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Vehicles are in contact with the road surface through tires, and the interaction at the tire-road interface is usually the major source of vibrations that is experienced by the passengers in the vehicle. Thus, it is critical to measure the vibrational characteristics of the tires in order to improve the safety and comfort of the passengers and also to make the vehicle quieter. The measurement results can also be used to validate numerical models. In this paper, Digital Image Correlation (DIC) as a non-contact technique is used to measure the dynamics of a racing tire in static and rolling conditions. The Kettering University FSAE car is placed on the dynamometer machine for this experiment. A pair of high-speed cameras is used to capture high-resolution images of the tire in a close-up view. The images are processed using DIC to obtain strain and displacement of the sidewall of the tire during rolling. The experiment is performed for various testing speeds.

The torsional natural frequencies of axles equipped with limited slip differential clutches depend on whether or not the tires and clutches are slipping since the effective inertia at each end of the axle is different for slipping and non-slipping conditions. Limited slip axle vibrations are typically analyzed for one tire slipping and the other not since that is the case for which the limited slip clutches are used. Vibrations often arise, however, during normal turning when both drive tires have good traction.

In automotive assembly facilities worldwide, many critical vehicle systems such as brakes, power steering, radiator, and air conditioning require the appropriate fluid to function. In order to insure that these critical vehicle systems receive the correct amount of properly treated fluid, automotive manufacturers employ a method called Evacuation and Fill. Due to their closed-loop design, many critical vehicle systems must be first exposed to vacuum prior to being flooded with fluid. Only after the evacuation and fill process is complete will the critical vehicle system be able to perform as specified. It has long been thought, but never proven, that humidity and entrenched fluid were major hindrances to the Evacuation and Fill process. Consequently, Ford Motor Company Advanced Manufacturing Technology Development, Sandalwood Enterprises, Kettering University, and Dominion Tool & Die conducted a detailed project on this subject.

Kettering University's Clean Snowmobile Challenge student design team has developed a new robust and innovative snowmobile for the 2004 competition. Switching from the previous years four-stroke automotive engine, Kettering University has utilized a modified snowmobile in-line four cylinder, four-stroke, fuel- injected engine. This engine has been installed into a 2003 Yamaha RX-1 snowmobile chassis. Exhaust emissions have been minimized through the use of a customized catalytic converter and an electronically controlled closed-loop fuel injection system. A newly designed and tuned exhaust as well as several chassis treatments have aided in minimizing noise emissions.

A Task and Message Schedule for a FlexCAN-based Hybrid-Electric vehicle (HEV) functional unit is described. The resulting schedule is a component of an incremental message and task scheduling approach based on a time-driven message schedule and priority-driven task schedule. The HEV functional unit involves the combined control and monitoring functions of an internal combustion engine working in parallel with a permanent magnet synchronous motor. The control algorithm for the synchronous motor has been simulated using VHDL-AMS. The global message system is supported by FlexCAN and the task scheduler system is supported by a priority based OS (e.g., OSEK or AUTOSAR).

Modeling and simulation of dynamic systems is not always a simple task. In this paper, the mathematical model of a 4 Degree Of Freedom (DOF) ride model is presented using a bond-graph technique with state energy variables. We believe that for the physical model as described in this research, the use of a bond-graph approach is the only feasible solution. Any attempt to use classical methods such as Lagrange equations or Newton's second law, will create tremendous difficulties in the transformation of a set of second order linear differential equations to a set of first order differential equations without violating the existence and the uniqueness of the solution of the differential equations, the only approach is the elimination of the damping of the tires, which makes the model unrealistic. The bond-graph model is transformed to a mathematical model. Matlab is used for writing a computer script that solves the engineering problem.

Safety is considered one of the most important parameters when designing a ground vehicle. The adverse effect of weather on a vehicle can lead to a surge in safety issues and accidents. Several safety assistance systems are available in modern vehicles, which are designed to lessen the negative effects of weather hazards. Although these safety systems can intervene during crucial conditions to avoid accidents, driving a vehicle on snowy or icy terrain can still be a challenging task. Road conditions with the least tire-road friction often results in poor vehicle handling, and without any kind of safety system it can lead to mishaps. With the use of Adams Car software and vehicle dynamics modeling, a realistic relationship between the vehicle and road surface may be established. The simulation can be used to have a better understanding of vehicle handling in snowy and icy conditions, tire-ice interaction, and tire modeling.

Environmental perception is considered an essential module for autonomous driving and Advanced Driver Assistance System (ADAS). Recently, deep Convolutional Neural Networks (CNNs) have become the State-of-the-Art with many different architectures in various object detection problems. However, performances of existing CNNs have been dropping when detecting small objects at a large distance. To deploy any environmental perception system in real world applications, it is important that the system achieves high accuracy regardless of the size of the object, distance, and weather conditions. In this paper, a robust sensor fused object detection system is proposed by utilizing the advantages of both vision and automotive radar sensors. The proposed system consists of three major components: 1) the Coordinate Conversion module, 2) Multi level-Sensor Fusion Detection (MSFD) system, and 3) Temporal Correlation filtering module.

The safety of ground vehicles is a matter of critical importance. Vehicle safety is enhanced with the use of control systems that mitigate the effect of unachievable demands from the driver, especially demands for tire forces that cannot be developed. This paper presents the results of a smart tire prototyping and validation study, which is an investigation of a smart tire system that can be used as part of these mitigation efforts. The smart tire can monitor itself using in-tire sensors and provide information regarding its own tire forces and moments, which can be transmitted to a vehicle control system for improved safety. The smart tire is designed to estimate the three orthogonal tire forces and the tire aligning moment at least once per wheel revolution during all modes of vehicle operation, with high accuracy. The prototype includes two in-tire piezoelectric deformation sensors and a rotary encoder.

To improve the safety of automated driving, the paramount target of this intelligent system is to detect and segment the obstacle such as car and pedestrian, precisely. Object detection in self-driving vehicle has chiefly accomplished by making decision and detecting objects through each frame of video. However, there are diverse group of methods in both machine learning and machine vision to improve the performance of system. It is significant to factor in the function of the time in the detection phase. In other word, considering the inputs of system, which have been emitted from eclectic type of sensors such as camera, radar, and LIDAR, as time-varying signals, can be helpful to engross ‘time’ as a fundamental feature in modeling for forecasting the object, while car is moving on the way. In this paper, we focus on eliciting a model through the time to increase the accuracy of object detection in self-driving vehicles.

A numerical study on the combustion of Methanol in a directly injected (DI) engine was conducted. The study considers the effect of the bowl-in-piston (BIP) geometry, swirl ratio (SR), and relative equivalence ratio (λ), on flame propagation and burn rate of Methanol in a 4-stroke engine. Ignition-assist in this engine was accomplished by a spark plug system. Numerical simulations of two different BIP geometries were considered. Combustion characteristics of Methanol under swirl and no-swirl conditions were investigated. In addition, the amount of injected fuel was varied in order to determine the effect of stoichiometry on combustion. Only the compression and expansion strokes were simulated. The results show that fuel-air mixing, combustion, and flame propagation was significantly enhanced when swirl was turned on. This resulted in a higher peak pressure in the cylinder, and more heat loss through the cylinder walls.

While many current vehicle network systems for body bus applications use event triggered analysis processes, the deterministic point of view raises concerns about system timing due to message latency. This paper studies the latency performance characteristics of a typical body bus vehicle network using event triggered analysis over the CAN bus.

Kettering University's entry in the 2002 Clean Snowmobile Challenge involves the installation of a fuel injected four-stroke engine into a conventional snowmobile chassis. Exhaust emissions are minimized through the use of a catalytic converter and an electronically controlled closed-loop fuel injection system, which also maximizes fuel economy. Noise emissions are minimized by the use of a specifically designed engine silencing system and several chassis treatments. Emissions tests run during the SAE collegiate design event revealed that a snowmobile designed by Kettering University produces lower unburned hydrocarbon (1.5 to 7 times less), carbon monoxide (1.5 to 7 times less), and oxides of nitrogen (and 5 to 23 times less) levels than the average automobile driven in Yellowstone National Park. The Kettering University entry also boasted acceleration performance better than the late-model 500 cc two-stroke snowmobile used as a control snowmobile in the Clean Snowmobile testing.

Kettering University's entry in the 2003 Clean Snowmobile Challenge entails the installation of a fuel injected four-stroke engine into a conventional snowmobile chassis. Exhaust emissions are minimized through the use of a catalytic converter and an electronically controlled closed-loop fuel injection system, which also maximizes fuel economy. Noise emissions are minimized by the use of a specifically designed engine silencing system and several chassis treatments. Emissions tests run during the SAE collegiate design event revealed that a snowmobile designed by Kettering University produces lower unburned hydrocarbon (1.5 to 7 times less), carbon monoxide (1.5 to 7 times less), and oxides of nitrogen (and 5 to 23 times less) levels than the average automobile driven in Yellowstone National Park. The Kettering University entry also boasted acceleration performance better than the late-model 500 cc two-stroke snowmobile used as a control snowmobile in the Clean Snowmobile testing.

Mechanical counter-pressure (MCP) spacesuit designs have been a promising, but elusive alternative to historical and current gas pressurized spacesuit technology since the Apollo program. One of the important potential advantages of the approach is enhanced mobility as a result of reduced bulk and joint torques, but the literature provides essentially no quantitative joint torque data or quantitative analytical support. Decisions on the value of investment in MCP technology and on the direction of technology development are hampered by this lack of information since the perceived mobility advantages are an important factor. An experimental study of a simple mechanical counter-pressure suit (elbow) hinge joint has been performed to provide some test data and analytical background on this issue to support future evaluation of the technology potential and future development efforts.

With the recent advances in rapid modeling and rapid prototyping, accurate simulation models for tires are very desirable. Selection of a tire slip model depends on the required frequency range and nonlinearity associated with the dynamics of the vehicle. This paper presents a brief overview of three major slip concepts including “Stationary slip”, “Physical transient slip”, and “Pragmatic transient slip”; tire models use these slip concepts to incorporate tire slip behavior. The review illustrates that there can be no single accurate slip model which could be ideally used for all modes of vehicle dynamics simulations. For this study, a rigid ring based semi-analytical tire model for intermediate frequency (up to 100 Hz) is used.

Numerous human cadaver impact studies have shown that acute injury to the knee, femoral shaft, and hip may be significantly reduced by increasing the contact area over the anterior surface of the knee. Such impact events are common in frontal crashes when the knee strikes the instrument panel (IP). The cadaveric studies show that the injury threshold of the knee-thigh-hip complex increases as the contact area over the knee is likewise increased. Unfortunately, no prior methodology exists to record the spatial and temporal contact pressure distributions in dummy (or cadaver) experiments. Previous efforts have been limited to the use of pressure sensitive film, which only yields a cumulative record of contact. These studies assumed that the cumulative pressure sensitive film image correlated with the peak load, although this has never been validated.

For virtual simulation of the vehicle attributes such as handling, durability, and ride, an accurate representation of pneumatic tire behavior is very crucial. With the advancement in autonomous vehicles as well as the development of Driver Assisted Systems (DAS), the need for an Intelligent Tire Model is even more on the increase. Integrating sensors into the inner liner of a tire has proved to be the most promising way in extracting the real-time tire patch-road interface data which serves as a crucial zone in developing control algorithms for an automobile. The model under development in Kettering University (KU-iTire), can predict the subsequent braking-traction requirement to avoid slip condition at the interface by implementing new algorithms to process the acceleration signals perceived from an accelerometer installed in the inner liner on the tire.

A vehicle’s performance and fuel economy plays an important role in obtaining a larger market share in the segment. This can be best achieved by optimizing the aerodynamics of the vehicle. Aerodynamics can be improved by altering the bodylines on a vehicle. Its drag coefficient can be maintained at a minimum value by properly designing various component profiles. The stability of a vehicle and Passenger comfort are affected by wind noise that is related to the aerodynamics of a vehicle. To study the effects of the above-mentioned parameters, the vehicle is tested inside a wind tunnel. In this paper, the authors study the body profile for different vehicles and analyze them using Computational Fluid Dynamics software - FLUENT. To study the influence of different body profiles on drag coefficient, 3 different vehicle segments are considered.

The objective of this project is to analyze potential design changes that can improve the performance of helical spring in an independent suspension. The performance of the helical spring was based upon the result measure of maximum value of stress acting on it and the amount displacement caused when the spring undergoes loading. The design changes in the spring were limited to coil cross section, spring diameter (constant & variable), pitch and length of the spring. The project was divided into Stage I & Stage II. For Stage I, using all the possible combinations of these design parameters, linear stress analysis was performed on different spring designs and their Stress and displacement results were evaluated. Based on the results, the spring designs were classified as over designed or under designed springs.