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The main objective of this research is to find a general empirical formula to predict vehicle frontal area applied to most types of vehicles. This was done on 21 vehicles; passenger cars, buses and trucks by calculating their frontal area by using image processing technique on cars photos extracted from catalogues. The software (Data Fit) is used to establish the required empirical formula. The results showed that the empirical formula is simple and accurate enough for finding out the vehicles frontal areas.

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.

A full vehicle of a preview control semi-active suspension system based on an interval type-2 fuzzy controller design using a magnetorheological (MR) damper to improve ride comfort is investigated in this paper. It is integrated with the force distribution system to obtain the optimal rate of road adhesion during braking and handling. The nonlinear suspension model is derived by considering vertical, pitch, and roll motions. The preview interval type-2 fuzzy technique is designed as a system controller, and it is attached with a Signum function method as a damper controller to turn on the voltage for the MR damper. This voltage is adjusted for each wheel based on the external excitation generated by road roughness in order to enhance ride comfort. To describe the effectiveness and adaptable responses of the preview controlled semi-active system, the performance is compared with both the passive and MR passive suspension systems during time and frequency domains.

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, the Kalman filter algorithm is used to design a practical adaptive control strategy. The adaptation is intended to adjust the system operation according to the changes of road input. A moderate adaptive time of at least 3 seconds is used. Limit stops are added to prevent the increase in the wheel travel behind the specified limit. The active suspension feedback system is designed based on measuring only the suspension displacement. A gain scheduling adaptive scheme which consists of four sets of state feedback gains is designed. The estimation process of dynamic tyre deflection and other necessary state variables through the Kalman filter is illustrated. Among other things, this estimate is used to derive the gain scheduling adaptive scheme. The strategy is applied to a quarter car active suspension system. Results are generated at a constant speed on random road profiles.

A non-linear mathematical model of a semi-active (2DOF) vehicle suspension using a magnetorheological (MR) damper with information concerning the road profile ahead of the vehicle is proposed in this paper. The semi-active vibration control system using an MR damper consists of two nested controllers: a system controller and a damper controller. The fuzzy logic technique is used to design the system controller based on both the dynamic responses of the suspension and the Padé approximation algorithm method of a preview control to evaluate the desired damping force. In addition, look-ahead preview of the excitations resulting from road irregularities is used to quickly mitigate the effect of the control system time delay on the damper response.

Welding is an excellent attachment or repair method. The advanced industries such as oil, automotive industries, and other important industries need to rely on reliable welding operations; collapse because of this welding may lead to an excessive cost in money and risk in human life. In the present research, an automatic system has been described to detect, recognize and classify welding defects in radiographic images. Such system uses a texture feature and neural network techniques. Image processing techniques were implemented to help in the image array of weld images and the detection of weld defects. Therefore, a proposed program was build in-house to automatically classify and recognize eleven types of welding defects met in practice.

In order to achieve the high capability of the ride comfort and regulating the tire slip ratio, a preview of a nonlinear semi-active vibration control suspension system using a magnetorheological (MR) fluid damper is integrated with traction control in this paper. A controlled semi-active suspension system, which consists of the system controller and damper controller, was used to develop ride comfort, while the traction controller is utilized to reduce a generated slip between the vehicle speed and rotational rate of the tire. Both Fractional-Order Filtered Proportional-Integral-Derivative (P¯IλDμ) and Fuzzy Logic connected either series or parallel with P¯IλDμ are designed as various methodologies of a system controller to generate optimal tracking of the desired damping force. The signum function method is modified as a damper controller to calculate an applied input voltage to the MR damper coil based on both preview signals and the desired damping force tracking.

The purpose of this paper is to investigate the efficiency of a quarter car semi-active suspension system with the state-derivative feedback controller using the Bouc-Wen model for magneto-rheological fluids. The magnetorheological (MR) dampers are classified as adaptive devices because of their characteristics can be easily modified by applying a controlled voltage signal. Semi-active suspension with MR dampers combines the benefits of active and passive suspension systems. The dynamic system captures the basic performance of the suspension, including seat travel distance, body acceleration, passenger acceleration, suspension travel distance, dynamic tire deflection and damping force. With minimal reliance on the use of sensors, the investigation aims to improve ride comfort and vehicle stability. In this study, the state derivative feedback controller and Genetic algorithm (GA) is utilized to improve the performance of semi-active suspension system.

Adaptive neuro-fuzzy inference system (ANFIS) technique has been developed and applied by numerous researchers as a very useful predictor for nonlinear systems. In this paper, non-parametric models have been investigated to predict the direct and inverse nonlinear dynamic behavior of magnetorheological (MR) fluid dampers using ANFIS technique to demonstrate more accurate and efficient models. The direct ANFIS model can be used to predict the damping force of the MR fluid damper and the inverse dynamic ANFIS model can be used to offer a suitable command voltage applied to the damper coil. The architectures and the learning details of the direct and inverse ANFIS models for MR fluid dampers are introduced and simulation results are discussed. The suggested ANFIS models are used to predict the damping force of the MR fluid damper accurately and precisely. Moreover, validation results for the ANFIS models are proposed and used to evaluate their performance.

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.

Squeal from brakes is a problem in the automotive industry and large efforts are made to understand the squeal tendencies. The approach taken is mainly to change the design of the caliper, fine-tune the brake pad material and finally to trim the introducing shims on the backside of the pads. Despite these efforts still no general solutions exist. To advance the situation, a deeper understanding of the actual source of excitation of the sound in the friction interface is needed. However, in the present investigation the surfaces modifications of brake disc and pad have been tested with respect to the understanding properties. The surfaces modifications are slotted pad material and coated disc. All tests have been made in a brake test stand consisting of a complete front wheel corner of a vehicle. The changes have resulted in a significant understand of the generated noise.

The DC power supply is ingredient part in the automotive industries as it has been used as a DC power supplies for a wide range of loads. Meanwhile, it is mandatory for battery charging. These types however, causes many problems such as poor power factor, high input current harmonics distortion and uncontrolled DC voltage. In this paper, an improved input power factor correction that uses a combined control system consists of two nested loops with a feedback of the DC voltage and input current as long as a feed forward from the output power. The system has been analyzed, modeled, simulated and experimentally verified. The novel feature of the proposed control scheme resides in fact that it is not only achieve nearly unity power factor with minimum input current total harmonics distortion only but it also introduce superior performance in DC voltage transient conditions.

In this paper, semi-active MR main suspension system based on system controller design to minimize pitch motion linked with MR-controlled seat suspension by considering driver’s biodynamics is investigated. According to a fixed footprint tire model, the transmitted tire force is determined. The linear-quadratic Gaussian (LQG) system controller is able to enhance ride comfort by adjusting damping forces based on an evaluation of body vibration from the dynamic responses. The controlled damping forces are tracked by the signum function controllers to evaluate the supply voltages for the front and rear MR dampers. Based on the sprung mass acceleration level and its derivative as the inputs, the optimal type-2 (T-2) fuzzy seat system controller is designed to regulate the controlled seat MR damper force.

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 present paper presents design considerations for a new tandem suspension system equipped with hydro-pneumatic components. The theory of the new suspension and its configuration were presented in a previously published SAE paper, [1]. In this design, most of the vertical motions were transformed into horizontal motions through two bell cranks. A hydraulic actuator is installed horizontally between the bell cranks and connected to an accumulator (gas spring) via a flow constriction (damper). Incorporating of hydro-pneumatic components in the new suspension system exhibits simple and applicable design. Moreover, further developments including active or semi-active vibration control systems, can be applied directly using the existing hydro-pneumatic components. Mathematical models are constructed to simulate the vehicle ride dynamics. Equations of motion are generated considering a conventional passive suspension (four springs tandem suspension) and the new designed suspension system.

It is well known that the excessive levels of vibration in heavy vehicles negatively affect driver comfortability, cargo safety and road condition. The current challenge in the field of suspension design for heavy vehicles is to optimize the suspension dynamic parameters to improve such requirements. Almost all of the previous work in this field is based on applying the mathematical optimization considering active or passive suspension systems to obtain the optimal dynamic parameters. In this work a new passive suspension systems for heavy trucks is suggested and compared with the conventional passive suspension systems. The new systems rely on transferring the vertical motion, (vibration), into horizontal motion through a bell-crank mechanism to be taken by a horizontal passive suspension system. The system dynamic parameters like body acceleration, suspension travel and dynamic tire load are calculated assuming random excitation due to road irregularities.

Integral Control strategy for vehicle chassis systems had been of great interest for vehicle designers in the last decade. This paper represents the interaction of longitudinal control and lateral control. In other words the traction control system and handling control system. Definitely, tire properties are playing a vital role in such interaction as it is responsible for the generated forces in both directions. A seven degrees of freedom half vehicle model is derived and used to investigate this interaction. The vehicle body is represented as a rigid body with three degrees of freedom, lateral and longitudinal, and yaw motions. The other four degrees are the two rotation motion of the front wheel and the rear wheel. This two motions for each wheel are spin motion and the steering motion. The traction controller is designed to modulate engine torque through adjusting the throttle angle of the engine upon utilized adhesion condition at the driving road wheels.

The anti-lock brake system (ABS) is a vital system in modern vehicles that prevents automotive wheels from locking during an emergency brake. This paper aims to introduce an efficient, optimized proportional integral derivative (PID) controller tuned using a genetic algorithm (GA) to enhance the performance of ABS. The PID control method is a very famous control algorithm employed in numerous engineering applications. The GA is used to solve the nonlinear optimization problem and search for the optimum PID controller gains by identifying the solution to the problem. A mathematical model of ABS is derived and simulated using Matlab and Simulink software. The proposed optimized PID-controlled ABS is compared to the conventional ABS controlled using a Bang-Bang controller. System performance criteria are evaluated and assessed under different road adhesion coefficient values to judge the success of the proposed PID controller tuned using GA.

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.