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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.

Laser cladding is used to coat a surface of a metal to enhance the metallurgical properties at the surface level of a substrate. For surface cladding operations, overlapping bead geometry is required. Single bead analyses do not provide a complete representation of essential properties; hence, this research focuses on overlapping conditions. The research scope targets the coaxial laser cladding process specifically for P420 stainless steel clad powder using a fiber optic laser with a 4.3 mm spot size on a low/medium carbon structural steel plate (AISI 1018). Many process parameters influence the bead geometrical shape, and it is assumed that the complex temperature distributions within the process could cause subsequent large variations in hardness values. The bead overlap configurations experiments are performed with 40%, 50% and 60% bead overlaps for a three-pass bead formation.

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.

The development of a collision severity model can serve as an important tool in understanding the requirements for devising countermeasures to improve occupant safety and traffic safety. Collision type, weather conditions, and driver intoxication are some of the factors that may influence motor vehicle collisions. The objective of this study is to use artificial neural networks (ANNs) to identify the major determinants or contributors to fatal collisions based on various driver, vehicle, and environment characteristics obtained from collision data from Transport Canada. The developed model will have the capability to predict similar collision outcomes based on the variables analyzed in this study. A multilayer perceptron (MLP) neural network model with feed-forward back-propagation architecture is used to develop a generalized model for predicting collision severity. The model output, collision severity, is divided into three categories - fatal, injury, and property damage only.

Explicit finite element simulations were conducted on an aluminum wheel model where a rotating bend moment was applied on its hub to simulate wheel cornering fatigue testing. A post-processor was developed to calculate equivalent von Mises alternating and mean stresses from stress tensor. The safety factors of fatigue design for each finite element were determined to assess the fatigue performance by utilizing the Goodman linear relationship. Elements with low safety factors were identified due to the prescribed boundary conditions and stress concentrations arising from wheel geometry.

Thermal comfort in automotive seating has been studied and discussed for a long time. The available research, because it is focused on the components, has not produced a model that provides insight into the human-seat system interaction. This work, which represents the beginning of an extensive research program, aims to establish the foundation for such a model. This paper will discuss the key physiological, psychological, and biomechanical factors related to perceptions of thermal comfort in automotive seats. The methodology to establish perceived thermal comfort requirements will also be presented and discussed.

One-dimensional transient modeling techniques are adapted to analyze the thermal behavior of lean-burn after-treatment systems when active flow control schemes are applied. The active control schemes include parallel alternating flow, partial restricting flow, and periodic flow reversal (FR) that are found to be especially effective to treat engine exhausts that are difficult to cope with conventional passive flow converters. To diesel particulate filters (DPF), lean NOx traps (LNT), and oxidation converters (OC), the combined use of active flow control schemes are identified to be capable of shifting the exhaust gas temperature, flow rate, and oxygen concentration to more favorable windows for the filtration, conversion, and regeneration processes. Comparison analyses are made between active flow control and passive flow control schemes in investigating the influences of gas flow, heat transfer, chemical reaction, oxygen concentration, and converter properties.

In this study the capabilities of a semi-active suspension and an active roll suspension are evaluated for comparison with a passive suspension. The vehicle used is a utility truck modeled as a multi-body system in ADAMS/Car while the ECU (electronic control unit) is built in Matlab/Simulink. Cosimulation is used in linking the vehicle model with the controller by exchanging the input and output values of each sub-system with one another. For the simulation models considered, results indicate that for a fish-hook cornering maneuver the semi-active suspension is limited in increasing vehicle performance while the active roll suspension significantly improves it. Further analysis is needed to confirm these findings.

Low temperature combustion (LTC), though effective to reduce soot and oxides of nitrogen (NOx) simultaneously from diesel engines, operates in narrowly close to unstable regions. Adaptive control strategies are developed to expand the stable operations and to improve the fuel efficiency that was commonly compromised by LTC. Engine cycle simulations were performed to better design the combustion control models. The research platform consists of an advanced common-rail diesel engine modified for the intensified single cylinder research and a set of embedded real-time (RT) controllers, field programmable gate array (FPGA) devices, and a synchronized personal computer (PC) control and measurement system.

Hollow polymer-based automotive components cannot, in general, be directly injection molded because they cannot be ejected from the mold. The common practice is to injection mold two or more parts, and then join these together with a welding process. Of the many joining process available, laser welding has an advantage in geometric design freedom. The laser weld joints are also generally stronger than those of vibration welds because the weld joints are located in the walls rather than on external flanges. Eliminating the external flanges also makes the part more compact. In transmission laser welding processes, the laser beam passes through a transparent part to its interface with an opaque part. The beam energy is absorbed near the interface in the opaque part, and heat flows back across to the transparent half to make the weld pool. So successful laser welds are possible only when there is a continuous interfacial fit between the parts.

With the increasing demand of emission reductions from the automotive industry, advanced after-treatment strategies have been investigated to overcome the challenges associated with meeting increasingly stringent emission regulations. Ongoing investigations on low temperature combustion (LTC) strategies are being researched to meet future emission regulations, however, the lowered exhaust temperature presents an even greater issue for exhaust after-treatment due to the change in combustion modes. Catalyst temperature is critical for the catalytic ability to maintain effective conversion efficiency of regulated emissions. The use of periodic flow reversal has shown benefits of maintaining catalyst temperature by alternating the exhaust flow direction through the catalytic converter, reducing the catalyst sensitivity to inlet gas temperature fluctuations.

In the recent decades, the emission and fuel efficiency regulations put forth by the emission regulation agencies have become increasingly stringent and this trend is expected to continue in future. The advanced spark ignition (SI) engines can operate under lean conditions to improve efficiency and reduce emissions. Under such lean conditions, the ignition and complete combustion of the charge mixture is a challenge because of the reduced charge reactivity. Enhancement of the in-cylinder charge motion and turbulence to increase the flame velocity, and consequently reduce the combustion duration is one possible way to improve lean combustion. The role of air motion in better air-fuel mixing and increasing the flame velocity, by enhancing turbulence has been researched extensively. However, during the ignition process, the charge motion can influence the initial spark discharge, resulting flame kernel formation, and flame propagation.

The handling of flexible components creates a unique problem set for pick and place automation within automotive production processes. Fabrics and woven textiles are examples of flexible components used in car interiors, for air bags, as liners and in carbon-fiber layups. These textiles differ greatly in geometry, featuring complex shapes and internal slits with varying material properties such as drape characteristics, crimp resistance, friction, and fiber weave. Being inherently flexible and deformable makes these materials difficult to handle with traditional rigid grippers. Current solutions employ adhesive, needle-based, and suction strategies, yet these systems prove a higher risk of leaving residue on the material, damaging the weave, or requiring complex assemblies. Pincer-style grippers are suitable for rigid components and offer strong gripping forces, yet inadvertently may damage the fabric, and introduce wrinkles / folded-over edges during the release process.

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.

Automotive Open System Architecture (AUTOSAR) is a system-level standard that is formed by the worldwide partnership of 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 (EC) 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, and assignments of the runnables to tasks and configuration of the Basic Software (BSW) modules are performed. The EC process involves configuring every single module of the AUTOSAR.

Diesel Particulate Filters (DPF) are viable to reduce smoke from diesel engines. An oxidation process is usually required to remove the Particulate Matter (PM) loading from the DPF substrates. In cases when the engine exhaust temperature is insufficient to initiate a thermal regeneration, supplemental energy is commonly applied to raise the exhaust gas and/or the DPF substrate temperatures. A flow reversal (FR) mechanism that traps a high temperature region in the DPF substrate by periodically altering the gas flow directions has been identified to be capable of reducing the supplemental energy and thus to improve the overall thermal efficiency of the engine. However, extended operations with low exhaust temperature lowers the DPF boundary temperatures that defers the regeneration processes. Furthermore, the temperature fluctuations caused by the periodic FR operation also increase the thermal stress in the DPF.

Electric power steering (EPS) systems have been used to replace hydraulic power steering systems in vehicles. How to enhance the safety and reliability while reducing the manufacturing cost of EPS systems is still of strong interest to the automotive industry. In this paper, modeling analysis is conducted for advanced control of electric power steering system. Specifically, a mathematical model is proposed for a column-mounted EPS system and then a simplified model for control design purpose is proposed. Issues that need to be addressed, such as noise/ disturbance attenuation as well as potential fault detection/tolerance are analyzed. Simulation using CarSim™ is also presented for an optimal control design using the simplified model as an example to validate the proposed ideas.

The purpose of this study is to determine the feasibility of simulating an active suspension using cosimulation. The vehicle used is a utility truck created in ADAMS/View while the E.C.U. (electronic control unit) is implemented in Simulink for both a fully-active and semi-active controller. The LQR (Linear Quadratic Regulator) is used for the fully-active system while the semi-active system uses a switching law adopted from Karnopp et al. {1}. Nonlinear and linear vehicle models are compared and the influence of suspension bushings is examined. All simulations undertaken are geared towards evaluating the ride capabilities of such systems.

In the present study, a design of experiment (DOE) technique, the Taguchi method, was used to develop as-cast high strength aluminum alloys with element additions of Si, Cu, Ni and Sr. The Taguchi method uses a special design of orthogonal arrays to study all the designed factors with a minimum of experiments at a relatively low cost. The element factors chosen for this study were Si, Cu, Ni and Sr content in the designed aluminum-based alloys. For each factor, three different levels of weight percentages were selected (Si: 6, 9, 12%, Cu: 3, 5, 7%, Ni: 0.5, 1, 1.5% and Sr: 0.01, 0.02, 0.03%). Tensile properties such as ultimate tensile strength, yield strength and elongation at failure were selected as three individual responses to evaluate the engineering performance of the designed alloys. The results of the factor response analysis were used to derive the optimal level combinations.

To increase vehicle range, light weighting of electric vehicles has been extensively researched and implemented by using aluminum intensive solutions. With regards to traction motors, aluminum alloys that have a desired combination of high electrical conductivity and strength are required for high power output and efficiency. In this research, a novel Al-Ce based alloy, with minor additions of Si and Mg for strengthening, was investigated in different heat treatment tempers to maximize mechanical properties while maintaining a high electrical conductivity. This new alloy system appears to have addressed the classic conundrum of the inverse relationship of mechanical performance verses electrical conductivity for traditional aluminum alloy systems. The results suggest that the Al-Ce-Si-Mg alloy had yield strength in excess of 120 MPa and electrical conductivity of at least 50 %IACS in the T5 and T6 conditions.