Improvement of semi-active suspensions through fuzzy-logic and top mount optimization

The goal of this research study is to develop a full-vehicle semi-active suspension system controller based on Fuzzy-Logic to improve the ride comfort and road holding performance of a vehicle. Furthermore, the harshness improvement that can be achieved through optimization of the damper top mount characteristics of the semi-active suspension system is analyzed. A generic full vehicle model with non-linear suspension component characteristics is constructed. The model has eleven DOF which include the bounce, pitch and roll motions of the body and the engine block as well as the bounce motion of the wheels and the driver. A novel non-linear damper top mount model is developed and employed in the vehicle model. The amplitude and frequency dependent parameters of the damper top mount model are identified from experimental data. The damper top mount model and the full vehicle ride dynamics model are validated through laboratory tests. An effective methodology for automated design of a Fuzzy-Logic semi-active suspension controller is developed, which can be used to obtain the optimal controller structure and parameters according to the ride comfort and road holding performance requirements. The proposed methodology uses the binary discrete genetic optimization algorithm to construct the membership functions and the rule base of the Fuzzy-Logic controller. In addition to this, the parameters of the detailed damper top mount model are optimized to improve the response of the vehicle also in the harshness frequency range. The results show that, the rule-optimized controller is able to improve the vehicle ride performance under different operating conditions. Furthermore, the optimized damper top mount characteristics provide significant improvement in the vehicle harshness.