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Tire-pavement interaction is a dominant noise source for passenger cars and trucks above 25 mph (40 km/h) and 43 mph (70 km/h), respectively. For the same pavement, tires with different tread pattern and construction generate noise of different levels and frequencies. In the present study, forty-two different tires were tested over a range of speeds (45-65 mph, i.e., 72-105 km/h) on a non-porous asphalt pavement (a section of U.S. Route 460, both eastbound and westbound). An On-Board Sound Intensity (OBSI) system was instrumented on the test vehicle to collect the tire noise data at both the leading and trailing edge of the tire contact patch. An optical sensor recording the once-per-revolution signal of the wheel was also installed to monitor the vehicle speed and, more importantly, to provide the data needed to perform the order tracking analysis in order to break down the tire noise into two components. These two components are: the tread pattern and the non-tread pattern noise. Based on the experimental noise data collected, two artificial neural networks (ANN) were developed to predict the tread pattern (ANN1) and the non-tread pattern noise (ANN2) components, separately. The inputs of ANN1 are the coherent tread profile spectrum and the air volume velocity spectrum calculated from the digitized 3D tread pattern. The inputs of ANN2 are the tire size and tread rubber hardness. The vehicle speed is also included as input for the two ANN's. The optimized ANN's are able to predict the tire-pavement interaction noise well for different tires on the pavement tested. Another outcome of this work is the complete literature review on Tire-Pavement Interaction Noise (TPIN), as an appendix of this dissertation and covering ~1000 references, which might be the most comprehensive compilation of this topic. PHD

In any automotive system, the tires play a very crucial role in defining both the safety and performance of the vehicle. The interaction between the tire and the road surface determines the vehicle's ability to accelerate, decelerate and steer. Having information about this interaction in real-time can be very valuable for the on-board advanced active safety systems to mitigate the risks ahead of time and keep the vehicle stable. The crucial information which can be obtained from the tire includes but are not limited to tire-road friction, tire forces (longitudinal, lateral), normal load, road surface characteristics and tire pressure. This information can be acquired through indirect vehicle dynamics based estimation algorithms or through direct measurements using sensors inside the tire. However, the indirect estimations fail to give an accurate measure of the vehicle state in certain conditions (e.g. side winds, road banking, surface change) and require ABS or VSC activation before the estimation begins. Therefore, to improve the performance of these active stability systems, direct measurement based approaches must be explored. This research expands the applications of Intelligent tire and focuses on using the sensor based measurement approach to develop estimation algorithms relating to tire force measurement. A tri-axial accelerometer is attached to the inner liner of the tire (Intelligent Tire) and two of such tires are placed on an instrumented (MSW, VBox, IMU, Encoders) VW Jetta. Different controlled tests are carried out on the instrumented vehicle and the Intelligent tire signal is analyzed to extract features related to the tire forces and pressure. Due to unavailability of direct force measurements at the wheel, a VW Jetta simulation model is developed in CarSim and the extracted features are validated with a good correlation. Master of Science

Irregularities in pavement profiles that exceed standard thresholds are usually rectified using a Diamond Grinding Process. Diamond Grinding is a method of Concrete Pavement Rehabilitation that involves the use of grinding wheels mounted on a machine that scraps off the top surface of the pavement to smooth irregularities. Profile Analysis Software like ProVAL© offers simulation modules that allow users to investigate various grinding strategies and prepare a corrective action plan for the pavement. The major drawback with the current Smoothness Assurance Module© (SAM) in ProVAL© is that it provides numerous grind locations which are both redundant and not feasible in the field. This problem can be overcome by providing a constrained grinding model in which a cost function is minimized; the resulting grinding strategy satisfies requirements at the least possible cost. Another drawback with SAM exists in the built-in grinder models that do not factor in the effect of speed and depth of cut on the grinding head. High speeds or deep cuts will result in the grinding head riding out the cut and likely worsening the roughness. A constrained grinding strategy algorithm with grinder models that factor in speed and depth of cut that results in cost effective grinding with better prediction of post grind surfaces through simulation is developed in this work. The outcome of the developed algorithm is compared to ProVAL's© SAM results. Master of Science

This research investigates a novel arrangement to pneumatic suspensions that are commonly used in heavy trucks, toward providing a dynamically balanced system that resists body roll and provides added roll stability to the vehicle. The new suspension, referred to as "balanced suspension," is implemented by retrofitting a conventional pneumatic suspension with two leveling valves and a symmetric plumbing arrangement to provide a balanced airflow and air pressure in the airsprings. This new design contributes to a balanced force distribution among the axles, which enables the suspension to maintain the body in a leveled position both statically and dynamically. This is in contrast to conventional heavy truck pneumatic suspensions that are mainly adjusted quasi-statically to level the body in response to load variations. The main objectives of the research are to discover and analyze the effects of various pneumatic components on the suspension dynamic response and numerically study the benefits of the pneumatically balanced suspension system. A pneumatic suspension model is established to capture the details of airsprings, leveling valves, check valves, pipes, and air tank based on the laws of fluid mechanics and thermodynamics. Experiments are designed and conducted to help determine and verify the modeling parameters and components. Co-simulation technique is applied to establish a multi-domain model that couples highly non-linear fluid dynamics of the pneumatic suspension with complex multi-body dynamics of an articulated vehicle. The model is used to extensively study effects of pneumatic balanced control of the suspensions on the tractor and trailer combination dynamics. The simulations indicate that the dual leveling valve arrangement of the balanced suspension provides better adjustments to the body roll by charging the airsprings on the jounce side, while purging air from the rebound side. Such an adjustment allows maintaining a larger difference in suspension force from side to side, which resists the vehicle sway and levels the truck body during cornering. Additionally, the balanced suspension better equalizes the front and rear drive axle air pressures, for a better dynamic load sharing and pitch control. It is evident from the simulation results that the balanced suspension increases roll stiffness without affecting vertical stiffness, and thereby it can serve as an anti-roll bar that results in a more stable body roll during steering maneuvers. Moreover, the Failure Mode and Effects Analysis (FMEA) study suggests that when one side of the balanced suspension fails, the other side acts to compensate for the failure. On the other hand, if the trailer is also equipped with dual leveling valves, such an arrangement will bring an additional stabilizing effect to the vehicle in case of the tractor suspension failure. The overall research results presented show that significant improvements on vehicle roll dynamics and suspension dynamic responsiveness can be achieved from the balanced suspension system. PHD

This study introduces new families of wavelets. The first is directly derived from the response of Second Order Underdamped Linear-Time-Invariant (SOULTI) systems, while the second is a generalization of the first to the complex domain and is similar to the Laplace transform kernel function. The first takes the acronym of SOULTI wavelet, while the second is named the Laplace wavelet. The most important criteria for a function or signal to be a wavelet is the ability to recover the original signal back from its continuous wavelet transform. It is shown that it is possible to recover back the original signal once the SOULTI or the Laplace wavelet transform is applied to decompose the signal. It is found that both wavelet transforms satisfy linear differential equations called the reconstructing differential equations, which are closely related to the differential equations that produce the wavelets. The new wavelets can have well defined Time-Frequency resolutions, and they have useful properties; a direct relation between the scale and the frequency, unique transform formulas that can be easily obtained for most elementary signals such as unit step, sinusoids, polynomials, and decaying harmonic signals, and linear relations between the wavelet transform of signals and the wavelet transform of their derivatives and integrals. The defined wavelets are applied to system analysis applications. The new wavelets showed accurate instantaneous frequency identification and modal decomposition of LTI Multi-Degree of Freedom (MDOF) systems and it showed better results than the Short-time Fourier Transform (STFT) and the other harmonic wavelets used in time-frequency analysis. The modal decomposition is applied for modal parameters identification, and the properties of the Laplace and the SOULTI wavelet transforms allows analytical and accurate identification methods. Ph. D.

Rubber friction is an important aspect to tire engineers, material developers and pavement engineers because of its importance in the estimation of forces generated at the contact, which further helps in optimizing tire and vehicle performances, and to estimate tire wear. It mainly depends on the material properties, contact mechanics and operating condition. There are two major contributions to rubber friction, due to repeated viscoelastic deformation from undulations of surface called hysteresis and due to Vander Waals interaction of the molecules called adhesion. The study focuses on analytical modeling of friction for stationary sliding of rubber block on rough surfaces. Two novel approaches are discussed and compared. Frictional shear stress is obtained from the energy dissipated at the contact interface due to the elastic deformations of rubber block at different length scales. Contact mechanics theories based on continuity approach combined with stochastic processes to estimate the real contact area, mean penetration depth and true stresses at contact depending on operating conditions. Rubber properties are highly temperature dependent. Temperature model developed based on heat diffusion relation is integrated to consider the effects of temperature rise due to frictional heating. Model results are validated with theoretical results of literature. Simulation results of friction model is obtained for Compound A sliding on rough surface. Material properties are obtained using Dynamic Mechanical Analysis and Time temperature superposition. Influence of the friction models under different conditions are discussed. Model results are validated with experimental data from Dynamic friction tester on a 120-grit surface followed by future works. Master of Science

This dissertation proposes an approach for 3D micro-scale shape reconstruction using photometric stereo (PS) with surface normal integration (SNI). Based on the proposed approach, a portable cost-effective stationary system is developed to capture 3D shapes in the order of micrometer scale. The PS with SNI technique is adopted to reconstruct 3D microtopology since this technique is highlighted for its capability to reproduce fine surface details at pixel resolution. Furthermore, since the primary hardware components are merely a camera and several typical LEDs, the system based on PS with SNI can be made portable at low cost. The principal contributions are three folds. First, a PS method based on dichromatic reflectance model (DRM) using color input images is proposed to generalize PS applicable to a wider range of surfaces with non-Lambertian reflectances. The proposed method not only estimates surface orientations from diffuse reflection but also exploits information from specularities owing to the proposed diffuse-specular separation algorithm. Using the proposed PS method, material-dependent features can be simultaneously extracted in addition to surface orientations, which offers much richer information in understanding the 3D scene and poses more potential functionalities, such as specular removal, intrinsic image decomposition, digital relighting, material-based segmentation, material transfer and material classification. The second contribution is the development of an SNI method dealing with perspective distortion. The proposed SNI is performed on the image plane instead of on the target surface as did by orthographic SNI owing to the newly derived representation of surface normals. The motivation behind the representation is from the observation that spatially uniform image points are simpler for integration than the non-uniform distribution of surface points under perspective projection. The new representation is then manipulated to the so-called log gradient space in analogy to the gradient space in orthographic SNI. With this analogy, the proposed method can inherit most past algorithms developed for orthographic SNI. By applying the proposed SNI, perspective distortion can be efficiently tackled with for smooth surfaces. In addition, the method is PS-independent, which can keep the image irradiance equation in a simple form during PS. The third contribution is the design and calibration of a 3D micro-scale shape reconstruction system using the derived PS and SNI methods. This system is originally designed for on-site measurement of pavement microtexture, while its applicability can be generalized to a wider range of surfaces. Optimal illumination was investigated in theory and through numerical simulations. Five different calibrations regarding various aspects of the system were either newly proposed or modified from existing methods. The performances of these calibrations were individually evaluated. Efficacy of the developed system was finally demonstrated through comprehensive comparative studies with existing systems. Its capability for on-site measurement was also confirmed. Ph. D.

Lack of drivers knowledge about the abrupt changes in pavement friction and poor performance of the vehicle stability, traction and ABS controllers on the low friction surfaces are the most important factors affecting car crashes. Due to its direct relation to vehicle stability, accurate estimation of tire-road characteristics is of interest to all vehicle and tire companies. Many studies have been conducted in this field and researchers have used different tools and have proposed different algorithms. One such concept is the Intelligent Tire. The application of intelligent tire in tire-road characterization is investigated in this study. Three different test setups were used in this research to study the application of the intelligent tires to improve mobility; first, a wheeled ground robot was designed and built. A Fuzzy Logic algorithm was developed and validated using the robot for classifying different road surfaces such as asphalt, concrete, grass, and soil. The second test setup is a portable tire testing trailer, which is a quarter car test rig installed in a trailer and towed by a truck. The trailer was equipped with different sensors including an accelerometer attached to the center of the tire inner-liner. Using the trailer, acceleration data was collected under varying conditions and a Neural Network (NN) algorithm was developed and trained to estimate the contact patch length, effective tire rolling radius and tire normal load. The third test setup developed for this study was an instrumented Volkswagen Jetta. Different sensors were installed to measure vehicle dynamic response. Additionally, one front and one rear tire was instrumented with an accelerometer attached to their inner-liner. Two intelligent tire based algorithms, a tire pressure estimation algorithm and a road condition monitoring algorithm, were developed and trained using the experimental data from the instrumented VW Jetta. The two-step pressure monitoring algorithm uses the acceleration signal from the intelligent tire and the wheel angular velocity to monitor the tire pressure. Also, wet and dry surfaces are distinguished using the acceleration signal from the intelligent tire and the wheel angular velocity through the surface monitoring algorithm. Some of the model based tire-road friction estimation algorithms, which are widely used for tire-road friction estimation, were also introduced in this study and the performance of each algorithm was evaluated in high slip and low slip maneuvers. Finally a new friction estimation algorithm was developed, which is a combination of experiment based and vehicle dynamic based approaches and its performance was also investigated. PHD

Semi-active suspensions have drawn particular attention due to their superior performance over the other types of suspensions. One of their advantages is that their damping coefficient can be controlled without the need for any external source of power. In this study, a handful of control approaches are implemented on a car models using MATLAB/Simulink. The investigated control methodologies are skyhook, groundhook, hybrid skyhook-groundhook, Acceleration Driven Damper, Power Driven Damper, H∞ Robust Control, Fuzzy Logic Controller, and Inverse ANFIS. H∞ Robust Control is an advanced method that guarantees transient performance and rejects external disturbances. It is shown that H∞ with the proposed modification, has the best performance although its relatively high cost of computation could be potentially considered as a drawback. Also, the proposed Inverse ANFIS controller uses the power of fuzzy systems along with neural networks to help improve vehicle ride metrics significantly. In this study, a novel approach is introduced to analyze and fine-tune semi-active suspension control algorithms. In some cases, such as military trucks moving on off-road terrains, it is critical to keep the vehicle ride quality in an acceptable range. Semi-active suspensions are used to have more control over the ride metrics compared to passive suspensions and also, be more cost-effective compared to active suspensions. The proposed methodology will investigate the skyhook-groundhook hybrid controller. This is accomplished by conducting sensitivity analysis of the controller performance to varying vehicle/road parameters. This approach utilizes sensitivity analysis and one-at-a-time methodology to find and reach the optimum point of vehicle suspensions. Furthermore, real-time tuning of the mentioned controller will be studied. The online tuning will help keep the ride quality of the vehicle close to its optimum point while the vehicle parameters are changing. A quarter-car model is used for all simulations and analyses. Ph. D.

The objective of this research is to provide an in-depth analysis of the contact patch behavior of a specific passenger car tire. A Michelin P205/60R15 tire was used for this study. Understanding the way the tire interacts with the road at various loads, inflation pressures and driving conditions is essential to optimizing tire and vehicle performance. The footprint shape and stress distribution pattern are very important factors that go into assessing the tire's rate of wear, the vehicle's fuel economy and has a major effect on the vehicle stability and control, especially under severe maneuvers. In order to study the contact patch phenomena and analyze these stresses more closely, a finite element (FE) tire model which includes detailed tread pattern geometry has been developed, using a novel reverse engineering process. In order to validate this model, an experimental process has been developed to obtain the footprint shape and contact pressure distribution. The differences between the experimental and the simulation results are discussed and compared. The validated finite element model is then used for predicting the 3D stress distribution fields at the contact patch. The predictive capabilities of the finite element tire model are also explored in order to predict the handling characteristics of the test tire under different maneuvers such as pure cornering and pure braking. Master of Science

The electromechanical design and development of a sophisticated roller rig testing facility at the Railway Technologies Laboratory (RTL) of Virginia Polytechnic and State University (VT) is presented. The VT Roller Rig is intended for studying the complex dynamics and mechanics at the wheel-rail interface of railway vehicles in a controlled laboratory environment. Such measurements require excellent powering and driving architecture, high-performance motion control, accurate measurements, and relatively noise-free data acquisition systems. It is critical to accurately control the relative dynamics and positioning of rotating bodies to emulate field conditions. To measure the contact forces and moments, special care must be taken to ensure any noise, such as mechanical vibration, electrical crosstalk, and electromagnetic interference (EMI) are kept to a minimum. This document describes the steps towards design and development of all electromechanical subsystems of the VT Roller Rig, including the powertrain, power electronics, motion control systems, sensors, data acquisition units, safety and monitoring circuits, and general practices followed for satisfying the local and international codes of practice. The VT Roller Rig is comprised of a wheel and a roller in a vertical configuration that simulate the single-wheel/rail interaction in one-fourth scale. The roller is five times larger than the scaled wheel to keep the contact patch distortion that is inevitable with a roller rig to a minimum. This setup is driven by two independent AC servo motors that control the velocity of the wheel and roller using state-of-the-art motion control technologies. Six linear actuators allow for adjusting the simulated load, wheel angle of attack, rail cant, and lateral position of the wheel on the rail. All motion controls are performed using digital servo drives, manufactured by Kollmorgen, VA, USA. A number of sensors measure the contact patch parameters including force, torque, displacement, rotation, speed, acceleration, and contact patch geometry. A unified communication protocol between the actuators and sensors minimizes data conversion time, which allows for servo update rates of up to 48kHz. This provides an unmatched bandwidth for performing various dynamics, vibrations, and transient tests, as well as static steady-state conditions. The VT Roller Rig has been debugged and commissioned successfully. The hardware and software components are tested both individually and within the system. The VT Roller Rig can control the creepage within 0.3RPM of the commanded value, while actively controlling the relative position of the rotating bodies with an unprecedented level of accuracy, no more than 16nm of the target location. The contact force measurement dynamometers can dynamically capture the contact forces to within 13.6N accuracy, for up to 10kN. The instantaneous torque in each driveline can be measured with better than 6.1Nm resolution. The VT Roller Rig Motion Programming Interface (MPI) is highly flexible for both programmers and non-programmers. All common motion control algorithms in the servo motion industry have been successfully implemented on the Rig. The VT Roller Rig MPI accepts third party motion algorithms in C, C++, and any .Net language. It successfully communicates with other design and analytics software such as Matlab, Simulink, and LabVIEW for performing custom-designed routines. It also provides the infrastructure for linking the Rig's hardware with commercial multibody dynamics software such as Simpack, NUCARS, and Vampire, which is a milestone for hardware-in-the-loop testing of railroad systems. Ph. D.

Vehicle suspension systems play an integral role in influencing the overall performance of a vehicle. The suspension system of a vehicle performs multiple tasks, such as maintaining contact between the tires and the road and isolating the frame of the vehicle from road-induced vibration and shocks. A significant amount of research has been directed to improving the performance of the suspension system by varying the damping coefficient so as to alter the frequency response of the system. This study describes the development of such a damper. The goal of this research has been to design, model, fabricate and test a novel semi-active damper. The damper consists of two independent electronically controlled units placed in series with one another. The system was initially simulated using a 2 DOF quarter-car model and the performance characteristics of the damper were outlined. Following that, multiple design iterations of the damper were created and a MATLAB/Simulink model was used to simulate physical and flow characteristics of the damper. After the design and analysis was complete, the damper was fabricated and tested using a shock dyno at CenTiRe. The test results were then compared to the simulation results so as to confirm performance of the damper. Additionally, the results obtained on the dyno were then compared against that of a relative single semi-active and passive damper. Master of Science

Tire testing has been one of the important aspects of the tire industry because it helps identify the tire behavior which further helps in improving the design of tires. It also helps automotive manufacturers choose the best tire for their automobiles. Indoor tire testing helps in relating the data better because of greater repeatability of the testing setup as compared to outdoor testing. This study focusses on modifying a rolling resistance machine to make it capable of force and moment and cleat testing along with the standard rolling resistance test. Additionally, the design of a mechanical loading mechanism (used to apply normal force on the tire) in place of the previous one using dead weights is also discussed. This study also talks about the structural and vibrational finite element analysis of a tire testing machine. Since the machine was designed to conduct different tire tests, different structural requirements of the tire positioning mechanism pertaining to each test were taken into consideration, and the structure was analyzed for maximum forces and moments acting on the assembly. Cleat testing subjects the tire as well as the structure to an impulse force which calls for the vibrational analysis of the assembly to avoid the structure from resonating. The design was modified to get it easily manufactured and assembled. These design changes and the aspects taken into consideration have also been discussed. Master of Science

Speed bump energy harvester, which aims to harvest energy from the passing by vehicles by absorbing their kinetic and potential energy, is designed, fabricated, simulated, and tested in this research. The proposed design is analyzed with a theoretical modelling which has then been validated with a ground test. Result reveals that the prototype has been able to produce up to 600 watts of peak power and around 150 watts of RMS power which is significant number. Further analysis has been done which theoretically suggests that the numbers could be increased up to 1 KW by optimizing the speed bump design and varying the system parameters such as electrical damping, mechanical damping, velocity and weight of the vehicles. Overall, system is able to increase the overall energy density by using Mechanical Motion Rectification (MMR) technology which would allow the increase in the power generation almost by double. Furthermore, different vehicle models have been used to analyze the effectiveness and accuracy of the harvester and also, the effect of harvester on the dynamics of the vehicle has been studied and analyzed in detail. Master of Science

Tires are the most influential component of the vehicle as they constitute the only contact between the vehicle and the road and have to generate and transmit forces necessary for the driver to control the vehicle. Hydroplaning is a phenomenon which occurs when a layer of water builds up between the tires of a vehicle and the road surface which leads to loss of traction that prevents the vehicle from responding to control inputs such as steering, braking or acceleration. It has become an extremely important factor in the automotive and tire industry to study the factors affecting vehicle hydroplaning. Nearly 10-20% of road fatalities are caused by lack of traction on wet surfaces. The tire tread pattern, load, inflation pressure, slip and camber angles influence hydroplaning to a great extent. Finite Element Analysis, although computationally expensive, provides an excellent way to study such Fluid Structure Interactions (FSI) between the tire-water-road surfaces. Abaqus FSI CEL approach has been used to study tire traction with various vehicle configurations. The tire force data obtained from the Finite Element simulations is used to develop a full vehicle hydroplaning model by integrating the relevant outputs with the commercially available vehicle dynamics simulation software, CarSim. Master of Science

The focus of this study is on the development of a state-of-the-art single-wheel roller rig for studying contact mechanics and dynamics in railroad applications. The use of indoor-based simulation tools has become a mainstay in vehicle testing for the automotive and railroad industries. In contrast to field-testing, roller rigs offer a controlled laboratory environment that can provide a successful path for obtaining data on the mechanics and dynamics of railway systems for a variety of operating conditions. The idea to develop a laboratory test rig started from the observation that there is a need for better-developed testing fixtures capable of accurately explaining the complex physics of wheel-rail contact toward designing faster, safer, and more efficient railway systems. A review of current roller rigs indicated that many desired functional requirements for studying contact mechanics currently are not available. Thus, the Virginia Tech Railway Technologies Laboratory (RTL) has embarked on a mission to develop a state-of-the-art testing facility that will allow experimental testing of contact mechanics in a dynamic, controlled, and consistent manner. VT roller rig will allow for closely replicating the boundary conditions of railroad wheel-rail contact via actively controlling all the wheel-rail interface degrees of freedom: cant angle, angle of attack, and lateral displacement. Two sophisticated independent drivelines are configured to precisely control the rotational speed of the wheels, and therefore their relative slip or creepage. A novel force measurement system, suitable for steel on steel contact, is configured to precisely measure the contact forces and moments at the contact patch. The control architecture is developed based on the SynqNet data acquisition system offered by Kollmorgen, the motors supplier. SynqNet provides a unified communication protocol between actuators, drives, and data acquisition system, hence eliminating data conversion among them. Various design analysis indicates that the rig successfully meets the set requirements: additional accuracy in measurements, and better control on the design of experiments. The test results show that the rig is capable of conducting various contact mechanics studies aimed for advancing the existing art. Beyond developing the experimental testing fixture for studying contact mechanics, this study provides a comprehensive review of the contact models. It discusses the simplifying assumptions for developing the models, compares the models functionality, and highlights the open areas that require further experimental and theoretical research. In addition, a multi-body dynamic model of the entire rig, using software package SIMPACK, is developed for conducting modal analysis of the rig and evaluating the performance of the rig's components. A MATLAB routine is also developed that provides a benchmark for developing creep curves from measurements of the rig and comparing them with existing creep curves. Ph. D.

It is important for highway agencies to monitor the pavement friction periodically and systematically to support their safety management programs. The collected data can help implement preservation policies that improve the safety of the roadway network and decrease the number of skidding-related crashes. This dissertation introduces new approaches to effectively use tire-pavement friction data for supporting asset management decisions. It follows a manuscript format and is composed of five papers. The first chapter of the dissertation discusses the principles of tire pavement friction and surface texture. Methods for measuring friction and texture are further discussed in this chapter. The importance of friction in safety design of highways is also highlighted. The second chapter discusses a case study on developing pavement friction management program. The proposed approach in this chapter can be used by highways agencies to develop pavement friction management program. Contrary to general perception, that friction is only influencing wet condition crashes, this study indicated that friction is associated with both wet and dry condition crashes. The third and fourth chapters of the dissertation introduce a soft-computing approach for pavement friction management. Artificial Neural Network and Fuzzy Logic approach are presented. The learning ability of Neural Network makes it appealing as it can learn from examples; however, Neural Network is generally complicated and hard to understand for practical purposes. The Fuzzy system on the other hand is easy to understand. The advantage of Fuzzy system over Artificial Neural Network is that it uses linguistic and human like rules. Sugeno Neuro-Fuzzy approach is used to tune the proposed Fuzzy Logic model. Neuro-Fuzzy approach has the benefit of incorporating both 'learning ability' of neural network and human ruled based decision making aspect of fuzzy logics. The application of the fuzzy system in real-time slippery spot warning system is demonstrated in chapter five. Finally, the sixth chapter of the dissertation evaluates the potential of grinding and grooving technique to restore friction properties of the pavement. Once sleek spots are identified through pavement friction management program, this technique can be used to restore the friction without compromising the roadway smoothness. Ph. D.

Engineers of off-road equipment, on-road vehicles, pavement, and tires must assess the roughness of a terrain surface for the design of their products. The International Roughness Index (IRI), a standardized means of assessing longitudinal road roughness, quantifies roughness based on the average suspension travel for a particular vehicle at a prescribed speed. The Discrete Roughness Index (DRI) developed in this work address fundamental limitations of the IRI. Specifically, the DRI is calculated for each discretely measured location along a terrain surface and is applicable to vehicles traveling at varying speeds and using parameters other than the Golden Quarter-Car on which the IRI is based. The development of the DRI begins with a consistent discretization of the terrain surface, vehicle response, and the IRI. Next the Fractional Response Coefficient is developed, the properties of which are critical in the development of the DRI. The DRI is developed and its properties are discussed through theory and simulation of the ASTM E1926-08 profile. One important property of the average DRI is that it converges to the IRI as the distance between sampled points becomes smaller, for the particular case when the Golden Quarter-Car model is simulated at 80 kph. The DRI is not an alternative to the standard IRI, therefore, but a widely applicable roughness measure of which the standard IRI is a single specialized application. Master of Science

The primary focus of this research is evaluation of feasibility, applicability, and accuracy of Doppler Light Detection And Ranging (LIDAR) sensors as non-contact means for measuring track speed, distance traveled, and curvature. Speed histories, currently measured with a rotary, wheel-mounted encoder, serve a number of useful purposes, one significant use involving derailment investigations. Distance calculation provides a spatial reference system for operators to locate track sections of interest. Railroad curves, using an IMU to measure curvature, are monitored to maintain track infrastructure within regulations. Speed measured with high accuracy leads to high-fidelity distance and curvature data through utilization of processor clock rate and left-and right-rail speed differentials during curve navigation, respectively. Wheel-mounted encoders, or tachometers, provide a relatively low-resolution speed profile, exhibit increased noise with increasing speed, and are subject to the inertial behavior of the rail car which affects output data. The IMU used to measure curvature is dependent on acceleration and yaw rate sensitivity and experiences difficulty in low-speed conditions. Preliminary system tests onboard a 'Hy-Rail' utility vehicle capable of traveling on rail show speed capture is possible using the rails as the reference moving target and furthermore, obtaining speed profiles from both rails allows for the calculation of speed differentials in curves to estimate degrees curvature. Ground truth distance calibration and curve measurement were also carried out. Distance calibration involved placement of spatial landmarks detected by a sensor to synchronize distance measurements as a pre-processing procedure. Curvature ground truth measurements provided a reference system to confirm measurement results and observe alignment variation throughout a curve. Primary testing occurred onboard a track geometry rail car, measuring rail speed over substantial mileage in various weather conditions, providing high-accuracy data to further calculate distance and curvature along the test routes. Tests results indicate the LIDAR system measures speed at higher accuracy than the encoder, absent of noise influenced by increasing speed. Distance calculation is also high in accuracy, results showing high correlation with encoder and ground truth data. Finally, curvature calculation using speed data is shown to have good correlation with IMU measurements and a resolution capable of revealing localized track alignments. Further investigations involve a curve measurement algorithm and speed calibration method independent from external reference systems, namely encoder and ground truth data. The speed calibration results show a high correlation with speed data from the track geometry vehicle. It is recommended that the study be extended to provide assessment of the LIDAR's sensitivity to car body motion in order to better isolate the embedded behavior in the speed and curvature profiles. Furthermore, in the interest of progressing the system toward a commercially viable unit, methods for self-calibration and pre-processing to allow for fully independent operation is highly encouraged. Ph. D.

Accurate and efficient tire models for deformable terrain operations are essential for performing vehicle simulations. Assessment of the forces and moments that occur at the tire-terrain interface, and the effect of the tire motion on properties of the terrain are crucial in understanding the performance of a vehicle. In order to model the dynamic behavior of the tire on different terrains, a lumped mass discretized tire model using Kelvin-Voigt elements is developed. To optimize the computational time of the code, different techniques were used in memory allocation, parameter initialization, code sequence, and multi-processing. This has resulted in significant improvements in efficiency of the code that can now run close to real time and therefore it is suitable for use by commercially available vehicle simulation packages. Model parameters are obtained using a validated finite element tire model, modal analysis, and other experimental test procedures. Experimental tests were performed on the Terramechanics rig at Virginia Tech. The tests were performed on different terrains; tire forces and moments, soil sinkage, and tire deformation data were collected for various case studies based on a design of experiment matrix. This data, in addition to modal analysis data were used to validate the tire model. Furthermore, to study the validity of the tire model, simulations at conditions similar to the test conditions were performed on a quarter car model. The results have indicated the superiority of this model as compared to other lumped parameter models currently available. Ph. D.

Automotive and Tire companies spend extensive amounts of time and money to tune their products through prototype testing at dedicated test facilities. This is mainly due to the limitations in the simulation capabilities that exist today. With greater competence in simulation, comes more control over designs in the initial stages, which in turn lowers the demand on the expensive stage of tuning. The work presented, aims at taking today's simulation capabilities a step forward by integrating models that are best developed in different software interfaces. An in-plane rigid ring model is used to understand the transient response of tires to various high frequency events such as Anti-Lock Braking and short wavelength road disturbances. A rule based ABS model performs the high frequency braking operation. The tire and ABS models have been created in the Matlab-Simulink environment. The vehicle model has been developed in CarSim. The models developed in Simulink have been integrated with the vehicle model in CarSim, in the form of a design tool that can be used by tire as well as vehicle designers for further tuning of the vehicle functional performances as they relate to in-line braking scenarios. Outdoor validation tests were performed to obtain data from a vehicle that was measured on a suspension parameter measuring machine (SPMM) in order to complement this design tool. The results of the objective tests performed have been discussed and the correlations and variations with respect to the simulation results have been analyzed. Master of Science

The evolution of vehicle safety systems, from the earliest brakes to today's accident avoidance systems, has led vehicles to have very high passenger safety. Driving on ice, though, still happens to be one of the driving conditions of low safety. A multitude of factors were identified by various studies to contribute to the complex frictional mechanism at the tire-ice interface. The tire is only force transmitting element of the vehicle, to the surface. Thus it is very essential to have in depth understanding of the contact phenomena at the tire-ice interface, to improve vehicle safety on icy roads. This study has led to understanding of the contact phenomena at the tire-ice contact through experimental studies and a semi-empirical based tire-ice contact model. Experimental studies included both indoor testing and outdoor testing, indoor testing was conducted using the Terramechanics Rig at the Advanced Vehicle Dynamics in Virginia Tech and field tests were conducted at the Keweenaw Research Center in Michigan Tech. The simulation results of the tire-ice model were validated against the findings of the indoor test program. The P225/60R16 97S Standard Reference Test Tire was the candidate tire for this study. The effects of operational parameters, were studied when in driving traction by comparison of the friction - slip ratio curves. The two tests procedures were performed to understand how each test method influences the test results. A comparison of the laboratory and field test method are also presented, with reasons for the differences in the measured values presented. The experimental study also led to development of a modular structured tire-ice model (TIM). The model computes the temperature rise in the contact patch based on the pressure distribution in the contact patch, thermal properties of the tread compound and of the ice surface. The contact patch is then classified into wet and dry regions based on the ice surface temperature and temperature rise simulations. The principle of thermal balance is then applied to compute the friction level in the contact patch. The tire-ice contact model is validated for two parameters: temperature rise and friction levels. Temperature rise from simulations are validated against temperature measurements at the leading and trailing edge of the contact patch. Friction levels at different conditions of load, inflation pressure, and ice temperatures have been simulated using the tire-ice contact model and compared to the experimental findings. Ph. D.

The focus of Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) research is to develop a system to avoid situations in which the vehicle exceeds its handling capabilities. The proposed method is predictive, estimating the ability of the vehicle to successfully navigate upcoming terrain, and it is assumed that the future vehicle states and local driving environment is known. An Intervention Strategy must be developed such that the vehicle is navigated successfully along a road via modest changes to the driver's commands and do so in a manner that is in harmony with the driver's intentions and not in a distracting or irritating manner. Clearly this research relies on the numerous new technologies being developed to capture and convey information about the local driving environment (e.g., bank angle, elevation changes, curvature, and friction coefficient) to the vehicle and driver. Ph. D.

Tires are the most influential component of the vehicle as they constitute the only contact between the vehicle and the road and have to generate and transmit forces necessary for the driver to control the vehicle. The demand for the tire models are increasing due to the need to study the variations of force generation mechanisms due to various variables such as load, pressure, speed, and road surface irregularities. Another need from the vehicle manufactures is the study of potential incompatibilities associated with safety systems such as Anti-lock Braking System (ABS) and Electronic Stability Control (ESC) and tires. For vehicle dynamic simulations pertaining to the design of safety systems such as ABS, ESC and ride controllers, an accurate and computationally efficient tire model is required. As these control algorithms become more advanced, they require accurate and extended validity in the range of frequencies required to cover dynamic response due to short wavelength road disturbances, braking and steering torque variations. Major thrust has been provided by the tire industry to develop simulation models that accurately predict the dynamic response of tires without the use of computationally intensive tools such as FEA. The objectives of this research are • To develop, implement and validate a rigid ring tire model and a simulation tool to assist both tire designers and the automotive industry in analyzing the effects of tire belt vibrations, road disturbances, and high frequency brake and steering torque variations on the handling, braking, and ride performances of the vehicle. • To further enhance the tire model by considering dynamic stiffness changes and temperature dependent friction properties. • To develop, and implement novel control algorithms for braking, stability, and ride performance improvements of the vehicle Ph. D.

The interaction between a tire and road surface is of critical importance as the motion of a car in both transient and steady-state maneuvers is predicated on the friction forces generated at the tire-road interface. A general method for predicting friction coefficients for an arbitrary asphalt pavement surface would be an invaluable engineering tool for designing many vehicle safety and performance features, tire design, and improving asphalt-aggregate mixtures used for pavement surfaces by manipulating texture. General, physics-based methods for predicting friction are incredibly difficult, if not impossible to realize—However, for the specific case of rubber sliding across a rough surface, the primary physical mechanisms responsible for friction, notably rubber hysteresis, can be modeled. The objective of the subsequent research is to investigate one such physics model, referred to as Persson Theory, and implement the constitutive equations into a MatLab® code to be solved numerically. The model uses high-resolution surface measurements, along with some of the physical properties of rubber as inputs and outputs the kinetic friction coefficient. The Persson model was successfully implemented into MatLab® and high resolution measurements (from optical microscopy and imaging software) were obtained for a variety of surfaces. Friction coefficients were calculated for each surface and compared with measured friction values obtained from British Pendulum testing. The accuracy and feasibility of the Persson model are discussed and results are compared with a simpler, semi-empirical indenter model. A brief discussion of the merits and drawbacks of the Persson model are offered along with recommendations for future research based on the information acquired from the present study. Master of Science

Road roughness is an important factor in determining the quality of a stretch of road. The International Roughness Index, a specific measure of road roughness, is widely used metric. However, in order to measure roughness, an accurate road profile must exist. To measure the roads, terrain profiling systems are commonly used. Modern systems based on laser scanners and inertial navigation systems (INS) are able to measure thousands of data points per seconds over a wide path. However, because of the subsystems in the profiling systems, they are susceptible to errors that reduce the accuracy of the measurements. Thus, both major subsystems - the laser and the navigation system - must be accurate and synchronized for the road to be correctly scanned. The sensors' mounting was investigated to ensure that the vehicle motion is accurately captured and accounted for, demonstrated in the Vehicle Terrain Performance Lab's (VTPL) Ford Explorer profilometer. Next, INS errors were addressed. These may include drift in the inertial measurement unit or errors due to poor reception with the global navigation satellite system. The solution to these errors was demonstrated through the VTPL's HMMWV profilometer. Master of Science

Studying the kinetic and kinematics of the rim-tire combination is very important in full vehicle simulations, as well as for the tire design process. Tire maneuvers are either quasi-static, such as steady-state rolling, or dynamic, such as traction and braking. The rolling of the tire over obstacles and potholes and, more generally, over uneven roads are other examples of dynamic events which are of importance. In the latter case, tire dynamic models are used for durability assessment of the vehicle chassis, and should be studied using high fidelity simulation models. In this study, a threedimensional finite element model (FEM) of the 16 inch TMPT Tire has been developed using the commercial software package ABAQUS. The purpose of this study is to investigate tire transient dynamic behavior for various inputs. The process of running dynamic FE tire simulations starts by statically inflating and loading the tire using an implicit method with refined mesh in the contact patch. Then, by using the "result transfer" option in ABAQUS, final state vectors are used as initial conditions for subsequent simulations. Using this sequence of loading steps helps increase the efficiency of the code. The validation of the model is performed in two stages. First, tire mode shapes and associated natural frequencies and damping values are compared with the experimental data. Second, a series of transient dynamic simulations are performed using an explicit method with a fine mesh around the circumference of the tire. Finally, the FEM model results are filtered to eliminate the numerical noise, and their correlation with the test data is investigated. Moreover, the peak values and time shifts associated with spindle forces as a function of normal load are studied. The results show that the tire dynamic response is autonomous. Master of Science

This dissertation proposes a novel computer modeling (DTFLOP modeling) technique to predict the real-time behavior of dynamic systems. The proposed DTFLOP modeling classifies the computation into the sequential computation, which is conducted on the CPU, and the parallel computation, which is performed on the GPU and formulates the data transmission between the CPU and the GPU using the parameters of the memory access speed and the floating point operations to be carried out on the CPU and the GPU by relating the calculation rate respectively. With the help of the proposed DTFLOP modeling it is possible to estimate the time cost for computing the model that represents a dynamic system given a certain computer. The proposed DTFLOP modeling can be utilized as a general method to analyze the computation of a model related to a dynamic system and two real life systems are selected to demonstrate its performance, the cooperative autonomous vehicle system and the full-field measurement system. For the cooperative autonomous vehicle system a novel parallel grid-based RBE technique is firstly proposed. The formulations are derived by identifying the parallel computation in the prediction and correction processes of the RBE. A belief fusion technique, which fuses not only the observation information but also the target motion information, has hen been proposed. The proposed DTFLOP modeling is validated using the proposed parallel grid-based RBE technique with the GPU implementation by comparing the estimated time cost with the actual time cost of the parallel grid-based RBE. The superiority of the proposed parallel grid-based RBE technique is investigated by a number of numerical examples in comparison with the conventional grid-based RBE technique. The belief fusion technique is examined by a simulated target search and rescue test and it is observed to maintain more information of the target compared with the conventional observation fusion technique and eventually leads to the better performance of the target search and rescue. For the full-field measurement system a novel parallel DCT full-field measurement technique for measuring the displacement and strain field on the deformed surface of a structure is proposed. The proposed parallel DCT full-field measurement technique measures the displacement and strain field by tracking the centroids of the marked dots on the deformed surface. It identifies and develops the parallel computation in the image analysis and the field estimation processes and then is implemented into the GPU to accelerate the conventional full-field measurement techniques. The detail strategy of the GPU implementation is also developed and presented. The corresponding software package, which also includes a graphic user interface, and the hardware system consist of two digital cameras, LED lights and adjustable support legs to accommodate indoor or outdoor experimental environments are proposed. The proposed DTFLOP modeling is applied to the proposed parallel DCT full-field measurement technique to estimate its performance and the well match with the actual performance demonstrates the DTFLOP modeling. A number of both simulated and real experiments, including the tensile, compressive and bending experiments in the laboratory and outdoor environments, are performed to validate and demonstrate the proposed parallel DCT full-field measurement technique. Ph. D.

The advent of finite element methods has changed the tire industry's design process over the past three decades. Analyses, previously impractical using analytical methods and physically limited by experimental methods, can now be performed using computational methods. This decreases the cost and time associated with bringing a new design to the marketplace; however some physical testing is still required to validate the models. The design, fabrication, installation, and operation of a tire, suspension, and chassis test fixture (TiSCTeF) is detailed as part of this study. This fixture will support the validation of effective, parametric finite element models currently under development, as well as the design and testing of suspension and chassis components for the Virginia Tech Formula SAE team. The fixture is designed to use the Formula SAE race car as the test platform. Initially, the fixture is capable of performing static load-deflection and free-rolling tire tests. Provision has been made in the design for incremental upgrades to support cornering tests and additional instrumentation. An initial load-deflection test has proven that the fixture is capable of creating reproducible data sets. Specific recommendations are made concerning the improvement of data quality for future tests. This study also presents a process for analyzing existing tire cornering data and eliminating anomalies to improve the effectiveness of normalization techniques found in the literature. The process is shown to collapse tire cornering data, which is partially ill- conditioned, onto master curves that consistently display the effect of inclination angle and tire inflation pressure on tire response. Master of Science

This study provides a comprehensive performance analysis of Wave-Adaptive Modular Vessels (WAM-V) using simulations and testing data. WAM-Vs are a new class of marine technology that build upon the advantages of lightweight, low-draft, catamaran construction. Independent suspensions above the hulls isolate the passengers and equipment from the harsh sea environment. Enhanced understanding of the relationship between suspension and vehicle performance is critical for future missions of interest to the U.S. Navy. Throughout this study, the dynamic properties of three different WAM-Vs were evaluated. A multi-body dynamics simulation was developed for the 100-ft WAM-V 'Proteus' based on an automotive 4-post shaker rig. The model was used to characterize the sensitivities of different suspension parameters and as a platform for future models. A 12-ft unmanned surface vessel (USV) was instrumented and sea trials were conducted in the San Francisco Bay. A dynamic 4-post simulation was created for the USV using displacement inputs calculated from acceleration data via a custom integration scheme. The data was used to validate the models by comparing the model outputs to sensor data from the USV. A vertical hydrodynamics testing rig was developed to investigate the interaction between the pontoons and the water surface to improve the understanding of how hydrodynamic forces affect suspension performance. A model was created to accurately simulate the hydrodynamic forces that result from vertical pontoon motion. The model was then scaled to fit a 33-ft WAM-V prototype. The 33-ft WAM-V was instrumented and sea trials were conducted in Norfolk, VA. The WAM-V's suspension was upgraded based on the testing results. A 2-post rig was also built for evaluating the 33-ft WAM-V's dynamics. Two dynamic models were made for the 33-ft WAM-V to evaluate different suspension designs. The results from this study have numerous impacts on the naval community and on the development of WAM-Vs. The methodology for testing and evaluation will allow for future WAM-V designs to be compared under controlled circumstances. The performance of WAM-Vs can then be compared against conventional platforms to determine their suitability for future missions. Simulation development will enable future WAM-Vs to be evaluated prior to undergoing sea trials. The hydrodynamic models become a powerful design tool that can be easily scaled and combined with the 4-post models. By providing the simulations and test data to future vessel designers, the designers will be able to intelligently evaluate numerous iterations early in the design phase, improving performance and safety. Ph. D.

Wavelet intensity based algorithm developed previously at VirginiaTech has been furthered and paired with an SVM based classifier. The wavelet intensity algorithm acts as a feature extraction algorithm. The wavelet transform is an effective tool as it allows one to narrow down upon the transient, high frequency events and is able to tell their exact location in time. According to prior work done in the field of signal processing, the local regularities of a signal can be estimated using a Lipchitz exponent at each time step of the signal. The local Lipchitz exponent can then be used to generate the wavelet intensity factor values. For each vertical acceleration value, corresponding to a specific location on the track, we now have a corresponding intensity factor. The intensity factor corresponds to break-no break information and can now be used as a feature to classify the vertical acceleration as a fault or no fault. Support Vector Machines (SVM) is used for this binary classification task. SVM is chosen as it is a well-studied topic with efficient implementations available. SVM instead of hard threshold of the data is expected to do a better job of classification without increasing the complexity of the system appreciably. Master of Science

The vertical force generated from terrain-tire interaction has long been of interest for vehicle dynamic simulations and chassis development. As the terrain serves as the main excitation to the suspension system through pneumatic tire, proper terrain and tire models are required to produce reliable vehicle response. Due to the high complexity of the tire structure and the immense size of a high fidelity terrain profile, it is not efficient to calculate the terrain-tire interaction at every location. The use of a simpler tire model (e.g. point follower tire model) and a pre-filtered terrain profile as equivalent input will considerably reduce the simulation time. The desired produced responses would be nearly identical to the ones using a complex tire model and unfiltered terrain, with a significant computational efficiency improvement. In this work, a terrain pre-filtering technique is developed to improve simulation efficiency while still providing reliable load prediction. The work is divided into three parts. First a stochastic gridding method is developed to include the measurement uncertainties in the gridded terrain profile used as input to the vehicle simulation. The obtained uniformly spaced terrain is considered probabilistic, with a series of gridding nodes with heights represented by random variables. Next, a constraint mode tire model is proposed to emulate the tire radial displacement and the corresponding force given the terrain excitation. Finally, based on the constraint mode tire model, the pre-filtering technique is developed. At each location along the tire's path, the tire center height is adjusted until the spindle load reaches a pre-designated constant load. The resultant tire center trajectory is the pre-filtered terrain profile and serves as an equivalent input to the simple tire model. The vehicle response produced by using the pre-filtered terrain profile and the simple tire model is analyzed for accuracy assessment. The computational efficiency improvement is also examined. The effectiveness of the pre-filtering technique is validated on probabilistic terrain by using different realizations of terrain profiles. It is shown through multiple profiles that the computational efficiency can be improved by three orders of magnitude with no statistically significant change in resulting loading. Ph. D.

The dynamic behavior of a vehicle is predominantly controlled by the forces and moments generated at the contact patch between the tire and the road surface. As a result, tire characteristics can dramatically change vehicle response, especially during maneuvers that yields the tires to reach to the limits of its adhesion capacity. To assist the driver in such cases and to prevent other possible instability scenarios, various vehicle control systems e.g. anti-lock brakes (ABS), stability controllers (ESP, ESC) or rollover mitigation schemes are introduced, which are generally known as active vehicle safety systems. Based on the above facts, one can easily come to the conclusion that to improve upon the current control algorithms developed for the technology in use; a vehicle control system design requires accurate knowledge of the tire states. This study proposes the use of a smart tire system that can provide information on momentary variation of tire features through the sensor units attached directly on the tire and develops control algorithms based on this information to assure the match-up between tire and controller dynamics. A prototype smart tire system was developed for field testing and for detailed analysis of its potential. Based on the collected prototype data, novel observer and controller schemes were developed to obtain dynamic tire state information and to improve vehicle handling performance. The proposed algorithms were implemented and evaluated using numerical analysis in Matlab/SimulinkR environment. For a more realistic simulation environment, vehicle models were integrated from Mechanical Simulations CarSimR® software suite. Ph. D.

Tires play an extremely important role in the operation of a vehicle as they transmit forces between the ground and the vehicle. Consistent efforts have been made over the years towards modeling and simulation of tires and more recently, there has been an increasing need to understand the transient response of tires to various high-frequency events such as anti-lock braking and short-wavelength disturbances from the road. Major thrust has been provided by the tire industry to develop simulation models that accurately predict the dynamic response of tires without the use of computationally intensive tools such as FEA. The objective of this research is to explain the development, implementation and validation of a simulation tool based on a dynamic tire model that would assist in the analysis of the effect of tire belt vibrations on the braking performance of a vehicle. A rigid ring tire model, tandem elliptical cam enveloping model and a rule-based ABS model have been developed for this purpose. These were combined together in a quarter vehicle model and implemented in Matlab-Simulink. These models were developed for adaptation with CarSim to provide a simulation tool that can be utilized in both tire and vehicle design processes. In addition to model implementation, a parameterization procedure was developed to estimate the parameters of the rigid ring tire and enveloping model based on experimental data for a given tire. Validation studies have also been performed to ensure the accuracy and validity of the tire model. Following this, the braking performance of ABS under different road surfaces were evaluated. Based on the simulation results, final conclusions were drawn with regards to the analysis and detailed recommendations for future work directed towards the improvement of the tool were provided. Master of Science

The main goal of this study is to improve the understanding of the interaction between a pneumatic tire and deformable terrain. A design of experiments has been implemented, that gives insight into the effect of individual tire and soil parameters, specifically wheel slip, normal load, inflation pres-sure, and soil compaction, as well as into the effect of combinations of such parameters on the tire and soil behavior. The results of such test data is exceedingly relevant, providing significant infor-mation to tire design for tire manufacturers, to users for operating conditions selection, as well as providing modeling parameters for tire models. Moreover, experimental investigation of tire-soil interaction provides validation data for tire models operating under similar conditions. In support of the validation of a soft soil tire model currently being developed at Virginia Tech under the auspices of the Automotive Research Center, experimental work has been performed on a low-speed, indoor single-wheel tester built to investigate studies in terramechanics. The terramechanics rig provides a well-controlled environment to assure repeatable testing conditions and void vehicle component ef-fects. The test tire for the rig is instrumented with a wireless sensory system that measures tire de-flection at the contact patch; combining this system with other instruments of the rig allows accurate estimations of wheel sinkage. A methodical soil preparation procedure has rendered great data to analyze several relations, such as the drawbar pull and the sinkage dependency on slip. The data col-lected indicated that, when looking at the effect of individual parameters, by increasing the soil com-paction, the normal load, and by decreasing the inflation pressure will result in a higher normalized drawbar pull. A higher normal load under all conditions consistently lowered the max tire sinkage depth. The sinkage has increased dramatically with the slip ratio, growing threefold larger at high slip (70-90%) when compared to lower slip (0-5%) ratios. Master of Science

A differential steered, 13.6 kg robot was developed as an intelligent tire testing system and was used to investigate the potential of using piezoelectric film sensors in small tube-type pneumatic tires to characterize tire-ground interaction.One focus of recent research in the tire industry has been on instrumenting tires with sensors to monitor the tire, vehicle, or external environment. On small robots, tire sensors that measure the forces and deflections in the contact patch could be used to improve energy efficiency and/or mobility during a mission.The robot was assembled from a SuperDroid Robots kit and instrumented with low-cost piezoelectric film sensors from Measurement Specialties between the inner tube and the tire. An unlaminated and a laminated sensor were placed circumferentially along the tread and an unlaminated sensor was placed along the sidewall. A slip ring transferred the signals from the tire to the robot. There, the signal conditioning circuit extended the time constant of the sensors and filtered electromagnetic interference. The robot was tested with a controlled power sequence carried out on polished cement, ice, and sand at three power levels, two payload levels, and with two tire sizes.The results suggest that the sensors were capable of detecting normal pressure, deflection, and/or longitudinal strain. Added payload increased the amplitude of the signals for all sensors. On the smaller tires, sensors generally recorded a smaller, wider signal on sand compared to cement, indicating the potential to detect contact patch pressure and length. The signals recorded by the unlaminated sensor along the tread of the smaller tire were lower on ice compared to cement, indicating possible sensitivity to tractive force. Results were less consistent for the larger tires, possibly due to the large tread pattern. Master of Science

Currently, in the railroad industry, the lack of electrical sources in freight cars is a problem that has yet to find practical solutions. Although the locomotive generates electricity to power the traction motors and all the equipment required to operate the train, the electrical power cannot, in a practical manner, be carried out along the length of the train, leaving freight cars unpowered. While this has not been a major issue in the past, there is a strong interest in equipping modern cars with a myriad of devices intended to improve safety, operational efficiency, or health monitoring, using devices such as GPS, active RFID tags, and accelerometers. The implementation of such devices, however, is hindered by the unavailability of electricity. Although ideas such as Timken's generator roller bearing or solar panels exist, the railroads have been slow in adopting them for different reasons, including cost, difficulty of implementation, or limited capabilities. The focus of this research is on the development of vibration-based electromechanical energy harvesting systems that would provide electrical power in a freight car. With size and shape similar to conventional shock absorbers, these devices are designed to be placed in parallel with the suspension elements, possibly inside the coil spring, thereby maximizing unutilized space. When the train is in motion, the suspension will accommodate the imperfections of the track, and its relative velocity is used as the input for the harvester, which converts the mechanical energy to useful electrical energy. Beyond developing energy harvesters for freight railcar primary suspensions, this study explores track wayside and miniature systems that can be deployed for applications other than railcars. The trackside systems can be used in places where electrical energy is not readily available, but where, however, there is a need for it. The miniature systems are useful for applications such as bicycle energy. Beyond the design and development of the harvesters, an extensive amount of laboratory testing was conducted to evaluate both the amount of electrical power that can be obtained and the reliability of the components when subjected to repeated vibration cycles. Laboratory tests, totaling more than two million cycles, proved that all the components of the harvester can satisfactorily survive the conditions to which they are subjected in the field. The test results also indicate that the harvesters are capable of generating up to 50 Watts at 22 Vrms, using a 10-Ohm resistor with sine wave inputs, and over 30 Watts at peak with replicated suspension displacements, making them suitable to directly power onboard instruments or to trickle charge a battery. Ph. D.

Accurate terrain models provide the chassis designer with a powerful tool to make informed design decisions early in the design process. During this stage, engineers are challenged with predicting vehicle loads through modeling and simulation. The accuracy of these simulation results depends not only on the fidelity of the model, but also on the excitation to the model. It is clear that the terrain is the main excitation to the vehicle [1]. The inputs to these models are often based directly on physical measurements (terrain profiles); therefore, the terrain measurements must be as accurate as possible. A collection of novel methods can be developed to aid in the study and application of 3D terrain measurements, which are dense and non-uniform, including efficient gridding, stochastic modeling, and compact characterization. Terrain measurements are not collected with uniform spacing, which is necessary for efficient data storage and simulation. Many techniques are developed to help effectively grid dense terrain point clouds in a curved regular grid (CRG) format, including center and random vehicle paths, sorted gridding methods, and software implementation. In addition, it is beneficial to characterize the terrain as a realization of an underlying stochastic process and to develop a mathematical model of that process. A method is developed to represent a continuous-state Markov chain as a collection of univariate distributions, to be applied to terrain road profiles. The resulting form is extremely customizable and significantly more compact than a discrete-state Markov chain, yet it still provides a viable alternative for stochastically modeling terrain. Many new simulation techniques take advantage of 3D gridded roads along with traditional 2D terrain profiles. A technique is developed to model and synthesize 3D terrain surfaces by applying a variety of 2D stochastic models to the topological components of terrain, which are also decomposed into frequency bandwidths and down-sampled. The quality of the synthetic surface is determined using many statistical tests, and the entire work is implemented into a powerful software suite. Engineers from many disciplines who work with terrain surfaces need to describe the overall physical characteristics compactly and consistently. A method is developed to characterize terrain surfaces with a few coefficients by performing a principal component analysis, via singular value decomposition (SVD), to the parameter sets that define a collection of surface models. Master of Science

The application of Model Reference Adaptive Control (MRAC) for train dynamic braking is investigated in order to control dynamic braking forces while remaining within the allowable adhesion and coupler forces. This control method can accurately determine the train braking distance. One of the critical factors in Positive Train Control (PTC) is accurately estimating train braking distance under different operating conditions. Accurate estimation of the braking distance will allow trains to be spaced closer together, with reasonable confidence that they will stop without causing a collision. This study develops a dynamic model of a train consist based on a multibody formulation of railcars, trucks (bogies), and suspensions. The study includes the derivation of the mathematical model and the results of a numerical study in Matlab. A three-railcar model is used for performing a parametric study to evaluate how various elements will affect the train stopping distance from an initial speed. Parameters that can be varied in the model include initial train speed, railcar weight, wheel-rail interface condition, and dynamic braking force. Other parameters included in the model are aerodynamic drag forces and air brake forces. An MRAC system is developed to control the amount of current through traction motors under various wheel/rail adhesion conditions while braking. Minimizing the braking distance of a train requires the dynamic braking forces to be maximized within the available wheel/rail adhesion. Excessively large dynamic braking can cause wheel lockup that can damage the wheels and rail. Excessive braking forces can also cause large buff loads at the couplers. For DC traction motors, an MRAC system is used to control the current supplied to the traction motors. This motor current is directly proportional to the dynamic braking force. In addition, the MRAC system is also used to control the train speed by controlling the synchronous speed of the AC traction motors. The goal of both control systems for DC and AC traction motors is to apply maximum available dynamic braking while avoiding wheel lockup and high coupler forces. The results of the study indicate that the MRAC system significantly improves braking distance while maintaining better wheel/rail adhesion and coupler dynamics during braking. Furthermore, according to this study, the braking distance can be accurately estimated when MRAC is used. The robustness of the MRAC system with respect to different parameters is investigated, and the results show an acceptable robust response behavior. Ph. D.

The primary purpose of this research is to investigate the effectiveness of a scaled roller rig for accurately assessing the contact mechanics and dynamics between a profiled steel wheel and rail, as is commonly used in rail vehicles. The established creep models of Kalker and Johnson and Vermeulen are used to establish correction factors, scaling factors, and transformation factors that allow us to relate the results from a scaled rig to those of a tangent track. �Correction factors, which are defined as the ratios of a given quantity (such as creep coefficient) between a roller rig and a track, are derived and used to relate the results between a full-size rig and a full-size track. Scaling factors are derived to relate the same quantities between roller rigs of different scales. Finally, transformation factors are derived by combining scaling factors with correction factors in order to relate the results from a scaled roller rig to a full-size tangent track. Close-end formulae for creep force correction, scaling, and transformation factors are provided in the thesis, along with their full derivation and an explanation of their limitations; these formulae can be used to calculate the correction factors for any wheel-rail geometry and scaling. For Kalker's theory, it is shown that the correction factor for creep coefficients is strictly a function of wheel and rail geometry, primarily the wheel and roller diameter ratio. For Johnson and Vermeulen's theory, the effects of creepage, scale, and load on the creep force correction factor are demonstrated. �It is shown that INRETS' scaling strategy causes the normalized creep curve to be identical for both a full-size and a scaled roller rig. �It is also shown that the creep force correction factors for Johnson and Vermeulen's model increase linearly with creepage, starting with the values predicted by Kalker's theory. �Therefore, Kalker's theory provides a conservative estimate for creep force correction factors. �A case study is presented to demonstrate the creep curves, as well as the correction and transformation factors, for a typical wheel-rail configuration. �Additionally, two studies by other authors that calculate the correction factor for Kalker's creep coefficients for specific wheel-rail geometries are reviewed and show full agreement with the results that are predicted by the formulae derived in this study. �Based on a review of existing and past roller rigs, as well as the findings of this thesis, a number of recommendations are given for the design of a roller rig for the purpose of assessing the wheel-rail contact mechanics. �A scaling strategy (INRETS') is suggested, and equations for power consumption of a roller rig are derived. Recommendations for sensors and actuators necessary for such a rig are also given. Special attention is given to the resolution and accuracy of velocity sensors, which are required to properly measure and plot the creep curves. Master of Science

Many common statistical techniques for modeling multidimensional dynamic data sets can be seen as variants of one (or multiple) underlying linear/nonlinear model(s). These statistical techniques fall into two broad categories of supervised and unsupervised learning. The emphasis of this dissertation is on unsupervised learning under multiple generative models. For linear models, this has been achieved by collective observations and derivations made by previous authors during the last few decades. Factor analysis, polynomial chaos expansion, principal component analysis, gaussian mixture clustering, vector quantization, and Kalman filter models can all be unified as some variations of unsupervised learning under a single basic linear generative model. Hidden Markov modeling (HMM), however, is categorized as an unsupervised learning under multiple linear/nonlinear generative models. This dissertation is primarily focused on hidden Markov models (HMMs). On the first half of this dissertation we study enhancements on the theory of hidden Markov modeling. These include three branches: 1) a robust as well as a closed-form parameter estimation solution to the expectation maximization (EM) process of HMMs for the case of elliptically symmetrical densities; 2) a two-step HMM, with a combined state sequence via an extended Viterbi algorithm for smoother state estimation; and 3) a duration-dependent HMM, for estimating the expected residency frequency on each state. Then, the second half of the dissertation studies three novel applications of these methods: 1) the applications of Markov switching models on the Bifurcation Theory in nonlinear dynamics; 2) a Game Theory application of HMM, based on fundamental theory of card counting and an example on the game of Baccarat; and 3) Trust modeling and the estimation of trustworthiness metrics in cyber security systems via Markov switching models. As a result of the duration dependent HMM, we achieved a better estimation for the expected duration of stay on each regime. Then by robust and closed form solution to the EM algorithm we achieved robustness against outliers in the training data set as well as higher computational efficiency in the maximization step of the EM algorithm. By means of the two-step HMM we achieved smoother probability estimation with higher likelihood than the standard HMM. Ph. D.

Early detection of rail defects is necessary for preventing derailments and costly damage to the train and railway infrastructure. A rail surface flaw can quickly propagate from a small fracture to a broken rail after only a few train cars have passed over it. Rail defect detection is typically performed by using an instrumented car or a separate railway monitoring vehicle. Rail surface irregularities can be measured using accelerometers mounted to the bogie side frames or wheel axles. Typical signal processing algorithms for detecting defects within a vertical acceleration signal use a simple thresholding routine that considers only the amplitude of the signal. As a result, rail surface defects that produce low amplitude acceleration signatures may not be detected, and special track components that produce high amplitude acceleration signatures may be flagged as defects. The focus of this research is to develop an intelligent signal processing algorithm capable of detecting and classifying various rail surface irregularities, including defects and special track components. Three algorithms are proposed and validated using data collected from an instrumented freight car. For the first two algorithms, one uses a windowed Fourier Transform while the other uses the Wavelet Transform for feature extraction. Both of these algorithms use an artificial neural network for feature classification. The third algorithm uses the Wavelet Transform to perform a regularity analysis on the signal. The algorithms are validated with the collected data and shown to out-perform the threshold-based algorithm for the same data set. Proper training of the defect detection algorithm requires a large data set consisting of operating conditions and physical parameters. To generate this training data, a dynamic wheel-rail interaction model was developed that relates defect geometry to the side frame vertical acceleration signature. The model was generated by using combined systems dynamic modeling, and the system was solved with a developed combined lumped and distributed parameter system numerical approximation. The broken rail model was validated with real data collected from an instrumented freight car. The model was then used to train and validate the defect detection methodologies for various train and rail physical parameters and operating conditions. Ph. D.

The contact between the tire and the road is the key enabler of vehicle acceleration, deceleration and steering. However, under the circumstances of sudden changes to the road conditions, the driver`s ability to maintain control of the vehicle maybe at risk. In many cases, this requires intervention from the chassis control systems onboard the vehicle. Although these systems perform well in a variety of situations, their performance can be improved if a real-time estimate of the tire-road contact parameters (ranging from kinematic conditions of the tire to its dynamic properties) are available. At the present stage of development, tire-road contact parameters are indirectly estimated using observers based on vehicle dynamics measurements (acceleration, yaw and roll rates, suspension deflections, etc). Although these methods present a relatively accurate solution, they rely heavily on tire and vehicle kinematic formulations and break down in case of abrupt changes in the measured quantities. To address this problem, researchers have been developing certain sensor based advanced tire concepts for direct measurement of the tire-road contact parameters. Thus the new terms "Intelligent Tire" and "Smart Tire", which mean online tire monitoring are thus enjoying increasing popularity among automotive manufacturers and formed the motivation for this thesis to explore the possibility of developing an intelligent tire system. The development of the so called "intelligent tire/ smart tire system" is expected to spur the development of a new generation of vehicle control system with modified control strategies, leveraging information directly coming from the interface between the tire and the road, and in turn significantly reducing the risk of accidents. The specific contributions of this thesis include the following: • Development of an intelligent tire system, with a special attention to development of measurement and sensor feature extraction methodologies of acceleration signals coming from sensors fixed to the tire innerliner • Design of an integrated vehicle state estimator for application to global chassis control • Development of a model-based tire-road friction estimation algorithm • Development of an intelligent tire based adaptive wheel slip controller for anti-lock brake system (ABS) • Development of a piezoelectric vibration energy harvesting system with an adaptive frequency tuning mechanism for intelligent tires Master of Science

In order to provide data for non-rolling tire models that are used in computer simulations of vehicle dynamics, a tire test rig is designed and manufactured which attaches to an MTS kinematics and compliance machine. This test rig is developed for the purpose of characterizing the loaded radius, overturning moment, and displacement of multiple tires in the vertical, lateral, and longitudinal test axes. Equations are developed and used to fit these parameters for the purpose of representing them in non-rolling vehicle simulation models. Master of Science

A method to adapt the Generalized Predictive Control parameters to improve broadband disturbance rejection was developed and tested. The effect of the parameters on disturbance rejection has previously been poorly understood and a trial and error method was used to achieve adequate results. This dissertation provides insight on the effect of the parameters, as well as an adaptive tuning method to adjust them. The study begins by showing the effect of the four GPC parameters, the control and prediction horizons, control weighting &lambda , and order, on the disturbance rejection and control effort of a vibrating plate. It is shown that the effect of increases in the control and prediction horizon becomes negligible after a certain point. This occurs at nearly the same point for a variety of &lambda 's and orders, and hence they can be eliminated from the tuning space. The control effort and closed-loop disturbance rejection are shown to be highly dependant on &lambda and order, thereby becoming the parameters that need to be tuned. The behavior is categorized into various groups and further investigated. The pole and zero locations of the closed-loop system are examined to reveal how GPC gains control and how it can fail for non-minimum phase plants. A set of fuzzy logic modules is developed to adapt &lambda with order fixed, and conversely to adapt order with &lambda fixed. The effectiveness of the method is demonstrated in both numerical simulations and laboratory experiments. Ph. D.

A drawbar pull (DP) test procedure was developed at the NASA Glenn Research Center (GRC) for testing and developing designs for off-road vehicles. The motivation was to develop a procedure that would produce repeatable results and could be replicated by other researchers. While developing the test methodology, it became apparent that there was a certain degree of scatter in the results among identical tests. In order to characterize the disparities, an experimental study was conducted consisting of systematically varying specific test parameters. The selected performance metric was the DP-TR (travel reduction) relation. The selected parameters were: 1) the starting terrain condition, 2) the distance traveled by the vehicle under an applied, constant DP force, and 3) the density of the prepared terrain. Respectively, these parameters were selected to observe: 1) how differences in the starting area, or "launch pad," would affect the resulting performance of a test, 2) if a steady-state region of performance exists and how does performance change with the distance traveled, and 3) the relationship between prepared terrain density and performance. These experiments were conducted in a dry, granular, cohesionless, silica based soil called the GRC-1 Lunar Soil Simulant. The results of these studies were that the variations in both the starting terrain condition and the distance traveled did not significantly affect performance. The relationship between performance and terrain density was that only in a region of low density was the TR constant; subsequently, the TR decreased steadily with increasing density. Master of Science

Catamarans provide vast deck space, high thrust efficiency, and excellent transverse stability, however, in rough conditions they can be susceptible to deck slamming from head seas or bow diving in following seas and a pitch-roll coupling effect that can lead to uncomfortable corkscrew motion under bow-quartering seas. A new class of catamaran called Wave-Adaptive Modular Vessels (WAM-V™) aims to help mitigate oceanic input from the cabin by allowing for the relative motion of components not common to classic catamaran design. This thesis presents a set of multi-body dynamics simulation models created for two active WAM-Vs™ along with analysis on their suspension characteristics. Both models provide conclusive and realistic results, with the final model being validated against on-water testing data from a 12-ft unmanned prototype WAM-V. The first of these simulations serves primarily as a tool to evaluate WAM-V™ response characteristics with respect to a variety of parametric variations. The modeling environment is highlighted along with details of the parametric simulation and how it was created. The results fall in line with our expectations and are presented along with analysis of the sensitivity of each parameter at three longitudinal locations. The final simulation attempts to model the response of a 12-ft unmanned surface vessel (USV) prototype of the WAM-V™ configuration. Testing data is collected, processed, and applied to the model for validation of its prediction accuracy. The results of the sea tests indicate that the simulation model performs well in predicting USV motions at sea. Future considerations for testing WAM-Vs™ can include changes in suspension and mass parameters as well as limiting particular degrees-of-freedom by making their joints rigid. Master of Science

A novel approach for estimating alertness levels from speech and tagging them with a reliability component has been developed. The Fatigue Quotient and Believability are both derived from the time series analysis of the speech signal in the communication between the operator and dispatch. Operator attention is the most important human factor element for safe transportation operations. In addition to substance abuse, illness and intoxication fatigue is a major contributing factor to the decrease of attention. The goal of this study was to develop a means to detect and estimate fatigue levels of railroad operating personnel during on-duty hours. This goal continues to gain importance with new efforts from the government to expand rail transportation operations as a tool for high speed mass transportation in urban areas. Previous research has shown that sleeping disorders, reduced hours of rest and disrupted circadian rhythms lead to significantly increased fatigue levels which manifest themselves in alterations of speech patterns as compared to alert states of mind. In this study vocal indicators of fatigue are extracted from the speech signal and Fuzzy Logic is used to generate an estimate of the cognitive state of the train conductor. The output is tagged with a believability metric based on its behavior with respect to previous outputs and a fully alert state. Communication between the conductor and dispatch over radio provides an unobtrusive way of accessing the speech signal through existing speech infrastructure. The speech signal is discretized and processed through a digital signal processing algorithm, which extracts speech metrics from the signal that were determined to be indicative of fatigue levels. Speech metrics include, but are not limited to, speech duration, silence duration, word production rate, phrase gap duration, number of words per phrase and speech intensity. A fuzzy logic minimum inference engine maps the inputs to an output through an empirically determined rule base. The rule base and the associated membership functions were derived from batch mode and real time testing and the subsequent tuning of parameters to refine the detection of changes in patterns. To increase the validity and transparency of the output time series analysis is used to create the believability metric. A moving average filter eliminates the short term fluctuations and determines the long term trend of the output. A moving standard deviation estimation quantifies instantaneous fluctuations and provides a measure of the difference to a nominal alertness state. A real time version of the algorithm was developed and prototyped on a generic, low cost and scalable hardware platform. Rapid Prototyping was realized through the Matlab/Simulink xPC Target toolbox which allowed for instant real time code generation, testing and modification. This testing environment together with batch mode testing was used to extensively test and fine tune parameters to improve the performance of the algorithm. A testing procedure was developed and standardized to collect data and tune the parameters of the algorithm. As a high level goal it was proven that the concept of digital signal processing and Fuzzy Logic can be utilized to detect changes in speech and estimate alertness levels from it. Furthermore, this study has proven that the framework to run such an analysis continuously as a monitoring function in locomotive cabins is feasible and can be realized with relatively inexpensive hardware. The development, implementation and testing process conducted for this project is explained and results are presented here. Ph. D.

For decades vehicle control has been extensively studied to investigate and improve vehicle stability and performance. Such controllers are designed to improve driving safety while the driver is still in control of the vehicle. It is known that human drivers are capable to learn and adapt to their built-in vehicle controller in order to improve their control actions based on their past driving experiences with the same vehicle controller. Although the learning curve varies for different human drivers, it results in a more constructive cooperation between the human driver and the computer-based vehicle controller, leading to globally optimal vehicle stability. The main intent of this research is to develop a novel cooperative interaction model between the human driver and vehicle controller in order to obtain globally optimal vehicle steering and lateral control. Considering the vehicle driver-controller interactions as a common two-player game problem where both players attempt to improve their payoffs, i.e., minimize their objective functions, the Game Theory approach is applied to obtain the optimal driver's steering inputs and controller's corrective yaw moment. Extending this interaction model to include more realistic scenarios, the model is discretized and a road preview model is added to account for the driver's preview-time characteristic. Also, a robust interaction model is developed to stabilize the vehicle performance while taking bounded uncertainty effects in driver's steering behavior into consideration using the Integral Sliding Mode control methodology. For evaluation purposes, a nonlinear vehicle dynamics model is developed that captures nonlinear tire characteristics and includes driver steering controllability and vehicle speed control systems such as cruise control, differential braking, and anti-lock braking systems. A graphical user interface (GUI) is developed in MATLAB to ease the use of the vehicle model and hopefully encourage its widespread application in the future. Simulation results indicate that the proposed cooperative interaction model, which is the end-product of human driver's and vehicle controller's mutual understanding of each other's objective and performance quality, results in more optimal and stable vehicle performance in lateral and yaw motions compared to the existing LQR controllers that tend to independently optimize the driver and vehicle controller inputs. Ph. D.

This research undertakes the problem of vibration control of vehicular and structural systems using intelligent materials and controllable devices. Advanced modeling tools validated with experimental test data are developed to help with understanding the fundamentals as well as advanced and novel applications of smart and conventional suspension systems. The project can be divided into two major parts. The first part is focused on development of novel smart suspensions using Magneto-Rheological (MR) fluids in unique configurations in order to improve efficiency, controllability, and safety of today's vehicles. In this part of the research, attention is paid to fundamentals as well as advanced applications of MR technology. Extensive rheological studies, both theoretical and experimental, are performed to understand the basic behaviors of MR fluids as complex non-Newtonian fluids in novel applications. Using the knowledge obtained from fundamental studies of MR fluids, unique application concepts are investigated that lead to design, development, and experimental testing of two new classes of smart devices: MR Hybrid Dampers and MR Squeeze Mounts. Multiple generations of these devices are built and tested as proof of concept prototypes. Advanced physics-based mathematical models are developed for these devices. Experimental test data are used to validate the models and great agreement is obtained. The models are used as design tools at preliminary as well as detailed design stages of device development. The significant finding in this part of the research is that MR fluids can deliver a much larger window of controllable force in squeeze mode compared to shear and valve modes which can be used in various applications. The second part of the research is devoted to the development of innovative design tools for suspension design and tuning. Various components of suspension systems are studied and modeled using a new physics-based modeling approach. The component of main interest is the shim stack assembly in hydraulic dampers which is modeled using energy and variational methods. A major finding is that the shims should be modeled individually in order to represent the sliding effects properly when the shim stack is deflected. Next, the individual component models are integrated into a full suspension model. This model is then used as a tool for suspension design, synthesis, and tuning. Using this design tool, suspension engineers in manufacturing companies and other industrial sections can easily perform parametric studies without the need to carry out time consuming and expensive field and laboratory tests. Ph. D.