Optimization of dual-function suspension structures using particle swarm optimization approaches

被引:0
|
作者
Wang, Guohong [1 ]
Kou, Farong [1 ]
机构
[1] Xian Univ Sci & Technol, Sch Mech Engn, Xian 710000, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Dual-function suspension; linear motor; magnetorheological damper; Pareto; optimization; particle swarm algorithms; ENERGY REGENERATION; VEHICLE; PARAMETERS; SYSTEM;
D O I
10.3233/JAE-220282
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The suspension system integrating both vibration control and energy harvesting capabilities is denoted as Dual-function Suspension (DFS). The principal objectives for DFS encompass lightweight structure, high output force, extensive adjustability in damping, and minimized energy consumption. In pursuit of optimizing the linear motor and magnetorheological damper (MRD) amalgamated into the DFS, a multi-objective Particle Swarm Optimization (PSO) algorithm is conceived, emphasizing primary and secondary objectives to enhance the holistic performance of the DFS. A comprehensive mathematical model of the DFS is established, and subsequent to this modeling, the structural parameters of DFS are meticulously analyzed. Drawing upon the insights from this analysis, primary and supplementary optimization objectives are delineated, employing PSO for the refinement of the DFS structure. Following this, the Pareto solution set, derived from the optimization process, is judiciously selected utilizing fuzzy theorem principles. The outcomes reveal that, under the constraints of unaltered suspension packaging dimensions and overall energy consumption, the optimized suspension system manifests a 50% augmentation in output force, a 30% expansion in adjustable damping range, and a 39% reduction in thrust ripple compared to its pre-optimized state.
引用
收藏
页码:19 / 37
页数:19
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