A Loss Separation-Based Dynamic Jiles-Atherton-Bingham Model for Magnetorheological Dampers

Area of Science:

• Mechanical Engineering
• Materials Science
• Control Systems

Background:

• Magnetorheological (MR) dampers exhibit complex nonlinear hysteresis, challenging to model dynamically.
• Conventional static Jiles-Atherton (JA) models fail to capture these dynamic hysteresis responses accurately.

Purpose of the Study:

• To develop an advanced dynamic model for MR dampers that accurately represents hysteresis.
• To improve the modeling of magnetic flux density and excitation current coupling in MR dampers.

Main Methods:

• Proposed a loss separation dynamic Jiles-Atherton model (LS-DJAM) integrating eddy current and excess loss mechanisms.
• Developed a hybrid particle swarm optimization-genetic algorithm (PSO-GA) for efficient LS-DJAM parameter identification.
• Established a magneto-mechanical constitutive relation by coupling the Bingham mechanical model with LS-DJAM.

Main Results:

• The LS-DJAM, optimized by PSO-GA, significantly improved MR damper output force modeling.
• PSO-GA parameter estimation enhanced accuracy by over 60%.
• The LS-DJAM reduced maximum modeling error by 87.5% compared to the conventional JA model.

Conclusions:

• The proposed LS-DJAM accurately captures the dynamic hysteresis characteristics of MR dampers.
• The study provides a robust framework for high-performance control and engineering optimization of MR dampers.