Optimization design of magnetorheological damper based on multi-objective whale algorithm

• Published in: Discover applied sciences Vol. 7; no. 6; pp. 531 - 23
• Main Authors: Zhao, Yuliang, Chen, Xiaoning, Huang, Xuhong, Liu, Caiwei, Liu, Wenfeng, Xu, Yanwei
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 23.05.2025; Springer Nature B.V; Springer
• Subjects: Algorithms; Applied and Technical Physics; Chemistry/Food Science; Control algorithms; Dampers; Damping; Design; Design optimization; Earth Sciences; Efficiency; Energy consumption; Engineering; Environment; Genetic algorithms; Magnetorheological damper; Materials Science; Mechanical properties; Neural networks; Optimization algorithms; Optimization techniques; Parameter estimation; Parameter identification; Parameter optimization; Parameter sensitivity; Sensitivity analysis; Sorting algorithms; Vibration; Whale algorithm; Magnetorheological damper; Sensitivity analysis; Whale algorithm; Parameter optimization
• ISSN: 3004-9261; 2523-3963; 3004-9261; 2523-3971
• DOI: 10.1007/s42452-025-07030-0

An efficient optimization design method for magnetorheological (MR) dampers, aimed at enhancing the damping force output and the adjustable coefficient, is explored in this study. The structural parameters of the double-rod MR damper, which significantly influence dynamic performance, were systematically analyzed and determined through Sobol Sensitivity Analysis. On this basis, the critical parameters were automatically optimized using Non-Dominated Sorting Whale Optimization Algorithm. By analyzing the unified Pareto front, the optimal structural parameters of the MR damper are determined and verified through numerical simulations and experimental comparisons. The results show that the key parameters affecting the mechanical performance of MR dampers can be reduced to five. The MR damper designed with these optimal parameters demonstrated a 17.1% increase in the adjustable coefficient and a 1.6-fold increase in damping force. Additionally, the optimization design method exhibited notable computational efficiency with superior global convergence characteristics, effectively solving the challenges in the optimization design of MR dampers. This study further deepens the optimization design theory of MR dampers and broadens the potential for diverse engineering applications. Article Highlights Sobol sensitivity analysis pinpoints critical parameters to boost optimization efficiency; Integrated Sobol-NSWOA methodology advances MR damper optimization; High-precision rapid-response method enables scalable MR damper production and applications.