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Nonparametric models do not require any assumptions on the underlying input/output relationship of the system being modeled so that they are highly useful for studying and modeling the nonlinear behaviour of Magnetorheological (MR) fluid dampers. However, the application of these models in semi-active suspension is very rare and most theoretical works available on this topic address the application of parametric models (e.g. Modified Bouc-Wen model). In this paper, a nonparametric MR damper model based on the Restoring Force Surface technique is applied in vehicle semi-active suspension system. It consists of a three dimensional interpolation using Chebyshev orthogonal polynomial functions to simulate the MR damper force as a function of the displacement, velocity and input voltage. Also, a damper controller based on a Signum function method is proposed, for the first time, for use in conjunction with the system controller of a semi-active vehicle suspension.

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.

The number of speed humps (sleeping policemen) has seen a global increase in the last decade. This paper addresses the geometric requirements of these humps using Genetic Algorithms optimization techniques to control the speed, stability, and ride feel of the traversing vehicles. The interaction between road hump profile and the modeled vehicles (passenger and a two-axle truck) are studied with a dynamic model. The shape of the proposed profile is described by numbers of amplitudes of harmonic functions. The extreme acceleration of the drivers’ seats of the vehicles traversing the hump is set as multiobjective function for the optimization process, taking into consideration the road-holding ability represented by the tire lift-off speed. The results show that hump geometry can be improved while fulfilling the requirements of speed control and vehicle dynamic responses.

In this paper, a direct technique to estimate the rollover threshold limits of partially filled tank trucks is applied for banked roadways. Overturning and restoring moments are calculated as functions of tank shape, fill level, gradient of both liquid cargo free surface and the lateral inclination of banked road surfaces. The static rollover threshold of tanker trucks traveling on laterally banked roadways is estimated by balancing the net value of the total overturning moment against the net value of the restoring moment. Different filling ratios are considered for circular, elliptical and modified tank vehicles. The rollover threshold limits are calculated considering a superelevation range of (0.0-0.1) for the lateral road banking as defined by Blue and Kulakowski (1991). It is shown that the vehicle rollover threshold limit increases with an increase of the angle of the lateral road banking.

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.

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.

Proportional integral derivative (PID) control method is an effective, easy in implementation and famous control technique applied in several engineering systems. Also, Genetic Algorithm (GA) is a suitable approach for optimum searching problems in science, industrial and engineering applications. This paper presents the usage of GA for determining the optimal PID controller gains and their implementation in the active quarter-vehicle suspension system to achieve good ride comfort and vehicle stability levels. The GA is applied to solve a combined multi-objective (CMO) problem to tune PID controller gains of vehicle active suspension system for the first time. The active vehicle suspension system is modeled mathematically as a two degree-of-freedom mechanical system and simulated using Matlab/Simulink software.

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.

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.

1 Rear wheel drive vehicles have a long driveline using a propeller shaft with two universal joints. Consequently, in this design usage of universal joints within vehicle driveline is inevitable. However, the angularity of the driveshaft resulting from vertical oscillations of the rear axle causes many torsional and bending fluctuations of the driveline. Unfortunately, most of the previously published research work in this area assume the propeller inclination angle is constant under all operating conditions. As a matter of fact, this assumption is not accurate due to the vehicle body attitudes either in pitch or bounce motions. Where the vehicle vibration due to the suspension flexibility, either passive or active type, exists.

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.

This paper introduces an optimum design for a feedback controller of a fully active vehicle suspension system using the combined multi-objective particle swarm optimization (CMOPSO) in order to minimize the actuator power consumption while enhancing the ride comfort. The proposed CMOPSO algorithm aims to minimize both the vertical body acceleration and the actuator power consumption by searching about the optimum feedback controller gains. A mathematical model and the equations of motion of the quarter-car active suspension system are considered and simulated using Matlab/Simulink software. The proposed active suspension is compared with both active suspension system controlled using the linear quadratic regulator (LQR) and the passive suspension systems. Suspension performance is evaluated in time and frequency domains to verify the success of the proposed control technique.

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.

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.