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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.

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.

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.