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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.

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.

Lean burn or EGR diluted combustion with enhanced charge motion is effective in improving the efficiency of spark ignition engines. However, the ignition process under these conditions is getting more challenging due to higher ignition energy required by the lean or diluted mixture, as well as the interactions of the gas flow on the flame kernel. Enhanced spark discharge energy is essential to initiate the combustion under these conditions. Moreover, the discharge process should be more carefully controlled to improve the effectiveness of the spark. In this study, spark ignition systems with boosted discharge energy are used to ignite diluted air-fuel mixture under forced flow conditions. The impacts of the discharge current level, the discharge duration and the discharge current profile on the ignition are investigated in detail using optical diagnosis.

For spark ignition (SI) engines, further improvement of engine efficiency has become the major development trend, and lean burn/EGR technologies, as well as intensified in-cylinder flow, need to be adapted to reach that target. Stronger ignition sources become more favorable under extreme lean/EGR conditions. Among the ignition technologies developed, multiple ignition sites technology has been proved to be an effective way to help with the initial flame kernel development. In this paper, a spark ignited 4-cylinder turbo-charged production engine is employed to investigate the impact of multiple ignition sites technology on engine performance under lean burn conditions. Four in-house designed 3-core sparkplugs are installed on the cylinders to replace traditional stock sparkplugs, in order to generate multiple ignition sites in the cylinders.

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.

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.

Successful manufacture of Carbon Fibre Reinforced Polymers (CFRP) by Long-Fibre Reinforced Thermoplastic (LFT) processes requires knowledge of the effect of numerous processing parameters such as temperature set-points, rotational machinery speeds, and matrix melt flow rates on the resulting material properties after the final compression moulding of the charge is complete. The degree to which the mechanical properties of the resulting material depend on these processing parameters is integral to the design of materials by any process, but the case study presented here highlights the manufacture of CFRP by LFT as a specific example. The material processing trials are part of the research performed by the International Composites Research Centre (ICRC) at the Fraunhofer Project Centre (FPC) located at the University of Western Ontario in London, Ontario, Canada.

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.

Increasingly stringent emission standards have promoted the interest in alternate fuel sources. Because of the comparable energy density to the existing fossil fuels and renewable production, alcohol fuels may be a suitable replacement, or an additive to the gasoline/diesel fuels to meet the future emission standards with minimal modification to current engine geometry. In this research, the combustion characteristics of neat n-butanol are analyzed under spark ignition operation using a single cylinder SI engine. The fuel is injected into the intake manifold using a port-fuel injector. Two modes of charge dilution were used in this investigation to test the limits of stable engine operation, namely lean burn using excess fresh air and exhaust gas recirculation (EGR). The in-cylinder pressure measurement and subsequently, heat release analysis are used to investigate the combustion characteristics of the fuel under low load SI engine operation.

For internal combustion engine systems, lean and diluted combustion is an important technology applied for fuel efficiency improvement. Because of the thermodynamic boundary conditions and the presence of in-cylinder flow, the development of a well-sustained flame kernel for lean combustion is a challenging task. Reliable spark discharge with the addition of enhanced delivered energy is thus needed at certain time durations to achieve successful combustion initiation of the lean air-fuel mixture. For a conventional transistor coil ignition system, only limited amount of energy is stored in the ignition coil. Therefore, both the energy of the spark discharge and the duration of the spark discharge are bounded. To break through the energy limit of the conventional transistor coil ignition system, in this work, an adaptive spark ignition system is introduced. The system has the ability to reconstruct the conductive ion channels whenever it is interrupted during the spark discharge.

The paper describes a ‘virtual motorsports’ event developed by the University of Windsor Vehicle Dynamics and Control Research Group. The event was a competitive project-based component of a Vehicle Dynamics course offered by the University's Department of Mechanical, Automotive, & Materials Engineering. The simulated race was developed to provide fourth year automotive engineering students with design and race experience, similar to that found in Formula SAE®or SAE Baja®, but within the confines of a single academic semester. The project, named ‘Formula463’, was conducted entirely within a virtual environment, and encompassed design, testing, and racing of hi-fidelity virtual vehicle models. The efficacy of the Formula463 program to provide students with a design experience using model based simulation tools and methods has been shown over the past two years. All of the software has been released under a General Public License and is freely available on the authors website.

We are witnessing a rapid and ongoing expansion of nanoscience, driven by potential applications in advanced materials and nanotechnology. There is a race to develop techniques that may allow controlling the size, shape of nanostructures that can allow the tuning of their optical and electronic properties. Plasmonics is a field that encompasses and profits from the optical enhancement in nanostructures that support plasmon excitations. One of these new techniques is surface-enhanced Raman scattering (SERS), commonly used for nanostructure characterization. In the present report, we present a theoretical model for plasmon excitation and electric field enhancement that help to provide an explanation for the special features observed in experimental SERS. Two sets of experimental results are discussed illustrating the make out of the signature of the plasmonics producing the optical enhancement.

This research focuses on comparing the biomechanical response of the head and neck of the Hybrid III 3-year-old anthropometric test device finite element model and pediatric cadaver data, under flexion-extension bending and axial tensile loading conditions. Previous experimental research characterized the quasi-static biomechanical response of the pediatric cervical spine under flexion-extension bending and tolerance in tensile distraction loading conditions. Significant differences in rotational and linear stiffness were found between the Hybrid III model and the pediatric cadaver data. In this research the biomechanical child cadaver neck response has been implemented into the 3-year-old Hybrid III child dummy FE model. An explicit finite element code (LS-DYNA) and the modified Hybrid III model were used to numerically simulate the previous cadaver tests and validate the altered Hybrid III neck.

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.

In this work, engine tests were performed to realize EGR-enabled LTC on a single-cylinder common-rail diesel engine with three different compression ratios (17.5, 15 and 13:1). The engine performance was first investigated at 17.5:1 compression ratio to provide baseline results, against which all further testing was referenced. The intake boost and injection pressure were progressively increased to ascertain the limiting load conditions for the compression ratio. To extend the engine load range, the compression ratio was then lowered and EGR sweep tests were again carried out. The strength and homogeneity of the cylinder charge were enhanced by using intake boost up to 3 bar absolute and injection pressure up to 180 MPa. The combustion phasing was locked in a narrow crank angle window (5~10° ATDC), during all the tests.

This paper proposes and evaluates the use of a robust variable torque distribution (VTD) yaw moment control for an all wheel drive (AWD) hybrid vehicle prototype currently under development. The proposed VTD controller was used to improve the linearity of vehicle response to driver input through the modulation of front-to-rear torque distribution and a corrective torque differential between the left and right rear wheels. The development of a non-linear vehicle model and a reference model tracking sliding mode based control are discussed. The efficacy of the proposed control system was demonstrated through the use of numerical simulations using the developed non-linear vehicle model. The simulation results presented indicate the effectiveness of the proposed system and the potential restrictions to such a system including tire saturation and drivetrain component limitations.

Heat-release and cylinder pressure based adaptive fuel-injection control tests were performed on a modern common-rail diesel engine to improve the engine operation in the low-temperature combustion (LTC) region. A single shot injection strategy with heavy amount of exhaust gas recirculation (EGR) was used to modulate the in-cylinder charge conditions to achieve the low-temperature combustion. Adaptive fuel-injection techniques were used to anchor the cylinder pressure characteristics in the desired crank angle window and thereby stabilize the engine operation. The response of the adaptive control to boost, fueling, and engine speed variations was also tested. A combination of adaptive fuel-injection and automatic boost/back-pressure controls had helped to make the transient emissions comparable to the steady-state LTC emissions.

Whole field displacement/strain measurement of automotive components can be done efficiently by digital image correlation based technique. Inverse problems with this kind of input data, such as the identification of damage parameters/effective modulus in different part of a component, can be pursued by either virtual fields method or finite element model updating. In this paper, the two methods are applied to the identification of a tension plate with a circular hole, and different aspects of the two methods are discussed. It is found that the success of virtual fields method relies on the choice of a set of optimal virtual displacement fields; finite element model updating, on the other hand, can be applied to any geometry and any load condition, and can also be applied to problems where only limited number of measurements are available. However, its performance relies on the choice of optimization algorithms.

Preliminary empirical and modeling analyses are conducted to evaluate the energy efficiency of in-cylinder and external fuel injection strategies and their impact on the energy required to enable diesel particulate filter (DPF) regeneration for instance. During the tests, a thermal wave that is generated from the engine propagates along the exhaust pipe to the DPF substrate. The thermal response of the exhaust system is recorded with the thermocouple arrays embedded in the exhaust system. To implement the external fuel injection, an array of thermocouples and pressure sensors in the DPF provide the necessary feedback to the control system. The external fuel injection is dynamically adjusted based on the thermal response of the DPF substrate to improve the thermal management and to reduce the supplemental energy. This research intends to quantify the effectiveness of the supplemental energy utilization on aftertreatment enabling.