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The integrated control between the vehicle chassis subsystems (suspension, brake, and steering) became one of the most important aspects for current developments to improve the dynamics of the vehicles. Therefore, the aim of this study is to investigate the influence of the preview control of the active suspension on the vehicle ride and braking performance. The vehicle performance was examined theoretically using a longitudinal half vehicle model with four degrees of freedom considering the rotational motion of the tires. The active suspension system model, tire-road interface model and braking system model are included in the vehicle model. In order to study the influence of the preview control on the vehicle ride and braking performance, an active suspension system control algorithm employing the lock-ahead preview information and the wheel-base time delay based on the optimal control theory is derived.

There is an increasing customer demand for adjustable chassis control features which enable adaption of the vehicle comfort and driving characteristics to the customer requirements. One of the most promising vehicle control systems which can be used to change the vehicle characteristics during the drive is the semi-active suspension system. This paper presents a Rule-Optimized Fuzzy Logic controller for semi-active suspension systems which can continuously adjust itself not only according to the road conditions but also to the driver requirements. The proposed controller offers three different control modes (Comfort, Normal and Sport) which can be switched by the driver during driving. The Comfort Mode minimizes the accelerations imposed on the driver and passengers by using a softer damping. On the other hand, the increased damping in Sport Mode provides better road holding capability, which is critical for sporty handling.

This paper presents a performance analysis study for the Rule-Optimized controller of a semi-active suspension system. The Rule-Optimized controller is based on a Fuzzy Logic control scheme which offers new opportunities in the improvement of vehicle ride performance. An eleven degree of freedom full vehicle ride dynamics model is developed and validated through laboratory tests performed on a hydraulic four-poster shaker. An optimization process is applied to obtain the optimum Fuzzy Logic membership functions and the optimum rule-base of the semi-active suspension controller. The global optima of the cost function which considers the ride comfort and road holding performance of the full vehicle is determined through discrete optimization with Genetic Algorithm (GA).

Following the developments in controlled suspension system components, the studies on the vertical dynamics analysis of vehicles increased their popularity in recent years. The objective of this study is to develop a semi-active suspension system controller using Adaptive-Fuzzy Logic control theories together with Kalman Filter for state estimation. A quarter vehicle ride dynamics model is constructed and validated through laboratory tests performed on a hydraulic four-poster shaker. A Kalman Filter algorithm is constructed for bounce velocity estimation, and its accuracy is verified through measurements performed with external displacement sensors. The benefit of using adaptive control with Fuzzy-Logic to maintain the optimal performance over a wide range of road inputs is enhanced by the accuracy of Kalman Filter in estimating the controller inputs. A gradient-based optimization algorithm is applied for improving the Fuzzy-Logic controller parameters.

Due to the importance of the fast transportation under every circumstance, the transportation process may require a high speed heavy vehicle from time to time, which may turn the transportation process more unsafe. Due to that fact the truck safety during braking and the ride comfort during long distance travelling with high speeds should be improved. Therefore, the aim of this work is to develop a control system which combines the suspension and braking systems. The control system consists of three controllers; the first one for the active suspension system of the truck body and cab, the second one for the ABS and, the third for the integrated control system between the active suspension system and the ABS. The control strategy is also separated into two strategies.

This paper presents a new and effective control concept for semi-active suspension systems. The proposed controller uses a Fuzzy Logic scheme which offers new opportunities in the improvement of vehicle ride performance. The Fuzzy Logic scheme tunes the controller to treat the conflict requirements of ride comfort and road holding parameters within a specified range of the suspension deflection. An eleven degree of freedom full vehicle ride dynamics model is constructed and validated through laboratory tests performed on a hydraulic four-poster shaker. A new optimization process for obtaining the optimum Fuzzy Logic membership functions and the optimum rule-base of the proposed semi-active suspension controller is proposed. Discrete optimization has been performed with a Genetic Algorithm (GA) to find the global optima of the cost function which considers the ride comfort and road holding performance of the full vehicle.

The current paper addresses the relationship between the damper top mount characteristics and the ride comfort and harshness of a vehicle. A detailed mathematical damper top mount model which can simulate the vertical force characteristics of damper top mounts is developed and verified with actual tests. The amplitude and frequency dependent parameters of the damper top mount model are extracted from experimental testing of a commercial damper top mount. In order to identify the model parameters, a new procedure based on a two-stage optimization routine using two sets of measurement data for the amplitude and frequency dependent parameters is proposed. The damper top mount model is validated by comparing the measured force of the damper top mount with the simulated force of the proposed model. The developed top mount model is then implemented into a quarter vehicle simulation model for studying the influence of damper top mount characteristics on vehicle ride comfort and harshness.

Nowadays, the anti-lock braking system, briefly ABS, is an important component in modern cars. Therefore, in this paper the one of the intelligent control theories “Fuzzy Logic Control” is suggested to create two different ABS controllers. The braking performance was examined theoretically using half vehicle model. The suspension system model, tire-road interface model and anti-lock braking system model are included in the model. The influence of vehicle initial speed and tire-road friction coefficient is investigated. The simulation results of the proposed controllers are compared with the conventional ABS controller and the Conventional Brake system. The results showed that, using Fuzzy Logic Control in ABS improved the braking performance than the conventional ABS. Furthermore, the improvement in the braking performance using fuzzy logic control is obtained without any additional sensors, which leads the controller to be more realizable for the industry application.

The paper deals with a theoretical study to present a new sort of the buses suspension systems employs a hydraulic connection between the front and rear dampers together with active suspension actuator at the front axle. The theoretical investigation based on a half vehicle model of the bus suspension system includes the engine mounting system. The hydraulic connection between the front and rear dampers is created according to the capillary tubes theory. Furthermore, the active suspension system control algorithm based on the optimal control theory is derived. The Genetic Algorithm optimization routine is applied to generate the active suspension control algorithm parameters. A comparison between the connected dampers suspension system, active suspension system, active-connected dampers suspension system, and the passive suspension system in terms of ride comfort and road holding at constant suspension working space is performed.

The objective of this study is to develop a Model Reference Control (MRC) strategy for active suspension System. The MRC strategy employs both the suspension look-ahead preview and wheelbase preview concepts, and the methodology of the MRC based on the ideal hybrid skyhook-groundhook concept. The study performed using a 13 degree-of-freedom (DoF) vehicle vertical dynamics model including the active suspension actuators masses. The engine mass, driver seat and anti-roll bar are considered in the model. The MRC strategy uses eight Proportional-Integral-Derivative (PID) controllers for both body and wheel control. A gradient-based optimization algorithm is applied to obtain the controller parameters using a cost function including both ride comfort and road holding performance.

Semi-active suspension offers variety of damping force range which demands greater need to optimize the top mount to ensure multiple objectives of ride comfort, harshness and safety can be achieved. For this purpose, this paper proposes a numerical optimization procedure for improving the harshness performance of the vehicle through the adjustment of the damper top mount characteristics of the semi-active suspension system. The proposed optimization process employs a frequency dependent combined objective function based on ride comfort and harshness evaluation. A detailed and accurate damper top mount mathematical model is implemented inside a validated full vehicle model to provide a realistic simulation environment for the optimization study. The semi-active suspension system employs a Rule-Optimized Fuzzy-Logic controller. The ride comfort and harshness of the full vehicle are evaluated by analyzing the body acceleration in different frequency ranges.