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Laser cladding is a method of material deposition through which a powdered or wire feedstock material is melted and consolidated by use of a laser to coat part of a substrate. Determining the parameters to fabricate the desired clad bead geometry for various configurations is problematic as it involves a significant investment of raw materials and time resources, and is challenging to develop a predictive model. The goal of this research is to develop an experimental methodology that minimizes the amount of data to be collected, and to develop a predictive model that is accurate, adaptable, and expandable. To develop the predictive model of the clad bead geometry, an integrated five-step approach is presented. From the experimental data, an artificial neural network model is developed along with multiple regression equations.

Ferritic nitrocarburizing offers excellent wear, scuffing, corrosion and fatigue resistance by producing a thin compound layer and diffusion zone containing ε (Fe2-3(C, N)), γ′ (Fe4N), cementite (Fe3C) and various alloy carbides and nitrides on the material surface. It is a widely accepted surface treatment process that results in smaller distortion than carburizing and carbonitriding processes. However this smaller distortion has to be further reduced to prevent the performance issues, out of tolerance distortion and post grinding work hours/cost in an automotive component. A numerical model has been developed to calculate the nitrogen and carbon composition profiles of SAE 1010 torque converter pistons during nitrocarburizing treatment. The nitrogen composition profiles are modeled against the part thickness to predict distortion.

Automotive Open System Architecture (AUTOSAR) is a system-level standard that is formed by the worldwide partnership of the automotive manufacturers and suppliers who are working together to develop a standardized Electrical and Electronic (E/E) framework and architecture for automobiles. The AUTOSAR methodology has two main activities: system configuration and the Electronic Control Unit (ECU) configuration. The system configuration is the mapping of the software components to the ECUs based on the system requirements. The ECU configuration process is an important part of the ECU software integration and generation. ECU specific information is extracted from the system configuration description and all the necessary information for the implementation such as tasks, scheduling, assignments of the runnables to tasks and configuration of the Basic Software (BSW) modules, are performed. The ECU configuration process involves configuring every single module of the AUTOSAR architecture.

The ‘boundary of space’ model representing all possible positions which may be occupied by a mechanism during its normal range of motion (for all positions and orientations) is called the work envelope. In the robotic domain, it is also known as the robot operating envelope or workspace. Several researchers have investigated workspace boundaries for different degrees of freedom (DOF), joint types and kinematic structures utilizing many approaches. The work envelope provides essential boundary information, which is critical for safety and layout concerns, but the work envelope information does not by itself determine the reach feasibility of a desired configuration. The effect of orientation is not captured as well as the coupling related to operational parameters. Included in this are spatial occupancy concerns due to linking multiple kinematic chains, which is an issue with multi-tasking machine tools, and manufacturing cells.

Contemporary manufacturing systems are still evolving. The system elements, layouts, and integration methods are changing continuously, and ‘collaborative robots’ (CoBots) are now being considered as practical industrial solutions. CoBots, unlike traditional CoBots, are safe and flexible enough to work with humans. Although CoBots have the potential to become standard in production systems, there is no strong foundation for systems design and development. The focus of this research is to provide a foundation and four tier framework to facilitate the design, development and integration of CoBots. The framework consists of the system level, work-cell level, machine level, and worker level. Sixty-five percent of traditional robots are installed in the automobile industry and it takes 200 hours to program (and reprogram) them.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

Carbon fiber sheet molding compound (SMC) is an attractive material for automotive lightweighting applications, but several issues present themselves when adapting a process developed for glass fiber composites to instead use carbon fibers. SMC is a discontinuous fiber material, so individual carbon fiber tows must be chopped into uniform rovings before being compounded with the resin matrix. Rotary chopping is one such method for producing rovings, but high wear rates are seen when cutting carbon fibers. Experiments were performed to investigate the wear progression of cutting blades during rotary carbon fiber chopping. A small rotary chopper with a polyurethane (PU) backing and thin, hardened steel blades was used to perform extended wear tests (120,000 chops, or until failure to reliably chop tows) to simulate the lifespan of blades during composite material production.

Autonomous vehicles are currently a subject of great interest and there is heavy research on creating and improving algorithms for detecting objects in their vicinity. A ROS-based deep learning approach has been developed to detect objects using point cloud data. With encoded raw light detection and ranging (LiDAR) and camera data, several basic statistics such as elevation and density are generated. The system leverages a simple and fast convolutional neural network (CNN) solution for object identification and localization classification and generation of a bounding box to detect vehicles, pedestrians and cyclists was developed. The system is implemented on an Nvidia Jetson TX2 embedded computing platform, the classification and location of the objects are determined by the neural network. Coordinates and other properties of the object are published on to various ROS topics which are then serviced by visualization and data handling routines.

Electric vehicle is increasingly becoming popular and an alternative choice for the consumers because of its environment-friendly operation. Permanent magnet synchronous machines are widely and commonly used as traction motors since they provide higher torque and power density. High torque and power density mean higher current which eventually causes higher temperature rise in the motor. Higher temperature rise directly affects the motor output. Standard tests for UDDS (Urban Dynamometer Driving Schedule) and HWFET (Highway Fuel Economy Driving Schedule) drive cycles are used to determine performance of traction motors in terms of torque, power, efficiency and thermal health. Traction motors require high torque at low speed for starting and climbing; high power at high speed for cruising; wide speed range; a fast torque response; high efficiency over wide torque and speed ranges and high reliability.

We are witnessing a rapid and ongoing expansion of nanoscience, driven by potential applications in advanced materials and nanotechnology. There is a race to develop techniques that may allow controlling the size, shape of nanostructures that can allow the tuning of their optical and electronic properties. Plasmonics is a field that encompasses and profits from the optical enhancement in nanostructures that support plasmon excitations. One of these new techniques is surface-enhanced Raman scattering (SERS), commonly used for nanostructure characterization. In the present report, we present a theoretical model for plasmon excitation and electric field enhancement that help to provide an explanation for the special features observed in experimental SERS. Two sets of experimental results are discussed illustrating the make out of the signature of the plasmonics producing the optical enhancement.

Experimental and numerical studies have been completed on the deformation behaviour of round AA6061-T6 aluminum extrusions during an axial cutting deformation mode employing both curved and straight deflectors to control the bending deformation of petalled side walls. Round extrusions of length 200 mm with a nominal wall thickness of 3.175 mm and an external diameter of 50.8 mm were considered. A heat treated 4140 steel alloy cutter and deflectors, both straight and curved, were designed and manufactured for the testing considered. The four blades of the cutter had an approximate average thickness of 1.00 mm which were designed to penetrate through the round AA6061-T6 extrusions. Experimental observations illustrated high crush force efficiencies of 0.82 for the extrusions which experienced the cutting deformation mode with the deflectors. Total energy absorption during the cutting process was approximately 5.48 kJ.

Carburized parts often see use in powertrain components for the automotive industry. These parts are commonly quenched and tempered after the carburizing process. The present study compared the austempering heat treatment to the traditional quench-and-temper process for carburized parts. Samples were produced from SAE 8620, 4320, and 8822 steels and heat treated across a range of conditions for austempering and for quench-and-tempering. Distortion was examined through the use of Navy C-Ring samples. Microstructure, hardness, and Charpy toughness were also examined. X-ray diffraction was used to compare the residual stress found in the case of the components after the quench-and-temper and the austempering heat treatments. Austempering samples showed less distortion and higher compressive residual stresses, while maintaining comparable hardness values in both case and core. Toughness measurements were also comparable between both processes.

Gray cast iron brake rotor experiences substantial wear during braking and contributes largely to the wear debris emissions. Surface coating on the gray cast iron rotor represents a trending approach dealing with the problems. In this research, a new plasma electrolytic aluminating (PEA) process was used for preparing an alumina-based ceramic coating with metallurgical bonding to the gray cast iron. Three different types of brake pads (ceramic, semi-metallic and non asbestos organic (NAO)) were used for tribotests. Performances of PEA coatings vs. different brake pad materials were comparatively investigated with respect to their coefficients of friction (COFs) and wear. The PEA-coated brake rotor has a dimple-like surface which promotes the formation of a thin transferred film to protect the rotor from wear. The transferred film materials come from the wear debris of the pads. The secondary plateaus are regenerated on the brake pads through compacting wear debris of the pads.

Light-weighting fiber composite materials introduced to reduce vehicle mass and known as innovative materials research activities since they provide high specific stiffness and strength compared to contemporary engineering materials. Nonetheless, there are issues related automation strategies and handling methods. Material handling of flexible textile/fiber components is a process bottleneck and it is currently being performed by setting up multi-stage manual operations for hand layups. Consequently, the long-term research objective is to develop semi-automated pick and place processes for flexible materials utilizing collaborative robots within the process. The immediate research is to experimentally validate innovatively designed grippers for efficient material pick and place tasks.

Environmental concerns and rising fuel costs are driving Ontario's municipalities and fleet operators to consider alternative vehicle technologies. Elevated fuel consumption and air emissions are attributed to the unique operations of fleet vehicles and in particular, during idling. While drivers of passenger vehicles may have the option of simply not idling, fleet and emergency vehicle operators, may need to keep the vehicle operating to supply power to critical onboard equipment. These demands may be exacerbated during seasonal, temperature extremes. However, prolonged idling can impose significant environmental and economic burdens. Hybrid vehicles have yet to be utilized widely by Ontario's fleets, but there are other approaches to reduce emissions, including alternative “green” technologies to operate in-vehicle equipment and maintain fleet vehicle capabilities instead of idling.

This paper proposes and evaluates the use of a robust variable torque distribution (VTD) yaw moment control for an all wheel drive (AWD) hybrid vehicle prototype currently under development. The proposed VTD controller was used to improve the linearity of vehicle response to driver input through the modulation of front-to-rear torque distribution and a corrective torque differential between the left and right rear wheels. The development of a non-linear vehicle model and a reference model tracking sliding mode based control are discussed. The efficacy of the proposed control system was demonstrated through the use of numerical simulations using the developed non-linear vehicle model. The simulation results presented indicate the effectiveness of the proposed system and the potential restrictions to such a system including tire saturation and drivetrain component limitations.

Whole field displacement/strain measurement of automotive components can be done efficiently by digital image correlation based technique. Inverse problems with this kind of input data, such as the identification of damage parameters/effective modulus in different part of a component, can be pursued by either virtual fields method or finite element model updating. In this paper, the two methods are applied to the identification of a tension plate with a circular hole, and different aspects of the two methods are discussed. It is found that the success of virtual fields method relies on the choice of a set of optimal virtual displacement fields; finite element model updating, on the other hand, can be applied to any geometry and any load condition, and can also be applied to problems where only limited number of measurements are available. However, its performance relies on the choice of optimization algorithms.

Preliminary empirical and modeling analyses are conducted to evaluate the energy efficiency of in-cylinder and external fuel injection strategies and their impact on the energy required to enable diesel particulate filter (DPF) regeneration for instance. During the tests, a thermal wave that is generated from the engine propagates along the exhaust pipe to the DPF substrate. The thermal response of the exhaust system is recorded with the thermocouple arrays embedded in the exhaust system. To implement the external fuel injection, an array of thermocouples and pressure sensors in the DPF provide the necessary feedback to the control system. The external fuel injection is dynamically adjusted based on the thermal response of the DPF substrate to improve the thermal management and to reduce the supplemental energy. This research intends to quantify the effectiveness of the supplemental energy utilization on aftertreatment enabling.

Rollover crash is one of the most serious safety problems for light weight vehicles. In the USA, rollover crashes account for almost one-third of all occupant fatalities in light weight vehicles. Similar statistics are found for other countries. Thus, rollover crashes have received significant attention in recent years. In the USA and Canada, automotive manufacturers are required to comply with the roof strength requirement of “1.5 times the unloaded vehicle weight” to ensure safety in rollover. NHTSA is currently considering a set of countermeasures to improve the rollover safety, where one of the proposals is to increase the roof strength limit to “2.5 times the unloaded vehicle weight”. This increased roof strength limit seemingly has been motivated based on the benchmark study of current vehicle fleet.

Heavy traffic volume makes tailgating a common picture on the road today. Wake interference, particularly in the scenario when a relatively small sedan drives into the wake of a large truck, may raise some serious highway safety concerns. In this paper, the characteristics of the separation bubble of model trucks with various degrees of details are studied. The objective is to find out the impact of truck model details on the characteristics of the wake bubble. Our wind tunnel results revealed that the degree of model detail has a significant effect on the wake bubble; the bubble length increases with model details.