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Alumina (Al2O3) thin film coatings are applied on Al alloys using Plasma Electrolytic Oxidation (PEO) method to reduce the wear and corrosion problems. Plasma Electrolytic Aluminating (PEA) is a technique which could generate Alumina coatings on cast iron, mild steel and copper alloys. In this study, the aim is to explore the anti-wear and anti-corrosion behaviours of PEA Alumina coatings on gray cast iron. The dry sliding tribology test data was obtained from Pin-on-Disk (POD) tests against SAE 52100 steel and Tungsten Carbide (WC) counterfaces. Comparing with the PEO Alumina coatings, the PEA Alumina coating has much lower Coefficient of Friction (COF) and less wear. The microstructure, chemical composition and phase composition of this coating were investigated with Scanning Electron Microscope (SEM), Energy-Dispersive X-Ray Spectroscopy (EDX) and X-Ray Diffraction (XRD), respectively. There was FeO (or FeAl2O4) found on the PEA Alumina coating.

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.

Ignition performance is critical for the implementation of diluted combustion for spark-ignition engines. The short circuit and restrike phenomena can influence the initial ignition volume and discharge duration which are important for the stable ignition processes. In this study, the short circuits and restrikes of spark channels are studied with various flow velocities, spark plug gaps and discharge energies. The development of the spark channels is captured by using the direct imaging technique with a CMOS camera equipped with an image intensifier. A multi-coil ignition system is designed to enable flexible control of discharge energies. The results show that the spark plug gap size is a critical parameter to suppress the phenomena of short circuits and restrikes. With the enlargement of spark plug gap, the maximum and average lengths of the spark channel effectively increase.

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.

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 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 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.

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.

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.

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.

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.

Following the development of new technologies in Vehicle Thermal Management aiming to both enhancing the MAC System efficiency and reducing the thermal load to be managed, a prediction tool based on the AMEsim platform was developed at Advanced PD EMEA. This tool is dedicated to predict the effect of the implementation of sensors monitoring both the relative humidity and the carbon dioxide (CO2) concentration (taking into account passengers' generated moisture and CO2). This model implemented with the usual comfort inputs (CO2 and RH acceptable ranges) considers the system variables influencing the comfort and predicts the increase of both RH and CO2 concentration in the cabin compartment in any driving cycle depending on the number of occupants.

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.

Industrial robotic arms and manipulators are systems that offer technological advances in automation, production, and logistical processes. Therefore, it is vital to understand and analyze the reachability and dexterity of such manipulators. This paper presents a reconfigurable algorithm for evaluation and 3D visual representation of the total workspace and singularity space of two and three degrees of freedom open-ended kinematic chains. A manipulator's performance is greatly depreciated at or near singular regions which may occur as subset(s) in its complete workspace. It is therefore crucial to understand the functional workspace of a manipulator for an enhanced performance in an industrial setting. The implementation of this algorithm requires two inputs namely; the joint type(s), rotational (R) or translational (T), and the Denavit-Hartenberg (D-H) parameters of the manipulator.

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.

Individuals with hearing impairments often report hearing difficulties within the driving environment. This is an ever growing issue given the increasing population of senior aged drivers. In this study, Speech Intelligibility Index (SII) is used to predict in-vehicle speech intelligibility of individuals having common hearing impairments. The effect of hearing threshold levels obtained from audiograms and the impact of vehicle background noise measured for various vehicle operating conditions, road surface types and talker and listener configurations are investigated. This is done by using measured and user-defined speech spectra as described by ANSI S3.5-1997 (Methods for Calculation of the Speech Intelligibility Index). The results demonstrate poor speech intelligibility for most situations considered and provide evidence for the need to improve automotive interior sound quality in terms of speech intelligibility for hearing impaired drivers including aged drivers.

Though the purpose of a vehicle's suspension is multi-faceted and complex, the fundamentals may be simply stated: the suspension exists to provide the occupants with a tolerable ride, while simultaneously ensuring that the tires maintain good contact with the ground. At the root of the familiar ride/handling compromise, is the problem that tuning efforts which improve either grip or handling are generally to the detriment of the other. This study seeks to set forth a clear means for examining the familiar ride/handing compromise, by first exploring the key ideas of these terms, and then by describing the development of content-rich metrics to permit a direct optimization strategy. For simplicity, the optimization problem was examined in a unilateral manner, where heave (vertical; z-axis) behaviour is examined in isolation, though the methods described herein may be extended to pitch and roll behaviour as well.

This research focuses on the further development of a child finite element model whereby implementation of pediatric cadaver testing observations considering the biomechanical response of the neck of children under tensile and bending loading has occurred. Prior to this investigation, the biomechanical neck response was based upon scaled adult cadaver behaviour. Alterations to the material properties associated with ligaments, intervertebral discs and facet joints of the pediatric cervical spine were considered. No alteration to the geometry of the child neck finite element model was considered. An energy based approach was utilized to provide indication on the appropriate changes to local neck biomechanical characteristics. Prior to this study, the biomechanical response of the neck of the child finite element model deviated significantly from the tensile and bending cadaver tests completed by Ouyang et al.

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 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.