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In-cylinder pressure measurement is an important tool in internal combustion engine research and development for combustion, cycle performance, and knock analysis in spark-ignition engines. In a typical laboratory setup, a sub crank angle resolved (typically between 0.1o and 0.5o) optical encoder is installed on the engine crankshaft, and a piezoelectric pressure transducer is installed in the engine cylinder. The charge signal produced by the transducer due to changes in cylinder pressure during the engine cycle is converted to voltage by a charge amplifier, and this analog voltage is read by a high-speed data acquisition (DAQ) system at each encoder trigger pulse. The high speed of engine operation and the need to collect hundreds of engine cycles for appropriate cycle-averaging requires significant processor speed and memory, making typical data acquisition systems very expensive.

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.

Making a sturdy battery box or enclosure is one of the many challenging issues that the expansion of electrification entails. Many characteristics of an effective battery housing contribute to the safety of passengers and shield the battery from the harsh environment created by vibrations and shocks due to varying road profiles in the vehicle. This results in stress and deformations of different degrees. There is a need to understand and develop a correlation between structural performance and lightweight design of battery enclosure as this can increase the range of the drive and the life cycle of a battery pack. This paper investigates the following points: I) A conceptualized CAD model of battery enclosure is developed to understand the design parameters such as utilization of different material for strength and structural changes for performance against vibration and strength.

A finite element/contact mechanics (FE/CM) method is used to determine the tooth contact forces, static transmission error, and tooth pair stiffnesses for spur gear pairs that have pitting damage. The pitting damage prevents portions of the tooth surface from carrying load, which results in meaningfully different contact pressure distribution on the gear teeth and deformations at the mesh. Pits of elliptical shape are investigated. Parametric analyses are used to investigate the effect of pit width (along the tooth face) and height (along the tooth profile) on the gear tooth mesh interface. Pitting damage increases static transmission error and decreases tooth pair stiffness. Tooth contact forces differ only in the portions of the mesh cycle when multiple pairs of teeth are in contact and share the transmitted load. Pitting damage does not change the loads when only a single pair of teeth are in contact.

Mobility in the automotive and transportation sectors has been experiencing a period of unprecedented evolution. A growing need for efficient, clean and safe mobility has increased momentum toward sustainable technologies in these sectors. Toward this end, battery electric vehicles have drawn keen interest and their market share is expected to grow significantly in the coming years, especially in light-duty applications such as passenger cars. Although the battery electric vehicles feature high performance and zero tailpipe emission characteristics, economic and technical issues such as battery cost, driving range, recharging time and infrastructure remain main hurdles that need to be fully addressed. In particular, the low power density of the battery limits its broad adoption in heavy-duty applications such as class 8 semi-trailer trucks due to the required size and weight of the battery and electric motor.

Fasteners, commonly used in automotive industry, play an important role in the safety and reliability of the vehicle structural system. In practical application, bolted joints would never undergo fully reversed loading; there always will be positive mean stress on bolt. The mean stress has little influence on the fatigue life if the maximum stress is lower than a threshold which is near the yield stress of the bolt. However, when the sum of the mean stress and the stress amplitude exceeds the threshold, the endurance limit stress amplitude decreases fast as the mean stress increases. The purpose of this paper is to research the fatigue endurance limit of a fastener and establish the threshold for safe design in automotive application. In order to obtain the fatigue endurance limit at different mean stress levels, various mechanical tests were performed on M12x1.75 and M16x1.5 Class 10.9 fasteners using MTS test systems.

A finite element/contact mechanics formulation is used to analyze the dynamic tooth forces that arise from damage-induced vibrations in spur gear pairs. Tooth root crack damage of varying sizes are analyzed for a wide range of speeds that include resonant gear speeds. The added localized compliance from tooth root crack damage leads to a re-distribution of the forces on the individual gear teeth in mesh. At speeds away from resonance, smaller dynamic forces occur on the damaged tooth and larger dynamic forces occur on the tooth that engages immediately after it. These dynamic tooth contact forces cause additional transient dynamic response in the gear pair. For certain speeds and sufficiently large tooth root cracks, the damage-induced dynamic response causes large enough vibration that tooth contact loss nonlinearity occurs. For some speeds near resonance, the damage-induced vibrations cause teeth that normally lose contact to remain in contact due to vibration.

In the automotive industry, a Malfunction Indicator Light (MIL) is commonly employed to signify a failure or error in a vehicle system. To identify the root cause that has triggered a particular fault, a technician or engineer will typically run diagnostic tests and analyses. This type of analysis can take a significant amount of time and resources at the cost of customer satisfaction and perceived quality. Predicting an impending error allows for preventative measures or actions which might mitigate the effects of the error. Modern vehicles generate data in the form of sensor readings accessible through the vehicle’s Controller Area Network (CAN). Such data is generally too extensive to aid in analysis and decision making unless machine learning-based methods are used. This paper proposes a method utilizing a recurrent neural network (RNN) to predict an impending fault before it occurs through the use of CAN data.

This work illustrates the potential of Electric Vehicles (EVs) as a grid support tool that will lower carbon emissions from both the energy production sector and the transportation sector. EVs can provide peak shaving power to the grid while discharging and valley filling power while charging to flatten the total load curve of a distribution system. The idea is called Vehicle to Grid (V2G). Flattening the load curve will allow utility providers to delay upgrading, or the purchase of new power generation stations, as well as best utilize renewable energy resources that may be uncontrollable in nature. Electrical energy production and transportation combined accounted for 2,534 million metric tons of carbon dioxide emissions in the US in 2019. Utilizing EVs for transportation as well as grid support will decrease this figure in each sector. This technology may pave the way to cleaner, more reliable, cost effective energy systems.

Billboards are an effective instrument of advertisement at areas with high traffic flow such as alongside highways. They provide information to drivers for food, fuel, lodging, attractions, etc. A novel mechanical billboard has been conceived recently which contains rolling tubes to alternate as many as twelve printed signs. It has the advantages of both flexibility and cost-effectiveness. A container is built to protect the mechanism from the weather elements. To allow the displayed messages to be visible, a transparent acrylic front is installed. Due to its mechanical properties, it is a challenging task in designing a functional acrylic front. A reinforcement is selected to counter the weak flexural rigidity of the front during winds. On the other hand, the reinforced acrylic front must maintain sufficient visibility.

The Press-in-Place (PIP) gasket is a static face seal with self-retaining feature, which is used for the mating surfaces of engine components to maintain the reliability of the closed system under various operating conditions. Its design allows it to provide enough contact pressure to seal the internal fluid as well as prevent mechanical failures. Insufficient sealing pressure will lead to fluid leakage, consequently resulting in engine failures. A test fixture was designed to simulate the clamp load and internal pressure condition on a gasket bolted joint. A sensor pad in combination with TEKSCAN equipment was used to capture the overall and local pressure distribution of the PIP gasket under various engine loading conditions. Then, the test results were compared with simulated results from computer models. Through the comparisons, it was found that gasket sealing pressure of test data and CAE data shows good correlations in all internal pressure cases when the bolt load was 500 N.

As the industry moves further into the automotive age, the failure of the cup during the transportation of the parts during the assembly process is costly. Among them, the effective contact area of the suction cup could influence the significant availability of the pressure, which is necessary to investigate the truth. The essential objective for this research is trying to improve the effectiveness of the suction cups during gripers work in company’s industry. In this research, the real work condition is simulated by the experimental setup to find the influence of the effective contact area. In this paper, the proper methodology to measure the effective area by testing different size cups under different conditions is described. The results are verified by the digital image correlation (DIC) technique.

Expanding upon the authors’ previous work which utilized a GT-Power model of the Cooperative Fuels Research (CFR) engine under Research Octane Number (RON) conditions, this work defines the boundary conditions of the CFR engine under Motored Octane Number (MON) test conditions. The GT-Power model was validated against experimental CFR engine data for primary reference fuel (PRF) blends between 60 and 100 under standard MON conditions, defining the full range of interest of MON for gasoline-type fuels. The CFR engine model utilizes a predictive turbulent flame propagation sub-model, and a chemical kinetic solver for the end-gas chemistry. The validation was performed simultaneously for thermodynamic and chemical kinetic parameters to match in-cylinder pressure conditions, burn rate, and knock point prediction with experimental data, requiring only minor modifications to the flame propagation model from previous model iterations.

Motivated by accurate representations in gear dynamics models, this work analyzes the force-deflection relationship between spur gear pairs when the gear teeth have tooth root cracks. A finite element/contact mechanics approach is used to accurately capture the elastic deformations of the gear mesh incorporating kinematic gear motion; elastic deflections of the teeth, root, and blank; and elastic contact between the mating gear teeth. Tooth root crack damage of fixed sizes are analyzed, and the resulting static transmission error and mesh stiffness are calculated. These FE/CM model outputs are relatively insensitive to important gear crack geometry, including the initial crack location, the path it follows, and its final location. Crack-induced changes in static transmission error and mesh stiffness are driven by the remaining amount of the tooth that is healthy. Calculations of average-slope and local-slope mesh stiffness are included because both are used in gear dynamic models.

Research in any field of study requires analysis and comparisons or real-time predictions to extract useful information. To prove that the results have practical potential, various filtering techniques and methodologies should be designed and implemented. Filters being a class of signal processing helps innovate new technologies with various kinds of outcomes, using filters there are always various methods to solve a problem. Considering the current COVID-19 situation, researchers are working on sequencing the novel coronavirus and the genomes of people afflicted with COVID-19 using CPUs and GPUs along with various filtering techniques. In this paper we are using a method of filter implementation to collect raw heart rate data samples from fingertip and ear lobe and process those results on CPUs and GPUs. Our method of implementation to collect raw heart rate data is using a photoplethysmography method.

A new method is demonstrated for rating the “severity” of a hypoid gear set duty cycle (revolutions at torque) using the intercept of T-N curve to support gearset selection and sizing decision across vehicle programs. Historically, it has been customary to compute a cumulative damage (using Miner's Rule) for a rotating component duty cycle given a T-N curve slope and intercept for the component and failure mode of interest. The slope and intercept of a T-N curve is often proprietary to the axle manufacturer and are not published. Therefore, for upfront sizing and selection purposes representative T-N properties are used to assess relative component duty cycle severity via cumulative damage (non-dimensional quantity). A similar duty cycle severity rating can also be achieved by computing the intercept of the T-N curve instead of cumulative damage, which is the focus of this study.

As vacuum suction cups are widely used in stamping plants, it becomes urgent and important to understand their performance and failure mode. Vacuum suction cups are employed to lift, move, and place sheet metal instead of human hands. Occasionally the vacuum cups would fail and drop parts, even it would cause expensive delays in the production line. In this research, several types of vacuum cups have been studies and compared experimentally. A new tensile device and test method was developed to measure the pulling force and deformation of vacuum cups. The digital image correlation technique has been adopted to capture and analyze the contour, deformation and strain of the cups under different working conditions. The experimental results revealed that the relevant influential parameters include cup type, pulling force angles, vacuum levels, sheet metal curvatures, etc.

Self-piercing riveting (SPR) has been used in production to join sheet materials since the early 1990s. A large amount of experimental trial work was required in order to determine an appropriate combination of rivet and anvil design to fulfill the required joint parameters. The presented study is describing the methodology of SPR joint design based on numerical simulation and experimental methods of defining required simulation input parameters. The required inputs are the stress-strain curves of sheet materials and rivets for the range of strains taking place in the SPR joining process, parameters required for a fracture model for all involved materials, and friction parameters for all interfaces of SPR process. In the current study, the normalized Cockroft-Latham fracture criterion was used for predicting fracture. Custom hole and tube expansion tests were used for predicting fracture of the riveted materials and the rivet, respectively.

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.

In this study, a unique multi-camera three-dimensional digital image correlation (3D-DIC) system was designed and applied to an engine dynamometer cell to measure the displacement and strain of the exhaust manifold while an engine was running in a durability test. In the engine dynamometer cell, the ambient temperature varies from 25°C to 80°C~100°C cyclically and the exhaust manifold experiences high temperatures up to 900°C with high frequency vibrations. In order to obtain reliable data under such conditions, two 3D-DIC systems were designed and set up in the engine dynamometer. One is a high-speed 3D-DIC system, consisting of cameras with a sampling rate of 1250 frames per second. It was used to measure the local displacement of the bolted joint in the exhaust manifold. The high-speed measurement system is able to record the behavior of the bolt during the thermal cycles.