

In the dense fabric of urban areas, electric scooters have rapidly become a preferred mode of transportation. As they cater to modern mobility demands, they present significant safety challenges, especially when interacting with pedestrians. In general, e-scooters are suggested to be ridden in bike lanes/sidewalks or share the road with cars at the maximum speed of about 15-20 mph, which is more flexible and much faster than pedestrians and bicyclists. Accurate prediction of pedestrian movement, coupled with assistant motion control of scooters, is essential in minimizing collision risks and seamlessly integrating scooters in areas dense with pedestrians. Addressing these safety concerns, our research introduces a novel e-Scooter collision avoidance system (eCAS) with a method for predicting pedestrian trajectories, employing an advanced Long short-term memory (LSTM) network integrated with a state refinement module.

Adhesively bonded joints have been applied in the automotive industry for the past few decades due to their advantages such as higher fatigue resistance, light weight, capability of joining dissimilar materials, good energy absorption, and high torsional stiffness for overall body structure. They also provide an effective seal against noise and vibration at a low cost. There exists the challenge of defining the fatigue characteristics of adhesive joints under cyclic loading conditions, and conventional methods have limitations in detecting the crack initiation of a bonded joint. This study introduces a method of detecting crack initiation by using the frequency method. It is found that stiffness change in the system is highly correlated to change in natural frequencies. By monitoring the change in natural frequencies, the crack initiation can be detected.

Integration of electric vehicles (EV) in power distribution systems reduces emissions that contribute to climate changes and improves public health by reducing ecological damage. Even though EVs significantly impact reducing carbon emissions and less dependency on hydrocarbon-based generators, they could negatively impact power systems, especially power quality. This paper analyzes electric vehicle charging stations’ impact on power quality concerning the voltage and current analysis of the harmonic distortion. As a case study, a sample system has been chosen, and a charging station is integrated into the system to investigate the harmonic impacts on the system. Finally, various mitigation techniques to eliminate the harmonics and minimize EVs’ adverse impacts on power quality in power distribution systems have been discussed.

This research proposes an automatic computer-aided design, analysis, and optimization process of a twist beam rear suspension system. The process combines CAD (Computer-Aided Design), CAE (Computer-Aided Engineering), and optimization technologies into an automation procedure, which includes: structural design, dynamic analysis, vibration analysis, durability analysis, and multidisciplinary optimization. The automation results shown the twist beam rear suspension weight reduced, the durability fatigue life increased, and the K&C (kinematics & compliance) characteristics are improved significantly.

Tribological performance of tungsten sulfide (WS2) nanoparticles, microparticles and mixtures of the two were investigated. Previous research showed that friction and wear reduction can be achieved with nanoparticles. Often these improvements were mutually exclusive, or achieved under special conditions (high temperature, high vacuum) or with hard-to-synthesize inorganic-fullerene WS2 nanoparticles. This study aimed at investigating the friction and wear reduction of WS2 of nanoparticles and microparticles that can be synthesized in bulk and/or purchased off the shelf. Mixtures of WS2 nanoparticles and microparticles were also tested to see if a combination of reduced friction and wear would be achieved. The effect of the mixing process on the morphology of the particles was also reported. The microparticles showed the largest reduction in coefficient of friction while the nanoparticles showed the largest wear scar area reduction.

Technological advancement in the automotive industry necessities a closer focus on the functional safety for higher automated driving levels. The automotive industry is transforming from conventional driving technology, where the driver or the human is a part of the control loop, to fully autonomous development and self-driving mode. The Society of Automotive Engineers (SAE) defines the level 4 of autonomy: “Automated driving feature will not require the driver to take over driving control.” Thus, more and more safety related electronic control units (ECUs) are deployed in the control module to support the vehicle. As a result, more complexity of system architecture, software, and hardware are interacting and interfacing in the control system, which increases the risk of both systematic and random hardware failures.

Multicore microcontrollers are rapidly making their way into the automotive industry. We have adopted the Cilk approach (MIT 1994) to develop a pure ANSI C Fork-Join dynamic scheduling runtime middle-layer with a work-stealing scheduler targeted for automotive multicore embedded systems. This middle-layer could be running on top of any AUTOSAR compliant multicore RTOS. We recently have successfully integrated our runtime layer into parts of legacy Ford powertrain software at Ford Motor Company. We have used the 3-core AURIX multicore chip from Infineon and the multicore RTA-OS. For testing purposes, we have forked some parallelizable functions inside two periodic tasks in Ford legacy powertrain software to be dynamically scheduled and executed on the available cores. Our preliminary evaluation showed 1.3–1.4x speedups for these two forked tasks.

The number of EVs are increasing in power distribution systems every day. This research analyses different penetration levels of electric vehicles in power distribution systems to provide stable energy for smart devices and observes its impacts on operational costs and environmental emissions. The supply of EV power is determined based on smart device consumption by optimal energy management of EV batteries so that both the utilities and the car owner get benefits. Utilities can save energy by reducing system loss, while EV owners can earn money by selling it to utilities at their convenient time for smart device operations. The PG&E 69-bus distribution system is used for the simulation and case studies. Case studies in this research show how the power management of EV's batteries charging and discharging characteristics benefits both utilities and EV owners. The uncertainty of the driving pattern of EVs is also considered in the research to get more accurate results.

This research assesses the integration of different levels of electric vehicles (EVs) in the distribution system and observes its impacts on environmental emissions and power system operational costs. EVs can contribute to reducing the environmental emission from two different aspects. First, by replacing the traditional combustion engine cars with EVs for providing clean and environment friendly transportation and second, by integrating EVs in the distribution system through the V2G program, by providing power to the utility during peak hours and reducing the emission created by hydrocarbon dependent generators. The PG&E 69-bus distribution system (DS) is used to simulate the integration of EVs and to perform energy management to assess the operational costs and emissions. The uncertainty of driving patterns of EVs are considered in this research to get more accurate results.

This paper describes the scuffing tests performed to understand the effect of surface roughness and lubrication on scuffing behavior for austempered ductile iron (ADI) material. As the scuffing tendency is increased, metal-to-metal interaction between contacting surfaces is increased. Lubrication between sliding surfaces becomes the boundary or mixed lubrication condition. Oil film breakdown leads to scuffing failure with the critical load. Hence, the role of surface roughness and lubrication becomes prominent in scuffing study. There are some studies in which the influence of the surface roughness and lubrication on scuffing was evaluated. However, no comprehensive scuffing study has been found in the literature regarding the effect of surface roughness and lubrication on scuffing behavior of ADI material. The current research took into account the inferences of surface roughness and lubrication on scuffing for ADI.

Passengers' frequent requests are for less Noise, Vibration and Harshness (NVH) in the vehicle compartment. This and the reduction of noise and vibration levels from major sources like the engine necessitate better performance of other sources of noise and vibrations in a vehicle. Some of these sources are the hydraulic circuits including the power steering system. Fluid pulses or pressure ripples, generated typically by a pump, become excitation forces to the structure of a vehicle or the steering gear and represent a considerable source of discomfort to the vehicle passengers. Current power steering technology attenuates this ripple along the pressure line connecting the pump to the steering gear. Finding the optimum design configuration for the components (hose, tuner, tube, and others) has been a matter of experience-based trial and error. This paper is a part of a program to simulate and optimize fluid borne noise in hydraulic circuits.

Design of sheet metal drawing processes requires accurate information about the distribution of restraining forces, which is usually accomplished by a set of drawbeads positioned along the perimeter of the die cavity. This study is targeting bringing together the results of finite element analysis and experimental data in order to understand the most critical factors influencing the restraining force. The experimental study of the restraining force was performed using drawbead simulator tool installed into a tensile testing machine. Based upon the experimental results, it was observed that the restraining force of the given drawbead configuration is dependent upon the depth of bead penetration, friction between the drawbead surfaces as well as the clearance between the flanges of the drawbead simulator. This clearance is often adjusted during stamping operations to increase or decrease material inflow into the die cavity without any modification in the die.

A multi-sensor Digital Image Correlation (DIC) system is employed to measure the deformation of metal specimens during tensile tests. The multi-sensor DIC system is capable of providing high quality contour and deformation data of a 3D object. Methodology and advantages of the multi-sensor DIC system is introduced. Tests have been done on steel and aluminum specimens to prove the performance of the system. With the help of the multi-sensor DIC system, we proposed our approaches to determine the forming limit based on shape change around the necking area instead of calculate the FLD based on the in-plane strains. With the employed system, all measurements are done post-deformation, no testing controlling mechanism, such as load force control or touching control, is required. The extracted data is analyzed and the result shows a possibility that we may be able to improve current technique for Forming Limit Diagram (FLD) measurement.

The coefficient of friction between surfaces is an important criterion for predicting metal behavior during sheet metal stamping processes. This research introduces an innovative technique to find the coefficient of friction on a lubricated aluminum sheet metal surface by simulating the industrial manufacturing stamping process while using 3D digital image correlation (3D-DIC) to track the deformation. During testing, a 5000 series aluminum specimen is placed inside a Stretch-Bend-Draw Simulator (SBDS), which operates with a tensile machine to create a stretch and bend effect. The friction coefficient at the contact point between an alloy sheet metal and a punch tool is calculated using an empirical equation previously developed. In order to solve for the unknown friction coefficient, the load force and the drawback force are both required. The tensile machine software only provides the load force applied on the specimen by the load cell.

Engineering design-decisions often involve many attributes which can differ in the levels of their importance to the decision maker (DM), while also exhibiting complex statistical relationships. Learning a decision-making policy which accurately represents the DM’s actions has long been the goal of decision analysts. To circumvent elicitation and modeling issues, this process is often oversimplified in how many factors are considered and how complicated the relationships considered between them are. Without these simplifications, the classical lottery-based preference elicitation is overly expensive, and the responses degrade rapidly in quality as the number of attributes increase. In this paper, we investigate the ability of deep preference machine learning to model high-dimensional decision-making policies utilizing rankings elicited from decision makers.

Polymer Electrolyte Membrane (PEM) fuel cells have grown in research and development for many applications due to their high efficiency and humble operating condition requirements. Water management in the cathode region of the PEM fuel cell is an essential and sensitive phenomenon for cold environments and fuel cell’s performance. This paper investigates the behavior of water production by constructing a transparent-cathode PEM fuel cell. The effects of pressure, relative humidity, and cathode stoichiometric ratio on the production of water as a function of time were studied. Each test set is compared to a reference state. The images of water liquid accumulation inside the cathode bipolar plate channels are shown with the corresponding polarization curves.

Digital Image Correlation (DIC) technology is a powerful tool in the field of experimental mechanics to obtain the full-field deformation/strain information of an object. It has been rapidly applied in industry in recent years. However, for the large-angle full-field strain measurement of small-sized cylindrical objects, it’s still a challenge to the DIC accurate measurement due to its small size and curved surface. In this paper, a measurement method based on the multi-camera DIC system is proposed to study the compressive performance of small-sized cylindrical materials. Three cameras form two stereo DIC measurement systems (1 and 2 cameras, and 2 and 3 cameras), each of which measures a part of the object. By calibrating three cameras at the same time, two stereos DIC coordinate systems can be unified to one coordinate system. Then match the two sets of DIC measurement data together to achieve large-angle measurement of the cylindrical surface.