Automatization Intelligent Control of Vehicle Magneto-Rheological Semi-Active Suspension

In order to address the problem that traditional passive suspension damping parameter cannot be adjusted which makes it difficult to improve vehicle ride comfort and handling stability, the paper proposes use of controllable magneto-rheological dampers in replace of passive dampers to establish semi-active suspension based on magneto-rheological dampers. By designing magneto-rheological damper reverse model based on BP neural network, it solves the problem of reverse request of input current required with expected damping force and damper piston relative displacement, forms closed loop feedback system with the inverse model and the designed fuzzy PID controller and achieves semi-active control of vehicle suspension. The experimental results and data analyses of inputting different road excitation in the system show that the intelligent hybrid control method proposed in this paper can effectively improve the vehicle ride comfort and handling stability and improve suspension system performance. This paper conducts comparative analyses of vehicle semi-active suspension system performance for the cases of different speeds on different roads, which further validate rationality and effectiveness of the method.