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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.

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 ever-stringent emission regulations are major challenges for the diesel fueled engines in automotive industry. The applications of advanced after-treatment technologies as well as alternative fuels [1] are considered as promising methodology to reduce exhaust emission from compression ignition (CI) engines. Using dimethyl ether (DME) as an alternative fuel has been extensively studied by many researchers and automotive manufactures since DME has demonstrated enormous potential in terms of emission reduction, such as low CO emission, and soot and sulfur free. However, the effect of employing DME in a lean NOX trap (LNT) based after-treatment system has not been fully addressed yet. In this work, investigations of the long breathing LNT system using DME as a reductant were performed on a heated after-treatment flow bench with simulated engine exhaust condition.

This study describes a zero-dimensional algorithm for tracking the intake dilution in real-time. The inputs to the model are the oxygen concentration from the exhaust oxygen sensor, the manifold air pressure and temperature (MAP/MAT), the mass air flow (MAF) and the estimated fuel injected per cycle from the engine control module. The intake manifold, the exhaust manifold and EGR system are discretized into 3 volumes and the detailed concentrations of the gas species comprising the exhaust, EGR and intake streams are tracked at each time step (on a cycle-by-cycle basis). The model does not need the EGR ratio to be known in advance and is also applicable to oxygenated fuels such as ethanol. The model response is tuned to a multi-cylinder engine and the model output is empirically validated against a wide range of engine operations including load and EGR transients.

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.

Carbon fiber sheet molding compound (SMC) is an attractive material for automotive lightweighting applications, but several issues present themselves when adapting a process developed for glass fiber composites to instead use carbon fibers. SMC is a discontinuous fiber material, so individual carbon fiber tows must be chopped into uniform rovings before being compounded with the resin matrix. Rotary chopping is one such method for producing rovings, but high wear rates are seen when cutting carbon fibers. Experiments were performed to investigate the wear progression of cutting blades during rotary carbon fiber chopping. A small rotary chopper with a polyurethane (PU) backing and thin, hardened steel blades was used to perform extended wear tests (120,000 chops, or until failure to reliably chop tows) to simulate the lifespan of blades during composite material production.

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.

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.

Electric vehicle is increasingly becoming popular and an alternative choice for the consumers because of its environment-friendly operation. Permanent magnet synchronous machines are widely and commonly used as traction motors since they provide higher torque and power density. High torque and power density mean higher current which eventually causes higher temperature rise in the motor. Higher temperature rise directly affects the motor output. Standard tests for UDDS (Urban Dynamometer Driving Schedule) and HWFET (Highway Fuel Economy Driving Schedule) drive cycles are used to determine performance of traction motors in terms of torque, power, efficiency and thermal health. Traction motors require high torque at low speed for starting and climbing; high power at high speed for cruising; wide speed range; a fast torque response; high efficiency over wide torque and speed ranges and high reliability.

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.

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.

Fatigue analysis incorporating explicit finite element simulation was conducted on a forged magnesium wheel model where a rotating bend moment was applied to the hub to simulate rotary fatigue testing. Based on wheel fatigue design criteria and a developed fatigue post-processor, the safety factor of fatigue failure was calculated for each finite element. Fatigue failure was verified through experimental testing. Design modifications were proposed by increasing the spoke thickness. Further numerical and experimental testing indicated that the modified design passed the rotary fatigue test.

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.

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.

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.

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.

Empirical work has been conducted with an EGR fuel reformer configured in a flow reversal and central fueling embedment to improve the fuel dispersion quality and the reforming energy efficiency. Comprehensive comparison analyses are made between the unidirectional flow and the periodic reversal flow embodiments of similar substrate size and properties; and between the inlet and central heating schemes. With a unidirectional EGR reformer, a large amount of supplemental heating is commonly required prior to reforming. The central-fueling and flow-reversal embedment in this study is shown to significantly reduce the supplemental heating energy. The EGR cooler loading for the two strategies is also analyzed. One-dimensional modeling analyses are conducted to evaluate the fuel delivery strategies and temperature profiles of the reformer at various reforming gas flow rates and engine-out exhaust temperatures and compositions.