Search Results

The application of DO-178B for the verification and validation of the safety-critical aspects of a steer-by-wire sub-system of a vehicle by using a spiral development model is discussed. The project was performed within a capstone design course at Kettering University. Issues including lessons learned regarding requirements, specifications, testing, verification, and validation activities as required by DO-178B are summarized.

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.

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.

Objection detection using a camera sensor is essential for developing Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) vehicles. Due to the recent advancement in deep Convolution Neural Networks (CNNs), object detection based on CNNs has achieved state-of-the-art performance during daytime. However, using an RGB camera alone in object detection under poor lighting conditions, such as sun flare, snow, and foggy nights, causes the system's performance to drop and increases the likelihood of a crash. In addition, the object detection system based on an RGB camera performs poorly during nighttime because the camera sensors are susceptible to lighting conditions. This paper explores different pedestrian detection systems at low-lighting conditions and proposes a sensor-fused pedestrian detection system under low-lighting conditions, including nighttime. The proposed system fuses RGB and infrared (IR) thermal camera information.

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.

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.

Object avoidance for autonomous driving is a vital factor in safe driving. When a vehicle travels from any random start places to any target positions in the milieu, an appropriate route must prevent static and moving obstacles. Having the accurate depth of each barrier in the scene can contribute to obstacle prevention. In recent years, precise depth estimation systems can be attributed to notable advances in Deep Neural Networks and hardware facilities/equipment. Several depth estimation methods for autonomous vehicles usually utilize lasers, structured light, and other reflections on the object surface to capture depth point clouds, complete surface modeling, and estimate scene depth maps. However, estimating precise depth maps is still challenging due to the computational complexity and time-consuming process issues. On the contrary, image-based depth estimation approaches have recently come to attention and can be applied for a broad range of applications.

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.

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.

Aerodynamics of trucks and other high sided vehicles is of significant interest in reducing road side accidents due to wind loading and in improving fuel economy. Recognizing the limitations of conventional wind tunnel testing, considerable efforts have been invested in the last decade to study vehicle aerodynamics computationally. In this paper, a three-dimensional near field flow analysis has been performed for axial and cross wind loading to understand the airflow characteristics surrounding a truck-like bluff body. Results provide associated drag for the truck geometry including the exterior rearview mirror. Modifying truck geometry can reduce drag, improving fuel economy.

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.

The kinematics and kinetics of a seven degree of freedom vehicle ride model with independent front and rear suspension are developed. Lagrange's equation is used to obtain the mathematical model of the vehicle. The equations of motion are transformed to state space equations in Linear Time Invariant (LTI) form. The effect of Chassis Design Factors (CDF) such as stabilizer bars, stiffness', Dynamic Index in Pitch (DIP) and mass ratio on the vehicle ride quality are investigated. The ride quality of the 3 dimensional vehicle that includes bounce, pitch, roll and unsprung masses motion is demonstrated in time domain response. The vehicle is considered as a Multi-Input-Multi-Output System (MIMO) subjected to deterministic ground inputs. Outputs of interest for the ride quality investigation are vertical and angular displacement and vertical accelerations. Numerical computer simulation analysis is performed using MATLAB® software.

Kettering University's Clean Snowmobile Challenge student design team has developed a new robust and innovative snowmobile for the 2005 competition. This snowmobile dramatically reduces exhaust and noise emissions and improves fuel economy compared with a conventional snowmobile. Kettering University has utilized a modified snowmobile in-line four cylinder, four-stroke, engine. The team added an electronically-controlled fuel-injection system with oxygen sensor feedback to this engine. This engine has been installed into a 2003 Yamaha RX-1 snowmobile chassis. Exhaust emissions have been further 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.

This work aims to present the application of mode coupling to a Formula Student racing vehicle and propose a solution. The major modes of a vehicle are heave, pitch, roll, and warp. All these modes are highly coupled – which means changing suspension rates or geometry will affect all of them – while alleviating some and making others worse characteristics. Decoupling these modes, or at least some of them, would provide more control over suspension setup and more refined race car dynamics for a given layout of the racetrack. This could improve mechanical grip and yield significant performance improvements in closed-circuit racing. If exploited well, this approach could also assist in the operation of the vehicle at an optimal kinematic state of the suspension systems, to gain the best wheel orientations and maximize grip from the tires under the high lateral accelerations and varied excitations seen on a typical road course.

Rapid changes in the automotive industry, including the growth of advanced vehicle controls and autonomy, are driving the need for more dedicated proving ground spaces where these systems can be developed safely. To address this need, Kettering University has created the GM Mobility Research Center, a 21-acre proving ground located in Flint, Michigan at the former “Chevy in the Hole” factory location. Construction of a proving ground on this site represents a beneficial redevelopment of an industrial brownfield, as well as a significant expansion of the test facilities available at the campus of Kettering University. Test facilities on the site include a road course and a test pad, along with a building that has garage space, a conference room, and an indoor observation platform. All of these facilities are available to the students and faculty of Kettering University, along with their industrial partners, for the purpose of engaging in advanced transportation research and education.

The “Range-of Motion of the Cervical Spine of Children” study is a collaboration between Kettering University and McLaren Regional Medical Center in Flint, Michigan to quantify and establish benchmarks of “normal” range of motion (ROM) in children. The results will be analyzed to determine mean and standard deviation of degrees of rotation and used to improve the occupant protection in motor vehicles, sports equipment and benefits of physical therapy. The data will be invaluable in the development of computational models to analyze processes involving children in motion.