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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.

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.

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.

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.

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.

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.

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.

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.”

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.

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.

Nitrocarburizing is an economical surface hardening process and is proposed as an alternative heat treatment method to carbonitriding. The focus of this study is to compare the size and shape distortion and residual stresses resulting from the ferritic nitrocarburizing and gas carbonitriding processes for SAE 1010 plain carbon steel. Gas, ion and vacuum nitrocarburizing processes utilizing different heat treatment temperatures and times were performed to compare the different ferritic nitrocarburizing processes. Navy C-Ring specimens and prototype stamped parts were used to evaluate size and shape distortion. X-ray diffraction techniques were used to determine the residual stresses in the specimens. Overall, the test results indicate that the nitrocarburizing process gives rise to smaller dimensional changes than carbonitriding, and that the size and shape distortion can be considerably reduced by applying appropriate ferritic nitrocarburizing procedures.

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.

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.

Automotive steering wheels depend on a structural skeleton made of steel, aluminum, or magnesium to be the basis for the mechanical properties of the finished part. The mechanical properties of concern are the fatigue properties and the crash performance. The purpose of this study was to evaluate the crash and the fatigue performance of a steering wheel skeleton fabricated by high pressure die casting. Two materials were used to produce two groups of wheels with identical geometry. The production part was designed, optimized and fabricated with AM50A magnesium. The production magnesium component met all of the regulatory design and performance requirements. A small sample run was made in a proprietary aluminum - magnesium alloy. The fatigue and crash properties were evaluated empirically. In fatigue testing, the aluminum skeletons displayed a significant improvement, with respect to the magnesium skeletons, in the number of cycles to failure at the loads tested.