A Vibration Control Method Using MRASSA for 1/4 Semi-Active Suspension Systems

Author:

Yan Liangwen1,Chen Jiajian1,Duan Chaoqun1,Zhao Cuilian1,Yang Rongqi2

Affiliation:

1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China

2. Shanghai Merchant Ship Design & Research Institute, Shanghai 201203, China

Abstract

The multi-subpopulation refracted adaptive salp swarm algorithm (MRASSA) was proposed for vibration control in 1/4 semi-active suspension systems. The MRASSA algorithm was applied to optimize suspension damping performance by addressing the local optimal and slow convergence speed challenge of the standard salp swarm algorithm for two-degrees-of-freedom 1/4 semi-active suspension systems. The developed MRASSA contains three key improvements: (1) partitioning multi-subpopulation; (2) applying refracted opposition-based learning; (3) adopting adaptive factors. In order to verify the performance of the MRASSA approach, a 1/4 suspension Simulink model was developed for simulation experiments. To further validate the results, a physical platform was built to test the applicability of the simulation model. The optimized suspension performance of MRASSA was also compared with three optimized models, namely, standard SSA, Single-Objective Firefly (SOFA) and Whale-optimized Fuzzy-fractional Order (WOAFFO). The experimental results showed that MRASSA outperformed the other models, achieving better suspension performance in complex environments such as a random road with a speed of 60 km/h. Compared to passive suspension, MRASSA led to a 41.15% reduction in sprung mass acceleration and a 15–25% reduction compared to other models. Additionally, MRASSA had a maximum 20% reduction in suspension dynamic deflection and dynamic load. MRASSA also demonstrated a faster convergence speed, finding the optimal solution faster than the other algorithms. These results indicate that MRASSA is superior to other models and has potential as a valuable tool for suspension performance optimization.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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