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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.

In recent years, bearing electrical failures have been a significant concern in electric cars, restricting electric engine life. This work aims to introduce a coating approach for preventing electrical erosion on 52100 alloy steel samples, the most common material used on manufacturing bearings. This paper discusses the causes of shaft voltage and bearing currents, and summarizes standard electrical bearing failure mechanisms, such as morphological damages and lubrication failures. Alumina coatings are suitable for insulating the 52100 alloy steel samples because alumina coatings provide excellent insulation, hardness, and corrosion resistance, among other characteristics. The common method to coat an insulated alumina coating on the bearing is thermal spraying, but overspray can cause environmental issues, and the coating procedures are costly and time-consuming.

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.

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.

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.

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.

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.

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.

Ultra-high strength steel (UHSS) and magnesium (Mg) alloy have found their importance in response to automotive strategy of light weighting. UHSS to be metal-formed by hot stamping usually has a hot-dipped aluminum-silicon alloy layer on its surface to prevent the high temperature scaling during the hot stamping and corrosion during applications. In this paper, a plasma electrolytic oxidation (PEO) process was used to produce ceramic oxide coatings on aluminized UHSS and Mg with intention to further improve their corrosion resistances. A potentiodynamic polarization corrosion test was employed to evaluate general corrosion properties of the individual alloys. Galvanic corrosion of the aluminized UHSS and magnesium alloy coupling with and without PEO coatings was studied by a zero resistance ammeter (ZRA) test. It was found that the heating-cooling process simulating the hot stamping would reduce anti-corrosion properties of aluminized UHSS due to the outward iron diffusion.

Automobile body panels made from advanced high strength steel (AHSS) provide high strength-to-mass ratio and thus AHSS are important for automotive light-weighting strategy. However, in order to increase their use, the significant wear damage that AHSS sheets cause to the trim dies should be reduced. The wear of dies has undesirable consequences including deterioration of trimmed parts' edges. In this research, die wear measurement techniques that consisted of white-light optical interferometry methods supported by large depth-of-field optical microscopy were developed. 1.4 mm-thick DP980-type AHSS sheets were trimmed using dies made from AISI D2 steel. A clearance of 10% of the thickness of the sheets was maintained between the upper and lower dies. The wear of the upper and lower dies was evaluated and material abrasion and chipping were identified as the main damage features at the trim edges.

Modularity in product architecture and its significance in product development have become an important product design topics in the last few decades. Several Product Modularity definitions and methodologies were developed by many researchers; however, most of the definitions and concepts have proliferated to the extent that it is difficult to apply one universal definition for modular product architecture and in product development. Automotive seat modular strategy and key factors for consideration towards modular seat design and assemblies are the main focus of this work. The primary objectives are focused on the most “natural segmentation” of the seat elements (i.e., cushions, backs, trims, plastics, head restraints, etc.) to enable the greatest ease of final assembly and greatest flexibility for scalable feature offerings around common assembly “hard-points.”

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.

Light-weighting of vehicles is one of the challenges for transportation industry due to the increasing pressure of demands in better fuel economy and environment protection. Advanced high strength steels (AHSS) are considered as prominent material of choice to realize lightweight auto body and structures at least in near term. Stamping of AHSS with conventional die materials and surface coatings, however, results in frequent die failures and undesired panel surface finish. A chromium nitride (CrN) coating with plasma nitriding case hardened layer on a die material (duplex treatment) is found to offer good wear and galling resistances. The coating failure initiates from fatigue cracking on the coating surface due to cyclic sliding frictions. In this work, cyclic inclined sliding wear test was used to imitate a stamping process for study on development of coating fatigue cracking, including crack length and spacing vs. sliding-cycles and sliding energy densities.

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.

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.

This study provides an overview of a novel method for evaluating in-vehicle speech intelligibility using the Speech Intelligibility Index (SII). The approach presented is based on a measured speech signal evaluated at the sentence Speech Reception Threshold (sSRT) in a simulated driving environment. In this context, the impact of different band importance functions in the evaluation of the SII using the Hearing in Noise Test (HINT) in a driving simulator is investigated.

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.

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.

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.