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Conventional axially loaded energy absorbers dissipate kinetic energy through progressive folding. The significant fluctuations in load and high risk of transition to global bending are drawbacks that engineers have attempted to mitigate through several methods. A novel energy dissipation mechanism, referred to as axial cutting, utilizes thin-walled extrusions and a strengthened cutting tool to absorb energy in an axial impact. Compared to progressive folding, this can be achieved with minimal fluctuations in load during the deformation process. Based upon estimates from finite element models, a series of test cases were postulated where, for 8 and 10-bladed cutting scenarios, greater total energy absorption could be achieved through axial cutting than with progressive folding of geometrically similar extrusions. The specimens were AA6061 extrusions having T6 temper conditions that possessed 63.5 mm outer diameters and 1.5 mm wall thicknesses.

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.

Due to high torque and power density, permanent magnet synchronous motor (PMSM) has become the most viable candidate for electric vehicle (EV) traction application. However, to obtain such high torque and power density within a compact motor structure can cause a significant temperature rise within the motor while operating. As a result of high temperature rise, permanent magnet demagnetization may even occur within the motor. Thus, PMSM is susceptible to thermal instability. Therefore, to ensure thermal stability during varying operating conditions, thermal analysis is a mandatory procedure in addition to electromagnetic analysis during the design phase of the motor. In this paper, a computationally efficient numerical finite element analysis (FEA) process has been proposed for thermal analysis of PMSM.

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.

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.

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.

End-of-life is the least studied phase of the vehicle life-cycle. Dismantling and shredding are the principal processes used for vehicle end-of-life (VEOL) management in Canada and the U.S. and are typically perceived as distinct processes, each one having its own unique challenges. Dismantling typically precedes shredding, with vehicle parts and materials removed for direct reuse, for remanufacturing and reuse, or for recycling. Dismantling may be perceived as a non-preferred alternative, compared to shredding, because it is principally a manual process which can be cost prohibitive in the North America/western labour market. However, there has been no exhaustive assessment of the dismantling process. Because of the complexity in automobiles, significantly more needs to be known about dismantling, its benefits and impacts, its efficiencies and inefficiencies, and its relation to other ELV management processes.

The paper describes a closed-loop vehicle simulation environment developed to support a virtual vehicle design and testing methodology, proposed for the University of Windsor Formula SAE team. Virtual prototyping and testing were achieved through co-simulation of Matlab/Simulink® and Carsim®. The development of the required hybrid-control driver and vehicle models are described. The proposed models were validated with in vehicle test data. The proposed methods have shown to be effective and robust in predicting driver response, while controlling the vehicle within the developed simulation environment.

A Mg-5.0wt.%Al-2.0wt.%Ca alloy (AC52) was cast at different cooling rates varying from 0.5 to 65 °C/s. The dendrites was characterized by determining the secondary dendrite arm spacing (SDAS) and the volume fraction of secondary eutectic phases with the linear intercept and point counting methods, respectively. The SDAS decreases significantly with increasing cooling rates, while the volume fraction of the eutectic phase increases from 10.8 ± 1.44 vol.% at 0.5 °C/s to 20.4 ± 1.52 vol.% at 20 °C/s. However, a further increase in cooling rate beyond 20 °C/s has limited influence on the volume fraction of eutectic phases. A large number of dispersed eutectic phases were observed in the primary α-Mg of the alloys cast at low cooling rates. Although, at the microscale, there were no dispersed eutectic phases in alloys cast at a high cooling rate of 30 °C/s, nanoscale eutectic phases were found by TEM observation.

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.

Performance of the ignition system becomes more important than ever, because of the extensively used EGR in modern spark-ignition engines. Future lean burn SI and SACI combustion modes demand even stronger ignition capability for robust ignition control. For spark-based ignition systems, extensive research has been carried out to investigate the discharge characteristics of the ignition process, including discharge current amplitude, discharge duration, spark energy, and plasma stretching. The correlation between the spark stretch and the discharge energy, as well as the impact of discharge current level on this correlation, are important with respect to both ignition performance, and ignition system design. In this paper, a constant volume combustion chamber is applied to study the impact of plasma stretch on the spark energy release process with cross-flow speed from 0 m/s up to 70 m/s.

Advanced ignition systems with enhanced discharge current have been extensively investigated in research, since they are highly regarded as having the potential to overcome challenges that arise when spark-ignition engines are running under lean or EGR diluted conditions. Local flow field is also of particular importance to improve the ignitability of the air-fuel mixture in SI engines as the spark plasma channel can be stretched by the flow across the spark gap, leading to longer plasma length, thus more thermal spark energy distributed to the air-fuel mixture in the vicinity of the spark plug. Research results have shown that a constantly high discharge current is effective to maintain a stable spark plasma channel with less restrikes and longer plasma holding period.

Neural networks are flexible modeling tools that can be used in conjunction with multi-body dynamics models to better predict nonlinear behaviour of components. This paper focuses on a process that incorporates a neural network model of a nonlinear damping force into a single degree of freedom mass-spring-damper model. Software tools and their interaction are specified. The verification of this process is the focal point of this paper and is a necessary step before further correlation studies can be performed on more complex component representations.

Fiber composite materials are widely used in many industrial applications - specially in automotive, aviation and consumer goods. Introducing light-weighting material solutions to reduce vehicle mass is driving innovative materials research activities as polymer composites offer high specific stiffness and strength compared to contemporary engineering materials. However, there are issues related to high production volume, automation strategies and handling methods. The state of the art for the production of these light-weight flexible textile or composite fiber products is setting up multi-stage manual operations for hand layups. Material handling of flexible textile/fiber components is a process bottleneck. Consequently, the long term research goal is to develop semi-automated pick and place processes for flexible materials utilizing collaborative robots within the process. Collaborative robots allow for interactive human-machine tasks to be conducted.

Laser cladding is a novel process of surface coating, and researchers in both academia and industry are developing additive manufacturing solutions for large, metallic components. There are many interlinked process parameters associated with laser cladding, which may have an impact on the resultant microhardness profile throughout the bead zone. A set of single bead laser cladding experiments were done using a 4 kW fiber laser coupled with a 6-axis robotic arm for 420 martensitic stainless steel powder. A design of experiments approach was taken to explore a wide range of process parameter settings. The goal of this research is to determine whether robust predictive models for hardness can be developed, and if there are predictive trends that can be employed to optimize the process settings for a given set of process parameters and microhardness requirements.

Gantry robots are mainly employed for applications requiring large workspace, with limited higher manipulability in one direction than the others. The Gantries offer very good mechanical stiffness and constant positioning accuracy, but low dexterity. Common gantries are CNC machines with three translational joints XYZ (3DOF) and usually with an attached wrist (+3DOF). The translational joints are used to move the tool in any position in the 3D workspace. The wrist is used to orient the tool by rotation about X, Y and Z axis. This standard kinematic structure (3T3R) produces a rectangular workspace. In this paper a full kinematic model for a 6DOF general CNC (gantry) machine is presented, along with the Jacobian matrix and singularity analysis. Using Denavit-Hartenberg convention, firstly, the general kinematic structure is presented, in order to assign frames at each link. The forward kinematic problem is solved using Maple 17 software.