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This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.

The automotive sector has taken a keen interest in lightweighting as new required performance standards for fuel economy come into place. This strategy includes parts consolidation, design optimization, and material substitution, with sustainable polymers playing a major role in reducing a vehicle’s weight. Sustainable polymers are largely biodegradable, biocompatible, and sourced from renewable plant and agricultural stocks. A facile way to enhance their properties, so they can indeed replace the ones made from fossil fuels, is by reinforcing them with fibers to make composites. Natural fibers are gaining more acceptance in the industry due to their renewable nature, low cost, low density, low energy consumption, high specific strength and stiffness, CO2 sequestration potential, biodegradability, and less wear imposed on machinery. Biocomposites then become a very feasible way to help address the fuel consumption challenge ahead of us.

In an effort to build a shear band of a lunar rover wheel which operates at lunar surface temperatures (40 to 400K), the design of a metallic cellular shear band is suggested. Six representative honeycombs with aluminum alloy (7075-T6) are tailored to have a shear modulus of 6.5MPa which is a shear modulus of an elastomer by changing cell wall thickness, cell angles, cell heights and cell lengths at meso-scale. The designed cellular solids are used for a ring typed shear band of a wheel structure at macro-scale. A structural performance such as contact pressure at the outer layer of the wheel is investigated with the honeycomb shear bands when a vertical force is applied at the center of the wheel. Cellular Materials Theory (CMT) is used to obtain in-plane effective properties of a honeycomb structure at meso-scale. Finite Element Analysis (FEA) with commercial software ABAQUS is employed to investigate the structural behavior of a wheel at macro-scale.

To facilitate the design of a non-pneumatic tire for NASA's new Moon mission, the authors used the Finite Element Method (FEM) to investigate the interaction between soil and non-pneumatic tire made of different cellular shear bands. Cellular shear bands, made of an aluminum alloy (AL7075-T6), are designed to have the same effective shear modulus of 6.5E+6 Pa, which is the shear modulus of an elastomer. The Lebanon sand of New Hampshire is used in the model. This sand has a complete set of material properties in the literature and Drucker-Prager/Cap plasticity constitutive law with hardening is employed to model the sand. The tires are treated as deformable bodies, and the authors used the penalty contact algorithm to model the tangential behavior of the contact. The friction between tire and sand is considered by using Coulomb's law. Numerical results show deformation of sand and tire.

Three-dimensional simulation has become an indispensable approach to develop improved understanding of ring rolling technology, with validity as the basic requirement of the ring rolling simulation. Cold ring rolling is simple conceptually, however complex to analyze as the metal forming process is subject to coupled effects with multiple influencing factors such as sizes of rolls and ring blank, form geometry, material, process parameters, and frictional effects. Investigating the coupled thermal and plastic deformation behavior (the plastic deformation state and its development) in the deformation zone during the process is significant for predicting metal flow in order to control the geometric and tensile residual stress quality of deformed rings, and to provide for cycle time optimization of the cold ring rolling process.

Due to titanium's excellent strength-to-weight ratio and high corrosion resistance, titanium and its alloys have great potential to reduce energy usage in vehicles through a reduction in vehicle mass. The mass of a road vehicle is directly related to its energy consumption through inertial requirements and tire rolling resistance losses. However, when considering the manufacture of titanium automotive components, the machinability is poor, thus increasing processing cost through a trade-off between extended cycle time (labor cost) or increased tool wear (tooling cost). This fact has classified titanium as a “difficult-to-machine” material and consequently, titanium has been traditionally used for application areas having a comparatively higher end product cost such as in aerospace applications, the automotive racing segment, etc., as opposed to the consumer automotive segment.