A parameter identification method for magnetorheological dampers using particle swarm-ant colony hybrid algorithm

Accurate parameter identification of magnetorheological dampers is the core prerequisite for ensuring their application effect in vibration control. Based on the hyperbolic tangent model, this paper proposes a hybrid particle swarm-ant colony optimization method for parameter identification. The optimal parameter configuration is determined via orthogonal experiments based on the damping force experimental data under 0–2 A currents, and verification is performed under multiple excitation conditions. The results show that the hybrid algorithm achieves significantly higher identification accuracy than single particle swarm optimization or ant colony optimization algorithm. Under 0–2 A currents, the proposed method yields Mean Squared Error values ranging from 1.03 to 1.76 and Root Mean Squared Error values from 1.01 to 1.33, with all R2 exceeding 0.99. The fitted curves exhibit excellent agreement with experimental data, and the identified parameters accurately reflect the rheological properties of magnetorheological fluids. This study constructs a high-precision damper parameter identification framework, providing strong support for the engineering application of magnetorheological dampers.