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In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

Many of the suspension adjustments that are made to improve the handling of asymmetric cars racing on banked oval tracks are not intuitively obvious to the engineer who is used to thinking of symmetric cars on relatively flat roads. This paper investigates the effects of typical suspension adjustments on the steady state handling of a Winston Cup race car. A relatively simple nonlinear car model is combined with a sophisticated tire model to predict steady-state handling on a banked track. The concept of dynamic wedge is explained, and its effects on handling of asymmetric race cars on banked ovals are examined. Results are presented that show the sensitivity of the handling to changes in various suspension characteristics.

Motor vehicle crashes involving novice drivers are significantly higher than matured driver incidents as reported by the National Highway Traffic Safety Administration Fatality Analysis Reporting System (NHTSA-FARS). Researchers around the world and the United States are focused on how to decrease crashes for this driver demographic. Novice drivers usually complete driver education classes as a pre-requisite for full licensure to improve overall knowledge and safety. However, compiled statistics still indicate a need for more in-depth training after full licensure. An opportunity exists to supplement in-vehicle driving with focused learning modules using automotive simulators. In this paper, a training program for “Following Etiquette” and “Situational Awareness” was developed to introduce these key driving techniques and to complete a feasibility study using a driving simulator as the training tool.

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.

Design of Automotive Composites reports that successful designs of automotive composites occurred recently in this arena. The chapters consist of eleven technical papers selected from the Automotive Composites and other relevant sessions that the editors have been organizing for the SAE International World Congress over the past five years. The book is divided into four sections: o Body Structures o Powertrain Components o Suspension Components o Electrical and Alternative Vehicle Components The composite design examples presented in Design of Automotive Composites come from the major OEMs and top-tier suppliers and are most relevant to the automotive materials challenges currently faced by the industry. Many of the innovative ideas have already been implemented on existing or new model vehicles, although a great deal of innovation is still in the works.

Providing acceptable ride quality of tractor semi-trailers is essential to their viability in the freight transport business. This paper describes the development of a design tool that may be used to investigate the vertical dynamic response and ride comfort of these vehicles. A 12 degrees-of-freedom (DOF) model of the vertical dynamic response was developed and simulated in MATLAB [1]. The model is analyzed in the frequency domain. The input to the model is a user-specified power spectral density (PSD) of the vertical road irregularities. Outputs include modal frequencies, damping ratios and mode shapes, frequency response functions, PSDs and root mean square (rms) vertical and longitudinal accelerations in 1/3 octave bands. The rms values are compared with the specifications for ride comfort cited in ISO 2631 [2].

It is well known that the ride quality of trucks is much harsher than that of automobiles. Additionally, truck drivers typically drive trucks for much longer duration than automobile drivers. These two factors contribute to the fatigue that a truck driver typically experiences during long haul deliveries. Fatigue reduces driver alertness and increases reaction times, increasing the possibility of an accident. One may conclude that better ride quality contributes to safer operation. The secondary suspensions of a tractor have been an area of particular interest because of the considerable ride comfort improvements they provide. A gap exists in the current engineering domain of an easily configurable high fidelity low computational cost simulation tool to analyze the ride of a tractor semi-trailer. For a preliminary design study, a 15 d.o.f. model of the tractor semi-trailer was developed to simulate in the Matlab/Simulink environment.

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.

A simulation of the vertical response of a nonlinear 1/4 car model consisting of a sprung and an unsprung mass was developed. It is being used for preliminary evaluation of various suspension configurations and control algorithms. Nonlinearities include hysteretic shock damping and switchable damping characteristics. Road inputs include discrete events such as bumps and potholes as well as randomly irregular roads having specified power spectral densities (PSDs). Fast Fourier transform data analysis procedures are used to process data from the simulation to obtain PSDs, rms values, and histograms of various response quantities. To aid in assessing ride comfort, the 1/3 octave band rms acceleration of the sprung mass is calculated and compared with specifications suggested by the International Standards Organization (ISO). Cross plots of the rms values of acceleration, suspension travel, and the force of the road on the tire are used to compare the performance of various suspensions.

With their high specific strength and stiffness, composites have the potential to significantly lower the vehicle weight, which can have a dramatic effect on improving fuel efficiency and reducing greenhouse gas emissions. For the past decade or so, composites have been experiencing several transitions, including the transition from micro-scale reinforcement fillers to nano-scale reinforcement fillers, resulting in the nanocomposite. The effectiveness of the nano-sized fillers in composites can be explained by one of their unique geometric properties: the length-to-thickness aspect ratio. Therefore, nano-sized fillers have exceptionally higher reinforcing efficiency than the conventional, large fillers. The effectiveness of the nano-sized fillers in composites is also due to their large surface area and surface energy.