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All automotive fleets' ownerships want to increase their fleets' availability; therefore, they resort to consider the conventional maintenance policy. Despite of, this policy increases fleets availability but the cost will be high. This is due to replace the parts before the end of their lifetime. On the other hand, this policy is based on time where it is not cost-effective. Consequently, this conventional maintenance policy is not adequate to fulfill the needs of high availability for automotive fleets. However, in this paper the study is directed to condition-based predictive maintenance concept as an alternative policy to determine fleet's health for increasing the fleet availability and to reduce the operating cost. The concept is based on predicting the system degradation and calculating the reliability function for the component. An application carried out on internal combustion engine crankshaft main bearing to illustrate the effectiveness of this technique.

The bearing capacity of soils stands as one of the most important parameters that determine the vehicles’ off-road mobility. Soil bearing capacity can be determined either experimentally or by calculation using analytical and or empirical formulas. One of the most famous formulas is the Bekker's. Recently, Artificial Neural Networks (ANNs) technique became a powerful tool that can be used for predicting systems’ behavior and performance. The main objective of this paper is to predict the bearing capacity of the soil (plate-sinkage relationships) by using Artificial Neural Networks and to compare the actual results of soil bearing capacity (collected data from Ph.D. Thesis) with results obtained from neural network model and Bekker's formula. The comparison showed clear superiority and accuracy of neural network technique. Another objective is to check the generalization ability of the neural network model in predicting the plate-sinkage relationships by using the hypothetical plate.

The previous research work on Active Independent Front Steering (AIFS) system concluded an enhanced vehicle response and tire adhesion utilization. Some research emphasizes the importance of Tire Work load (TWL) in the generation of maximum possible tire forces that ensures vehicle controllability and stability. In this study, a mathematical model is constructed to investigate the effect of TWL as a parameter on AIFS performance. Toward such a target, a new Fuzzy control strategy is developed based on TWL and vehicle yaw rate as control inputs for the AIFS controller. Unfortunately, the TWL is not a measurable parameter or even easy to be estimated. Consequently, another control strategy was implemented based on slip angle and vehicle yaw rate as inputs for the AIFS controller.

The dynamics of vehicles became one of the most important aspects for current developments of electronically controlled steering, suspension and traction/braking systems. However, most of the published research on vehicle maneuverability doesn't take into account the effect of the dynamic tire load and its variation on uneven roads. Clearly, it was stated that using a suitable active suspension system could reduce this dynamic tire load. This dynamic tire load is playing a vital role as it is the major link between the vertical and lateral forces exerted on the road, which affects the lateral dynamics of the vehicle. In this paper, a practical hydro-pneumatic limited bandwidth active suspension system with and without wheelbase preview control is used to study its influence on the vehicle stability in lateral direction. The model is a longitudinal half car with four degrees of freedom.

Dynamic modeling of the gear vibration is a useful tool to study the vibration response of a geared system under various gear parameters and operating conditions. An improved understanding of vibration signal is required for early detection of incipient gear failure to achieve high reliability. However, the aim of this work is to make use of a 6-degree-of-freedom gear dynamic model including localized tooth defect for early detection of gear failure. The model consists of a gear pair, two shafts, two inertias representing load and prime mover and bearings. The model incorporates the effects of time-varying mesh stiffness and damping, backlash, excitation due to gear errors and modifications. The results indicate that the simulated signal shows that as the defect size increases the amplitude of the acceleration signal increases. The crest factor and kurtosis values of the simulated signal increase as the fault increases.

This research aims to model and assess autonomous vehicle controller while including a four-wheel steering and longitudinal speed control. Such a modeling process simulates human driver behavior with consideration of real vehicle dynamics’ characteristics during standard maneuvers. However, a four-wheel steering control improves vehicle stability and maneuverability as well. A three-degree of freedom bicycle model, lateral deviation, yaw angle, and longitudinal speed is constructed to describe vehicle dynamics’ behavior. Moreover, a comprehensive traction model is implemented which includes an engine, automatic transmission, and non-linear magic formula tire model for simulation of vehicle longitudinal dynamics. A combination of proportional integral derivative (PID) longitudinal controller and fuzzy lateral controller are implemented simultaneously to track the desired vehicle path while minimizing lateral deviation and yaw angle errors.

This study presents a practical theoretical method to judge the aerodynamic response of buses in the early design stage based on both aerodynamic and design parameters. A constant longitudinal velocity 2-DOF vehicle lateral dynamics model is used to investigate the lateral response of a bus under nine different wind gusts excitations. An appropriate 3-D CFD simulation model of the bus shape results is integrated with carefully chosen design parameters data of a real bus chassis and body to obtain vehicle lateral dynamic response to the prescribed excitations. Vehicle model validity is carried out then, the 2-DOF vehicle lateral dynamics model has been executed in MATLAB Simulink environment with the selected data. Simulation represents the vehicle in a straight ahead path then entered a gusting wind section of the track with a fixed steering wheel. Vehicle response includes lateral deviation (LD), lateral acceleration (LA), yaw angle (YA) and yaw rate (YR).

Vehicle Handling performance depends on many parameters. One of the most important parameters is the dynamic behavior of the steering system. However, steering system had been enhanced thoroughly over the past decade where Active Front Steering (AFS) is now present and other system as Active Independent Front Steering (AIFS) is currently in the research phase. Actually, AFS system adopt the front wheels’ angles base on the actual input steering angle from the driver according to vehicle handling dynamics performance. While, the AIFS controls the angle of each front wheel individually to avoid reaching the saturation limits of any of the front wheels’ adhesion. In this paper modeling and analysis of an AIFS is presented with Tire Work Load (TWL) based controller. Magic Formula tire model is implemented to represent the tire in lateral slip condition.

In this paper, a hybrid roll control system, including passive and active roll control units, is designed to improve the roll dynamics of tanker vehicles and to reduce the lateral shifts of the liquid cargo due to lateral accelerations. The passive control system consists of radial partitions installed inside the vehicle container. These partitions rotate in phase with the liquid cargo as one unit about the longitudinal axis of the container in response to the induced momentum forces due to the lateral acceleration excitation. Torsion dampers are fixed between the partitions and the container's front and rear walls to reduce the oscillating motion of the liquid cargo. While the passive partition dampers control the dynamics of the liquid cargo inside the container, the dampers of the vehicle suspension are switchable, generating anti-roll damping moments based on the lateral acceleration level and the container filling ratio.