Modeling and Parameter Identification of MR Damper considering Excitation Characteristics and Current

Abstract

Smart structures such as damping adjustable dampers made of magnetorheological (MR) fluid can be used to attenuate vibration transmission in vehicle seat suspension. The main research content of this paper is the nonlinearity and hysteresis characteristics of the MR damper. A hysteretic model considering both excitation characteristics and input current is proposed to fit the damper force-velocity curve for the MR damper under different conditions. Multifactor sensitivity analysis based on the neural network method is used to obtain importance parameters of the hyperbolic tangent model. In order to demonstrate the fitting precision of the different models, the shuffled frog-leaping algorithm (SFLA) is employed to identify the parameters of MR damper models. The research results indicate that the modified model can not only describe the nonlinear hysteretic behavior of the MR damper more accurately in fixed conditions, compared with the original model, but also meet the fitting precision under a wide range of magnitudes of control current and excitation conditions (frequency and amplitude). The method of parameter sensitivity analysis and identification can also be used to modify other nonlinear dynamic models.