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Polyurethane (PU) foam is used for many automotive applications with the benefits of being lightweight, durable, and resistant to heat and noise. Applications of PU foams are increasing to include non-traditional purposes targeting consumer comfort. An example of this is the use of PU foam between the engine and engine cover of a vehicle for the purpose of noise abatement. This addition will provide a quieter ride for the consumer, however will have associated environmental impacts. The additional weight will cause an increase in fuel consumption and related emissions. More significant impacts may be realized at the end-of-life stage. Recycling PU foams presents several challenges; a lack of market for the recyclate, contamination of the foams, and lack of accessibility for removal of the material.

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 paper describes the application of the Fourier Amplitude Sensitivity Test (FAST) method [1] to investigate the effect of uncertainty in design parameters on the thermal system performance of vehicle underbody components. The results from this study will pinpoint the design parameters which offer the greatest opportunity for improvement of thermal system performance and reliability. In turn, this method can save engineering time and resources. An analytical model was developed for a vehicle underbody system consisting of a muffler, heat shield, and spare tire tub. The output from this model was defined as the temperature of the spare tire tub. The majority of the input parameters in this model deviate from their nominal values due to environmental factors, wear and ageing, and/or variation in the manufacturing process.

The increased availability of natural gas (NG) in the U.S. has renewed interest in the application to heavy-duty (HD) diesel engines in order to realize fuel cost savings and reduce pollutant emissions, while increasing fuel economy. Reactivity controlled compression ignition (RCCI) combustion employs two fuels with a large difference in auto-ignition properties to generate a spatial gradient of fuel-air mixtures and reactivity. Typically, a high octane fuel is premixed by means of port-injection, followed by direct injection of a high cetane fuel late in the compression stroke. Previous work by the authors has shown that NG and diesel RCCI offers improved fuel efficiency and lower oxides of nitrogen (NOx) and soot emissions when compared to conventional diesel diffusion combustion. The work concluded that NG and diesel RCCI engines are load limited by high rates of pressure rise (RoPR) (>15 bar/deg) and high peak cylinder pressure (PCP) (>200 bar).

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.

Advanced combustion engines dominate all automotive applications. Future high efficiency clean combustion engines can contribute significantly to sustainable transportation. Effective ignition strategies are studied to enable lean and diluted combustion under considerably high-density mixture and strong turbulences, for improving the efficiency and emissions of future combustion engines. Continuous discharge and multi-site ignition strategies have been proved to be effective to stabilize the combustion process under lean and EGR diluted conditions. Continuous discharge strategy uses a traditional sparkplug with a single spark gap and multiple ignition coil packs. The ignition coil packs operate under a specific time offset to realize a continuous discharge process with a prolonged discharge duration. Multi-site ignition strategy also uses multiple ignition coil packs.

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.

Empirical results indicated that the engine emission and fuel efficiency of low-temperature combustion (LTC) cycles can be optimized by adjusting the fuel-injection scheduling in order to obtain appropriate combustion energy release or heat-release rate patterns. Based on these empirical results the heat-release characteristics were correlated with the regulated emissions such as soot, hydrocarbon and oxides of nitrogen. The transition from conventional combustion to LTC with the desired set of heat-release rate has been implemented. This transition was facilitated with the simplified heat-release characterization wherein each of the consecutive engine cycles was analyzed with a real-time controller embedded with an FPGA (field programmable gate array) device. The analyzed results served as the primary feedback control signals to adjust fuel injection scheduling. The experimental efforts included the boost/backpressure, exhaust gas recirculation, and load transients in the LTC region.

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.

Simultaneous low NOx (< 0.15 g/kWh) & soot (< 0.01 g/kWh) are attainable for enhanced premixed combustion that may lead to higher levels of hydrocarbons and carbon monoxide emissions as the engine cycles move to low temperature combustion, which is a departure from the ultra low hydrocarbon and carbon monoxide emissions, typical of the high compression ratio diesel engines. As a result, the fuel efficiency of such modes of combustion is also compromised (up to 5%). In this paper, advanced strategies for fuel injection are devised on a modern 4-cylinder common rail diesel engine modified for single cylinder research. Thermal efficiency comparisons are made between the low temperature combustion and the conventional diesel cycles. The fuel injection strategies include single injection with heavy EGR, and early multi-pulse fuel injection under low or medium engine loads respectively.

Extensive empirical work indicates that the exhaust emission and fuel efficiency of modern common-rail diesel engines characterise strong resilience to biodiesel fuels when the engines are operating in conventional high temperature combustion cycles. However, as the engine cycles approach the low temperature combustion (LTC) mode, which could be implemented by the heavy use of exhaust gas recirculation (EGR) or the homogeneous charge compression ignition (HCCI) type of combustion, the engine performance start to differ between the use of conventional and biodiesel fuels. Therefore, a set of fuel injection strategies were compared empirically under independently controlled EGR, intake boost, and exhaust backpressure in order to improve the neat biodiesel engine cycles.

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.

In this study, a procedure for characterizing advanced high strength steel sheets is presented in view of determining the material parameters for constitutive models that can be used for accurate prediction of springback and sidewall curl. The mechanical properties of DP980 and TRIP780 sheets were obtained experimentally, and their cyclic tension-compression behaviour was modeled with the Chaboche nonlinear kinematic hardening model and the Yoshida-Uemori two-surface plasticity model that are implemented in LS-DYNA. The unloading moduli were determined from monotonic tension tests at various prestrain levels. An inverse approach based on linear and quadratic response surfaces created by Sequential Strategy with Domain Reduction (SRSM) methodology using LS-OPT software was used and investigated to identify specific material parameters in each constitutive model.