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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 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.

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.

Vehicle suspension is considered a vital system of modern automotive and necessary to offer an adequate level of ride comfort and roadholding. In the present paper, a fuzzy-based sliding surface (FBSS) controller is designed, as a system controller for the first time, for a semi-active vehicle suspension using a magnetorheological (MR) damper in order to minimize the transmitted unwanted vibrations to the passengers. Therefore, an ideal reference skyhook model is employed to construct the sliding surface, which is the input of fuzzy logic. MR damper is a semi-active device and is controlled indirectly using an external voltage source. So a neural-based damper controller is used to compute the applied voltage to the magnet coil of the MR damper in series with the FBSS system controller. The proposed semi-active controlled quarter-vehicle suspension using an MR damper is solved numerically by Matlab.

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 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.

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.

Vehicle suspension along with tires and steering linkages is designed for safe vehicle control and to be free of irritating vibrations. Therefore the suspension system designs are a compromise between ride softness and handing ability. However, this work is concerned with a theoretical investigation into the ride behavior of actively suspended vehicles. It is based on using fuzzy logic control (FLC) to implement a new sort of active suspension system. Comparisons between the behavior of active suspension system with FLC with those obtained from active systems with linear control theory (LQR), ideal skyhook system and the conventional passive suspension systems. Results are introduced in such a way to predict the benefits that could be achieved from fuzzy logic system over other competing systems. Furthermore, a controller is designed and made by using results of FLC system, theoretical inputs are used to examine the validity of this controller.

Gear fault diagnosis is important in the vibration monitoring of any rotating machine. When a localized fault occurs in gears, the vibration signals always display non-stationary behavior. In early stage of gear failure, the gear mesh frequency (GMF) contains very little energy and is often overwhelmed by noise and higher-level macro-structural vibrations. An effective signal processing method would be necessary to remove such corrupting noise and interference. This paper presents the value of optimal wavelet function for early detection of faulty gear. The Envelope Detection (ED) and the Energy Operator are used for gear fault diagnosis as common techniques with and without the proposed optimal wavelet to verify the effectiveness of the optimal wavelet function. Kurtosis values are determined for the previous techniques as an indicator parameter for the ability of early gear fault detection. The comparative study is applied to real vibration signals.

In the design of recreational vehicle alternators, a particular challenge arises from marketing and engineering teams' desire to ensure that their products meet “best in class” sound quality characteristics. Furthermore, it is desirable to know these characteristics in measurable engineering terms in the product design stage, preferably before prototypes are built and tested. However, the aim of this paper is to investigate experimentally the electromagnetic sound quality characteristics of a vehicle alternator with the view of determination. For this reason, a special test rig was designed to simulate the alternator electromagnetic noise source. The results indicate that significant information can be obtained for this source. This can be an effective way to control this generated noise and consequently improve the vehicle alternator sound quality and look promising.

In this paper, a fuzzy-PID controller is applied in a half vehicle active suspension system to enhance vibration levels of vehicle chassis and passenger seat. The fuzzy-PID controller consists of fuzzy and PID connecting in a series manner, the fuzzy output is considered as the PID input. Genetic Algorithm (GA) is selected to tune controller parameters to obtain optimal values that minimize the objective function. The equations of motion of five-degrees-of-freedom active half-vehicle suspension system are derived and simulated using Matlab/Simulink software. Double bumps and random road excitations are used to study the performance of suspension systems including bounce and pitch motion. The performance of the active suspension system using optimized fuzzy-PID controller is compared with conventional passive to show the efficiency of the proposed active suspension system.

Proportional integral derivative (PID) control technique is a famous and cost-effective control strategy, in real implementation, applied in various engineering applications. Also, the ant colony optimization (ACO) algorithm is extensively applied in various industrial problems. This paper addresses the usage of the ACO algorithm to tune the PID controller gains for a semi-active heavy vehicle suspension system integrated with cabin and seat. The magnetorheological (MR) damper is used in main suspension as a semi-active device to enhance the ride comfort and vehicle stability. The proposed semi-active suspension consists of a system controller that calculate the desired damping force using a PID controller tuned using ACO, and a continuous state damper controller that predict the input voltage that is required to track the desired damping force.

In this paper, a nonlinear semi-active vehicle suspension system using MR fluid dampers is investigated to enhance ride comfort and vehicle stability. Fuzzy logic and fuzzy self-tuning PID control techniques are applied as system controllers to compute desired front and rear damping forces in conjunction with a Signum function method damper controller to assess force track-ability of system controllers. The suggested fuzzy self-tuning PID operates fuzzy system as a PID gains tuner to mitigate the vehicle vibration levels and achieve excellent performance related to ride comfort and vehicle stability. The equations of motion of four-degrees-of-freedom semi-active half-vehicle suspension system incorporating MR dampers are derived and simulated using Matlab/Simulink software.

Proportional-integral-derivative (PID) controller is effective, popular and cost effective for a lot of scientific and engineering applications. In this paper, PID and fuzzy-self-tuning PID (FSTPID) controllers are applied to improve the performance of an active seat suspension system to enhance the pregnant woman comfort. The equations of motion of thirteen-degrees-of-freedom (13-DOF) active seat suspension system incorporating pregnant woman body model are derived and simulated. PID gains are tuned and estimated using genetic algorithm (GA) to formulate GA PID controller. In FSTPID, fuzzy logic technique is used to tune PID controller gains by selecting appropriate fuzzy rules using Matlab/Simulink software. Both controlled active seat suspension systems are compared with a passive seat suspension. Suspension performance is evaluated under bump and random road excitations in order to verify the success of the proposed controllers.