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This paper investigates the tire-road interaction for tires equipped with two different solid rubber material definitions within a Finite Element Analysis virtual environment, ESI PAMCRASH. A Mixed Service Drive truck tire sized 315/80R22.5 is designed with two different solid rubber material definitions: a legacy hyperelastic solid Mooney-Rivlin material definition and an Ogden hyperelastic solid material definition. The popular Mooney-Rivlin is a material definition for solid rubber simulation that is not built with element elimination and is not easily applicable to thermal applications. The Ogden hyperelastic material definition for rubber simulations allows for element destruction. Therefore, it is of interest and more suited for designing a tire model with wear and thermal capabilities.

With the rise in demand, advanced steering control and electric vehicle technology are rapidly developing in modern times. Due to a controller's role as a backbone for the modern vehicle, its study has become increasingly crucial. This research proposes a novel 4th axle steering (4AS) feedforward controller that utilizes the first, second and fourth axle steering control for an 8x8 scaled electric combat vehicle. The vehicle is tested using the predefined path following. The novel 4AS controller is then compared to the Ackermann steering condition at different speeds. In the scaled vehicle used for this research, each wheel is independently driven by an in-wheel motor, while the steering is carried out by linear actuators. Individual eight-wheel steering control systems are designed and installed on the scaled vehicle to evaluate the driving performance from low speed to high speed. The 4AS steering method is implemented to improve the stability of the scaled vehicle at high speeds.

This work investigates the steering and wheel speed control of a completely custom built 8x8 scaled electric combat vehicle (SECV) which has been constructed to meet the Ackermann condition at low speeds. During remote control operation the scaled vehicle is capable of continuously maintaining and varying the individual wheel speed and individual wheel steering angles of all eight wheels in real time. Several steering scenarios have been developed including traditional (front 2-axle steering), fixed third axle (first, second and fourth axle steering), all wheel steering and crab steering (all wheels are parallel with same steering angle). The traditional, two axle steering scenario is experimentally tested for accuracy in this work with planned future research for experimental analysis of the other steering configurations. This work is conducted using Arduino software to control the physical SECV and TruckSim software to simulate the dynamics of the vehicle.

This paper investigates the impact of tread design on the tire-terrain interaction of two similar-sized truck tires with distinctly different tread designs running over various terrains and operating conditions using advanced computation techniques. The two truck tires used in the research are off-road tires sized 315/80R22.5 wide which were designed through Finite Element Analysis (FEA). The truck tire models were validated in static and dynamic domains using several simulation tests and measured data. The terrain includes a flooded surface and a snowed surface which were modelled using Smoothed-Particle Hydrodynamics (SPH) technique and calibrated using pressure-sinkage and direct shear tests. Both truck tire models were subjected to rolling resistance and cornering tests over the various flooded surface and snowed surface terrain conditions on the PAM-CRASH software.

The physical characteristics of Mars's soil have an impact on how easily a spacecraft can land and navigate the planet's surface. On the surface of Mars, wheeled robots known as "rovers" were planted to carry out scientific investigations on the planet's historical temperature, surface geology, and possibilities for past or current life. The challenges of guiding mobile robots across terrain that is sloping, rocky, and deformable have brought to light the significance of creating precise simulation models of the tire and mars soil interaction. In this paper, current efforts to create a terramechanics-based model of rover movement using a Non-Pneumatic (NP) tire on planetary surfaces are discussed. Since no rocks or soils have been brought back to Earth from Mars, Martian simulants are frequently used for testing rovers and other devices for Mars terrain research.

Slip or relative rotation between the tire and rim is a significant concern for vehicle operation and wheel manufacturing since it leads to wheel imbalance and vibration as well as power losses. A slip situation typically occurs due to improper bead lubrication and mounting, irregularities in the bead seat, and extreme loading conditions with high torques and low tire pressures. Currently, there are relatively few published studies on the tire-rim interface, and they mainly focus on topics such as the mounting process, load transfer, and friction modelling. This leaves a gap to explore the measurement and variation of gross tire-rim slip under the dynamic conditions of a driven tire. In this paper, a previously developed and validated FEA truck tire model was modified to include a frictional contact surface between the tire and rim, and then the slip ratio between the tire and rim was measured under different operating conditions.

This paper focuses on developing an advanced analytical tire-terrain interaction model for full vehicle performance prediction purposes. The truck tire size 315/80R22.5 is modeled using the Finite Element Analysis (FEA) technique and validated against manufacturer experimental data in static and dynamic domains. While the terrain is modeled using Smoothed-Particle Hydrodynamics (SPH) technique and calibrated using experimental results of pressure-sinkage and direct shear tests. The contact between the FEA tire model and the SPH soil model is defined using the node symmetric node to segment with the edge treatment algorithm. The model setup consists of four tires appended back to back over a box filled with soil particles to represent a multi-axle off-road truck. The distances between the four tires are similar to the distances between the four axles of an off-road truck.

This paper presents the modelling, calibration and sensitivity analysis of LETE sand soil using Visual Environment’s Pam Crash. LETE sand is modelled and converted from Finite Element Analysis mesh (FEA) to Smooth-particle hydrodynamics (SPH). The sand is then calibrated using terramechanics published data by simulating a pressure sinkage test and shear box test using the SPH LETE sand particles. The material properties such as tangent modulus, yield strength and bulk modulus are configured so the simulation’s results match those of theoretical values. Sensitivity analysis of the calibrated LETE sand material is then investigated. The sensitivity analysis includes mesh size, plate geometry, smoothing length, max smoothing length, artificial viscosity and contact thickness. The effect of these parameters on the sand behavior is analyzed.

This paper focuses on predicting the rolling resistance and hydroplaning of a wide base truck tire (Size: 445/50R22.5) on dry and wet surfaces. The rolling resistance and hydroplaning are predicted at various inflation pressures, loads, velocities, and water depths. The wide base truck tire was previously modeled and validated using Finite Element Analysis (FEA) technique in virtual performance software (Pam-Crash). The water is modeled using Smoothed-Particle Hydrodynamics (SPH) method and Murnaghan equation of state. A water layer is first built on top of an FEA rigid surface to represent a wet surface. The truck tire is then inflated to the desired pressure. A vertical load is then applied to the center of the tire. For rolling resistance tests variable constant longitudinal speeds are applied to the center of the tire. The forces in the vertical and longitudinal directions are computed, and the rolling resistance is calculated.