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Compression ignition internal combustion engines provide unmatched power density levels, making them suitable for numerous applications including heavy-duty freight trucks, marine shipping, and off-road construction vehicles. Fossil-derived diesel fuel has dominated the energy source for CI engines over the last century. To mitigate the dependency on fossil fuels and lessen anthropogenic carbon released into the atmosphere within the transportation sector, it is critical to establish a fuel source which is produced from renewable energy sources, all the while matching the high-power density demands of various applications. Dimethyl ether (DME) has been used in non-combustion applications for several decades and is an attractive fuel for CI engines because of its high reactivity, superior volatility to diesel, and low soot tendency. A range of feedstock sources can produce DME via the catalysis of syngas.

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.

In recent years, bearing electrical failures have been a significant concern in electric cars, restricting electric engine life. This work aims to introduce a coating approach for preventing electrical erosion on 52100 alloy steel samples, the most common material used on manufacturing bearings. This paper discusses the causes of shaft voltage and bearing currents, and summarizes standard electrical bearing failure mechanisms, such as morphological damages and lubrication failures. Alumina coatings are suitable for insulating the 52100 alloy steel samples because alumina coatings provide excellent insulation, hardness, and corrosion resistance, among other characteristics. The common method to coat an insulated alumina coating on the bearing is thermal spraying, but overspray can cause environmental issues, and the coating procedures are costly and time-consuming.

Major original equipment manufacturers (OEMs) have already marketed electric vehicles in large scale but apart from business strategies and policies, the real engineering problems must be addressed. Lithium-ion batteries are a promising technology for energy storage; however, their low energy density and complex electro-chemical nature, compared to fossil fuels, presents additional challenges. Their complex nature and strong temperature dependence during operation must be studied with additional accuracy, capable to predict their behavior. In this research, a pseudo two dimensional (P2D) electro-chemical model, for a recent high capacity NMC pouch cell for automotive applications is developed. The electrochemical model with its temperature dependent parameters is validated at high, low, and reference temperature within 10°C to 50°C temperature range. For each temperature various discharge C-rates to accurately replicate the battery cell operational conditions.

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.

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.

Due to high torque and power density, permanent magnet synchronous motor (PMSM) has become the most viable candidate for electric vehicle (EV) traction application. However, to obtain such high torque and power density within a compact motor structure can cause a significant temperature rise within the motor while operating. As a result of high temperature rise, permanent magnet demagnetization may even occur within the motor. Thus, PMSM is susceptible to thermal instability. Therefore, to ensure thermal stability during varying operating conditions, thermal analysis is a mandatory procedure in addition to electromagnetic analysis during the design phase of the motor. In this paper, a computationally efficient numerical finite element analysis (FEA) process has been proposed for thermal analysis of PMSM.

Fiber composite materials are widely used in many industrial applications - specially in automotive, aviation and consumer goods. Introducing light-weighting material solutions to reduce vehicle mass is driving innovative materials research activities as polymer composites offer high specific stiffness and strength compared to contemporary engineering materials. However, there are issues related to high production volume, automation strategies and handling methods. The state of the art for the production of these light-weight flexible textile or composite fiber products is setting up multi-stage manual operations for hand layups. Material handling of flexible textile/fiber components is a process bottleneck. Consequently, the long term research goal is to develop semi-automated pick and place processes for flexible materials utilizing collaborative robots within the process. Collaborative robots allow for interactive human-machine tasks to be conducted.

Thermal comfort in automotive seating has been studied and discussed for a long time. The available research, because it is focused on the components, has not produced a model that provides insight into the human-seat system interaction. This work, which represents the beginning of an extensive research program, aims to establish the foundation for such a model. This paper will discuss the key physiological, psychological, and biomechanical factors related to perceptions of thermal comfort in automotive seats. The methodology to establish perceived thermal comfort requirements will also be presented and discussed.

A three-pole spark igniter, with the concept to broaden the ignition area, is employed in this paper to investigate the effect of spark discharge strategies on the early ignition burning process. The prototyped three-pole igniter has three independent spark gaps arranged in a triangular pattern with a circumradius of 2.3 mm. Direct-capacitor discharge techniques, utilizing close-coupled capacitors parallel to the spark gap, are applied on the three-pole igniter to enhance either the transient spark power or the overall energy. In particular, the simultaneous discharge of high energy plasma on three spark gaps can produce a surface-like ignition process which intensifies the plasma-flame interaction, thereby producing a rapid flame kernel development. The ignition strategies are evaluated in both constant volume combustion vessels and a modified single-cylinder metal engine.

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.

The development of a collision severity model can serve as an important tool in understanding the requirements for devising countermeasures to improve occupant safety and traffic safety. Collision type, weather conditions, and driver intoxication are some of the factors that may influence motor vehicle collisions. The objective of this study is to use artificial neural networks (ANNs) to identify the major determinants or contributors to fatal collisions based on various driver, vehicle, and environment characteristics obtained from collision data from Transport Canada. The developed model will have the capability to predict similar collision outcomes based on the variables analyzed in this study. A multilayer perceptron (MLP) neural network model with feed-forward back-propagation architecture is used to develop a generalized model for predicting collision severity. The model output, collision severity, is divided into three categories - fatal, injury, and property damage only.

Environmental concerns and rising fuel costs are driving Ontario's municipalities and fleet operators to consider alternative vehicle technologies. Elevated fuel consumption and air emissions are attributed to the unique operations of fleet vehicles and in particular, during idling. While drivers of passenger vehicles may have the option of simply not idling, fleet and emergency vehicle operators, may need to keep the vehicle operating to supply power to critical onboard equipment. These demands may be exacerbated during seasonal, temperature extremes. However, prolonged idling can impose significant environmental and economic burdens. Hybrid vehicles have yet to be utilized widely by Ontario's fleets, but there are other approaches to reduce emissions, including alternative “green” technologies to operate in-vehicle equipment and maintain fleet vehicle capabilities instead of idling.

In this study the capabilities of a semi-active suspension and an active roll suspension are evaluated for comparison with a passive suspension. The vehicle used is a utility truck modeled as a multi-body system in ADAMS/Car while the ECU (electronic control unit) is built in Matlab/Simulink. Cosimulation is used in linking the vehicle model with the controller by exchanging the input and output values of each sub-system with one another. For the simulation models considered, results indicate that for a fish-hook cornering maneuver the semi-active suspension is limited in increasing vehicle performance while the active roll suspension significantly improves it. Further analysis is needed to confirm these findings.

The implementation of fuel cell-battery hybrid vehicles requires a supervisory control strategy that manages the power distribution between the fuel cell and the energy storage device (i.e., battery). Several advanced control methods have already been developed and published in literature. However, most control methods have been developed for different vehicle types and using different mathematical models. The performance of these power management methods have not been directly compared for the same application. This study aims at obtaining direct analytical comparisons, which will provide useful insight in selecting a power management method for fuel cell-battery hybrid vehicles.

Though the purpose of a vehicle's suspension is multi-faceted and complex, the fundamentals may be simply stated: the suspension exists to provide the occupants with a tolerable ride, while simultaneously ensuring that the tires maintain good contact with the ground. At the root of the familiar ride/handling compromise, is the problem that tuning efforts which improve either grip or handling are generally to the detriment of the other. This study seeks to set forth a clear means for examining the familiar ride/handing compromise, by first exploring the key ideas of these terms, and then by describing the development of content-rich metrics to permit a direct optimization strategy. For simplicity, the optimization problem was examined in a unilateral manner, where heave (vertical; z-axis) behaviour is examined in isolation, though the methods described herein may be extended to pitch and roll behaviour as well.

This research focuses on the further development of a child finite element model whereby implementation of pediatric cadaver testing observations considering the biomechanical response of the neck of children under tensile and bending loading has occurred. Prior to this investigation, the biomechanical neck response was based upon scaled adult cadaver behaviour. Alterations to the material properties associated with ligaments, intervertebral discs and facet joints of the pediatric cervical spine were considered. No alteration to the geometry of the child neck finite element model was considered. An energy based approach was utilized to provide indication on the appropriate changes to local neck biomechanical characteristics. Prior to this study, the biomechanical response of the neck of the child finite element model deviated significantly from the tensile and bending cadaver tests completed by Ouyang et al.

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.

This research focuses on the response of the Q3, Hybrid III 3-year-old dummy and a child finite element model in a simulated 213 sled test. The Q3 and Hybrid III 3-year old child finite element models were developed by First Technology Safety Systems. The 3-year-old child finite element model was developed by Nagoya University by model-based scaling from the AM50 (50 percentile male) total human model for safety. The child models were positioned in a forward facing, five-point child restraint system using Finite Element Model Builder. An acceleration pulse acquired from an experimental 213 sled test, which was completed following the guidelines outlined in the Federal Motor Vehicle Safety Standard 213 using a Hybrid III 3-year-old dummy, was applied to the seat buck supporting the child restraint seat. The numerical simulations utilizing the Q3, Hybrid III 3-year-old and the child finite element model were conducted using the explicit non-linear finite element code LS-DYNA.

Rollover crash is one of the most serious safety problems for light weight vehicles. In the USA, rollover crashes account for almost one-third of all occupant fatalities in light weight vehicles. Similar statistics are found for other countries. Thus, rollover crashes have received significant attention in recent years. In the USA and Canada, automotive manufacturers are required to comply with the roof strength requirement of “1.5 times the unloaded vehicle weight” to ensure safety in rollover. NHTSA is currently considering a set of countermeasures to improve the rollover safety, where one of the proposals is to increase the roof strength limit to “2.5 times the unloaded vehicle weight”. This increased roof strength limit seemingly has been motivated based on the benchmark study of current vehicle fleet.