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.

Tire-Pavement Interaction Noise (TPIN) becomes the main noise source contributor for passenger vehicles traveling at speeds above 40 kph. Therefore, it represents one of the main contributors to noise environmental pollution in residential areas nearby highways. TPIN has been subject of exhaustive studies since the 1970s. Still, almost 50 years later, there is still not an accurate way to model it. This is a consequence of a large number of noise generation mechanisms involved in this phenomenon, and their high complexity nature. It is acknowledged that the main noise mechanisms involve tire vibration, and air pumping within the tire tread and pavement surface. Moreover, TPIN represents the only vehicle noise source strongly affected by an external factor such as pavement roughness. For the last decade, new machine learning algorithms to model TPIN have been implemented. However, their development relay on experimental data, and do not provide strong physical insight into the problem. This research studied the correct configuration of such tools. More specifically, Artificial Neural Network (ANN) configurations were studied. Their implementation was based on the problem requirements (acoustic sound pressure prediction). Moreover, a customized neuron configuration showed improvements on the ANN TPIN prediction capabilities. During the second stage of this thesis, tire noise test was undertaken for different tires at different pavements surfaces on the Virginia Tech SMART road. The experimental data was used to develop an approach to account for the pavement profile when predicting TPIN. Finally, the new ANN configuration, along with the approach to account for pavement roughness were complemented using previous work to obtain what is the first reasonable accurate and complete tool to predict tire noise. This tool uses as inputs: 1) tire parameters, 2) pavement parameters, and 3) vehicle speed. Tire noise narrowband spectra for a frequency range of 400-1600 Hz is obtained as a result. / Master of Science / Tire-Pavement Interaction Noise (TPIN) becomes the main noise source contributor for passenger vehicles traveling at speeds above 40 kph. Therefore, it represents one of the main contributors to noise environmental pollution in residential areas nearby highways. TPIN has been subject of exhaustive studies since the 1970s. Still, almost 50 years later, there is still not an accurate way to model it. This is a consequence of a large number of noise generation mechanisms involved in this phenomenon, and their high complexity nature. It is acknowledged that the main noise mechanisms involve tire vibration, and air pumping within the tire tread and pavement surface. Moreover, TPIN represents the only vehicle noise source strongly affected by an external factor such as pavement roughness. For the last decade, machine learning algorithms, based on the human brain structure, have been implemented to model TPIN. However, their development relay on experimental data, and do not provide strong physical insight into the problem. This research focused on the study of the correct configuration of such machine learning algorithms applied to the very specific task of TPIN prediction. Moreover, a customized configuration showed improvements on the TPIN prediction capabilities of these algorithms. During the second stage of this thesis, tire noise test was undertaken for different tires at different pavements surfaces on the Virginia Tech SMART road. The experimental data was used to develop an approach to account for the pavement roughness when predicting TPIN. Finally, the new machine learning algorithm configuration, along with the approach to account for pavement roughness were complemented using previous work to obtain what is the first reasonable accurate and complete computational tool to predict tire noise. This tool uses as inputs: 1) tire parameters, 2) pavement parameters, and 3) vehicle speed.

The low frequency (0-500 Hz) automotive noise and vibration behavior is influenced by the rolling dynamics of the tire. Driven by pressing environmental concerns, the automotive industry has strived to innovate fuel-efficient and quieter powertrain systems over the last decade. This has eventually led to the prevalence of hybrid and electric vehicles. With the noise masking effect of the engine orders being absent, the interior structure-borne noise is dominated by the tire pavement interaction under 500 Hz. This necessitates an accurate estimation of rolling tire dynamics. To this date, there is no direct procedure available for modal analysis of rolling tires with tread patterns under realistic operating conditions. The present start-of-art laser vibrometer based non-contact measurements are limited to tread vibration measurement of smooth tires only in a lab environment. This study focuses on devising an innovative strategy to use a wireless Tire Cavity Accelerometer (TCA) and two optical sensors in a tire on drum setup with cleat excitation to characterize dynamics of tread vibration in an appreciably easier, time and cost-effective approach. In this approach, First, the TCA vibration signal in a single test run is clustered into several groups representing an array of virtual sensor position at different circumferential positions. Then modal identification has been performed using both parametric and non-parametric operational modal identification procedures. Furthermore, relevant conclusions are drawn about the observed modal properties of the tire under rolling including the limitations of the proposed method. The method proposed here, as is, can be applied to a treaded tire and can also be implemented in an on-road test setup. / Master of Science / The low frequency(0-500 Hz) interior noise and vibration of an automobile is primarily influenced by the dynamics of the rolling tire. In recent studies, the laser vibrometer with moving mirrors for measurement of vibration on the tread of a rotating tire has been used. However, these are limited to tires without tread pattern. In this study, an innovative experimental way of performing operational modal analysis using the Tire cavity Accelerometer (TCA) and optical sensors is presented. The proposed method is simpler in terms of instrumentation and cost and time-effective. This method, as is, can also be implemented in case of a treaded tire

ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California / Testing aircraft brake and tire systems often results in tire temperatures that makes the aircraft unsafe to approach (due to explosion risk) for up to 45 minutes; this complicates cost effective test execution. This paper describes work on a wireless sensor system that measures multiple tire temperatures and transmits the data to someone at a safe distance (>300 ft). The solution consists of a sensor patch adhered directly to the tire which measures the tire temperature. The patch transmits these measurements to off-tire reader/relay nodes that subsequently sends the data to a system controller and display device.

Thesis (Master)--İzmir Institute of Technology, İzmir, 2005 / Keywords: city hans, alteration, restitution, Ottoman Hans. Includes bibliographical references (leaves 183-185)

The purpose of this work has been to generate a method by which an automobile tire manufacturer can optimally allocate its weekly production ticket to its automatic tire-curing presses. The problem is of interest for the reason that the value of the objective function is markedly affected by the relative locations of tires amongst themselves. This consideration has negated the possibility of a solution being effected by the application of an algorithm for the classical linear assignment problem. In this work the problem has been formulated and solved as a quadratic assignment problem. The logic of this method of solution has been programmed and subsequently used to solve example problems, the results of which are extremely encouraging. / Thesis / Master of Engineering (MEngr)

The tire is one of the most important components of the vehicle. It has many functions, such as supporting the load of the vehicle, transmitting the forces which drive, brake and guide the vehicle, and acting as the secondary suspension to absorb the effect of road irregularities before transmitting the forces to the vehicle suspension. A tire is a complex reinforced rubber composite air container. The structure of the tire is very complex. It consists of several layers of synthetic polymer, many flexible filaments of high modulus cord, and glass fiber, which are bonded to a matrix of low modulus polymeric material. As the tire is the only component of the vehicle which makes contact with the road surface, almost all forces and moments acting on the vehicle must be transferred by the tire. To predict the dynamics of the vehicle, we need to know these forces and moments generated at the tire contact patch. Therefore, tire models that accurately describe this dynamic behavior are needed for vehicle dynamic simulation. Many researchers developed tire models for vehicle dynamic simulations; however, most of the development in tire modeling has been limited to deterministic steady-state on-road tire models. The research conducted in this study is concerned with the development of semi-empirical transient tire models for on-road and off-road vehicle simulations. The semi-empirical transient tire model is developed based on existed tire models, analytical tire structure mechanics analysis, and experimental data collected by various researchers. The tire models were developed for vehicle traction, handling and ride analysis. The theoretical mechanics analysis of the tire model focused on the determination of tire and terrain deformation. Then, the results are used together with empirical data to calculate the force response and the moment response. Moreover, the influence of parametric uncertainties in tire parameters on the tire-terrain interaction is investigated. The parametric uncertainties are quantified and propagated through the tire models using a polynomial chaos theory with a collocation approach. To illustrate the capabilities of the tire models developed, both deterministic and stochastic tire models are simulated for various scenarios and maneuvers. Numerically simulated results are analyzed from the perspective of vehicle dynamics. Such an analysis can be used in tire and vehicle development and design. / Ph. D.

Induced vibrations due to tire-pavement interaction are one of the main sources of vehicle exterior noise, especially near highways and main roads where traveling speeds are above 50 kph. Its dominant spectral content is approximately within 500-1500 Hz. However, accurate prediction tools within this frequency range are not available. Current methods rely on structural modeling of the complete tire using finite elements and modal expansion approaches that are accurate only at low frequencies. Therefore, alternative physically-based models need to be developed. This work proposes a new approach that incorporates wave behavior along the tire's circumferential direction, while modes are assumed along its transversal direction. The formulation for new infinite plate and cylindrical shell structural models of a tire is presented. These are capable of accounting for orthotropic material properties, different structural parameters between the belt and sidewalls, inflation pressure, and rotation of the tire. In addition, a new contact model between the pavement and the tire is developed presented. The excitation of the tire due to the impact of the tread-pattern blocks in the contact patch region is characterized and coupled to the structure of the tire. Finally, a Boundary Element Method is implemented in order to compute the vibration-induced noise produced by the tire. All the modeling components are combined in a single prediction tool named Wave Pro Tire. Lastly, simulated responses and validation cases are presented in terms of harmonic responses, Frequency Response Functions (FRF), and produced noise. / Doctor of Philosophy / Induced vibrations due to tire-pavement interaction are one of the main sources of vehicle exterior noise, especially near highways and main roads where traveling speeds are above 50 kph. Accurate prediction tools are not currently available. Therefore, new physically based models need to be developed. This work proposes a new approach to model the tire’s structure with a formulation that accounts for multiple physical phenomena. In addition, a model that simulates the contact between the pavement and the tire’s tread is presented. Finally, the vibrations are coupled to the produced noise in a single prediction tool named Wave Pro Tire. This work also includes simulated responses and validation cases.

Doctor of Philosophy / The control systems installed in modern vehicles lack crucial information regarding the interaction between the tires and the road surface. This knowledge gap significantly impacts the safety and control of the vehicle. Thus, to address this issue, this research introduces a novel fusion approach to estimate friction at the tire-road contact interface. This hybrid fusion friction estimation algorithm employs techniques like signal processing and machine learning, backed up by information from various vehicle and tire dynamics models, to develop algorithms that estimate the level of friction between the tire and the road. This fusion approach enables more precise estimations of the friction coefficient in both normal driving situations and scenarios involving sudden changes in speed or road conditions. Therefore, this research aids in enhancing vehicle safety and control by providing improved information about such tire-road interactions.

Tire parameters play a very important role in tire performance. Depending on the driving conditions for which a given tire is designed, its parameters must be chosen appropriately (e.g., the radius of the tire, the width of the tire, material properties of different sections). Among tire characteristics, the material properties of the rubber compounds have a vital role in tire behavior. Previous studies show that the material properties of the rubber are highly dependent on temperature. Thus, a comprehensive study on the effect of the material properties of the rubber on tire performance for different temperatures as well as different road conditions is required. In this study, a theoretical model has been developed for tire-ice interaction. The temperature changes obtained from the model are used to calculate the height of the water film created by the heat generated due to the friction force. Next, the viscous friction coefficient at the contact patch is obtained. By using the thermal balance equation at the contact patch, dry friction is obtained. Knowing the friction coefficients for the dry and wet regions, the equivalent friction coefficient is calculated. The model has been validated using experimental results for three similar tires with different rubber compounds properties. For the experimental part of this study, four tires have been selected for testing. Three of them have identical tire geometry and structure but different rubber tread compounds. Several tests were conducted for the chosen tires in three modes: free-rolling, braking, and traction. The tests were performed for two different normal loads (4 kN and 5.6 kN), two different inflation pressures (21 psi (144.8 kPa) and 28 psi (193 kPa)), and three tire temperatures levels (-10°C, -5°C, and -1 °C). The Terramechanics Rig at TMVS at Virginia Tech has been used for conducting the tests. The results from this study show the sensitivity of the magnitude of the tractive force with respect to parameters such as tire temperature, normal load, etc. The results also indicate that the tire with the lowest value of the Young modulus has the highest traction among all four tires used in this study. The model developed can be used to predict the temperature changes at the contact patch, the tire friction force, the areas of wet and dry regions, the height of the water film for different ice temperatures, different normal loads, etc. The results from this study coincide with the obtained results from the experiments. According to the data available, tire B with the smallest value of Young modulus and the smallest value of the specific heat parameter was shown to have the highest friction coefficient in both simulation and experiment. After validating the results using experimentally collected data, the model was used to perform a sensitivity analysis on the tire performance with respect to six material properties of the tread rubber: thermal conductivity, rubber density, Young's modulus, specific heat, roughness parameter of the rubber, and radii of spherical asperities of the rubber. The results from this study show the sensitivity of the magnitude of the friction coefficient to the rubber material properties. The friction coefficient has a direct relationship with the density of the rubber and has an inverse relationship with Young's modulus, specific heat, and roughness parameter. / Doctor of Philosophy / In order to decrease the number of deaths and injuries caused by driving on icy roads and increase the safety of the vehicle, it is important to improve the tire performance on ice. To this, understanding the effects of different tire and road parameters such as material properties of the rubber, loading condition, and temperature on the tire-ice performance is required. Tire parameters play a very important role in tire performance. Depending on the driving conditions for which a given tire is designed, its parameters must be chosen appropriately In this project, the effects of different tire and terrain parameters such as rubber material properties on tire performance on ice using an experimental and modeling approach have been studied. For the experimental part of this study, several tests were conducted for more than 30 tires with different material properties. The results of this study show what are the most important material properties of the rubber for designing a tire with the best performance on ice. For the modeling part of this study, a semi-analytical model was developed. The model was validated using collected experimental data and was used to predict the performance of the tire by having information about its material and physical properties. The developed model called ATIIM2.0 has several advantages. First, it is a unique model for a complete tire (not a rubber block) that can be used to predict the performance of the tire by using its material properties. In addition, this model can be connected to vehicle models to improve the performance of the vehicle in general. The model developed can be used to predict the temperature changes at the contact patch, the tire friction force, the areas of wet and dry regions, the height of the water film for different ice temperatures, different normal loads, etc. The results from this study coincide with the obtained results from the experiments.