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Dimensional variation simulation is a computer aided engineering (CAE) method that analyzes the statistical efforts of the component variation to the quality of the final assembly. The traditional tolerance analysis method and commercial CAE software are often based on the assumptions of the rigid part assembly. However, the vehicle functional attributes, such as, ride and handling, NVH, durability and reliability, require understanding the assembly quality under various dynamic conditions while achieving vehicle dimensional clearance targets. This paper presents the methods in evaluating and analyzing the impacts of the assembly variations for the vehicle dynamic performance. Basic linear tolerance stack method and advanced study that applies various CAE tools for the virtual quality analysis in the product and process design will be discussed.

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.

A snap-fit is a form-fitting joint, which is used to assemble plastic parts together. Snap-fits are available in different forms like a projecting clip, thicker section or legs in one part, and it is assembled to another part through holes, undercuts or recesses. The main function of the snap-fit is to hold the mating components, and it should withstand the vibration and durability loads. Snap-fits are easy to assemble, and should not fail during the assembling process. Based on the design, these joints may be separable or non-separable. The non- separable joints will withstand the loads till failure, while separable joints will withstand only for the design load. The insertion and the retention force calculation for the snaps are very essential for snap-fit design. The finite element analysis plays a very important role in finding the insertion and the retention force values, and also to predict the failure of the snaps and the mating components during this process.

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.

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.

The SAE Fuel Cell Vehicle (FCV) Safety Working Group has been addressing FCV safety for over 9 years. The initial document, SAE J2578, was published in 2002. SAE J2578 has been valuable as a Recommended Practice for FCV development with regard to the identification of hazards and the definition of countermeasures to mitigate these hazards such that FCVs can be operated in the same manner as conventional gasoline internal combustion engine (ICE)-powered vehicles. SAE J2578 is currently being revised so that it will continue to be relevant as FCV development moves forward. For example, test methods were refined to verify the acceptability of hydrogen discharges when parking in residential garages and commercial structures and after crash tests prescribed by government regulation, and electrical requirements were updated to reflect the complexities of modern electrical circuits which interconnect both AC and DC circuits to improve efficiency and reduce cost.

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.

SAE 8620 and other steels are typically used in the carburized condition for powertrain applications in the automotive industry, i.e., differential ring gears, camshafts, and transmission gears. Although current recommended carburizing practice involves normalizing the steel prior to carburizing, elimination of this normalizing treatment could lead to significant cost reductions. This research examines whether the normalizing process prior to carburizing could be eliminated without negatively affecting part performance. This study focused on the effects of the initial microstructure on the residual stress, retained austenite, and effective case depths of carburized SAE 8620 and PS-18 steels.

The focus of this study was to determine the residual stress and retained austenite profiles for carbonitrided and nitrocarburized SAE 1010 plain carbon steel and to relate these profiles to one another and to the distortion resulting from heat treatment. Navy C-ring specimens were used for the purpose of this study and X-ray diffraction techniques were used to measure both residual stress and retained austenite. The findings from this research are then applied to a manufacturing application involving the surface hardening of a thin shelled, plain carbon steel automotive component.

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.

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors.

Springback compensation studies on a few selected auto panels from the hot selling Chrysler 300C are presented with details. LS-DYNA® is used to predict the springback behavior and to perform the iterative compensation optimization. Details of simulation parameters using LS-DYNA® to improve the prediction accuracy are discussed. An iterative compensation algorithm is also discussed with details. Four compensation examples with simulation predictions and actual panel measurement results are included to demonstrate the effectiveness of LS-DYNA® predictions. An aluminum hood inner and a high strength steel roof bow are compensated, constructed and machined based on simulation predictions. The measurements on actual tryout panels are then compared with simulation predictions and good correlations were achieved. Iterative compensation studies are also done on the aluminum hood inner and the aluminum deck lid inner to demonstrate the effectiveness of LS-DYNA® compensation algorithm.

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.

A D.C. permanent magnet motor powered fan can serve as a cooling package air flow meter. This allows for continuous air flow monitoring during vehicle operation with applications to more precise air flow control schemes. In the freewheel mode, the air flow is a linear function of the open circuit voltage of the motor. In the powered mode, the motor voltage and current can be used with a motor and fan model to predict fan air flow. The model is explained and verifying test results are presented. Comparison of the accuracy and complexity vs. that of arrays of precision anemometers is provided.

Spot Welding is an important welding technique which is widely used in automotive and aerospace industry. One of the keys of checking the quality of the welds is measuring the size of the nugget. In this paper, the Shearographic technique is utilized to test weld joint samples under the thermal loading condition. The goal is to identify the different group of the nuggets (i.e. small, middle, and large sizes, which indicate the quality of spot welds). In the experiments, the sample under test is fixed by a magnet method from behind at the four edges. Thermal loading was applied in the back side and the sample is inspected using the digital Shearographic system in the front side. Results show the great possibility of classifying the nugget size into three groups and the measurement is well repeatable.