A novel reliable parametric model for predicting the nonlinear hysteresis phenomenon of composite magnetorheological fluid

Magnetorheological fluid (MRF), as a novel intelligent composite material, possesses unique controllable properties in the presence of a magnetic field, thereby opening up new possibilities for its engineering applications. This study proposes a novel parametric model to predict the nonlinear hysteresis behavior of MRF using micron-scale carbonyl iron particles. Experiments with large-amplitude shear tests (10% strain amplitude, 0.1 Hz and 1 Hz frequencies) were conducted at five current levels (0 A, 0.5 A, 1 A, 1.5 A, and 2 A) to identify model parameters via a genetic optimization algorithm. The proposed model, with fewer parameters and no differential operators, outperforms existing models (e.g. Bouc-Wen and hyperbolic tangent models) in capturing MRF’s nonlinear behavior. This research provides a robust theoretical framework for predicting the nonlinear hysteresis in automotive dampers and semi-active suspension control.