• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2026, Vol. 62 ›› Issue (1): 374-383.doi: 10.3901/JME.260027

Previous Articles    

Non-probabilistic Reliability Analysis and Optimization of Semi-active Suspension with Energy Harvesting Characteristic

GAO Xiang1, ZHANG Xiang1, NIU Junchuan2,3, HE Lei1, WANG Zhonglong1, WU Hu1   

  1. 1. School of Mechanical Engineering, Shandong University of Technology, Zibo 255000;
    2. School of Mechanical Engineering, Shandong University, Jinan 250061;
    3. Key Laboratory of High Efficiency and Clean Mechanical Manufacture (Shandong University), Ministry of Education, Jinan 250061
  • Received:2025-02-19 Revised:2025-10-11 Published:2026-02-13

Abstract: For demonstrating the vibration isolation capability and energy harvesting characteristic of semi-active suspension based on magneto-rheological (MR) damper with key parameters perturbation, the dynamical model of semi-active suspension with key parameters perturbation is established. The vibration performance is investigated in time and frequency domain respectively by interval analysis approach. The non-probabilistic reliability calculating model is formulated via shortest distance method, the non-probabilistic reliability is evaluated with key parameters perturbation. The grey relation analysis approach is employed to determine the influential degree of key parameters on non-probabilistic reliability. The balance index is proposed based on dynamical programming theory including vibration isolation performance and energy harvesting simultaneously, and the influence of key parameters on balance index is conducted. The optimal key parameters are obtained by solving Nash equilibrium of the balance index. The results indicate that the clearance of flow channel h affects the non-probabilistic reliability most obviously. The comprehensive performance of suspension is enhanced by adjusting the structural parameters of MR damper most significantly.

Key words: semi-active suspension, energy harvesting magneto-rheological (MR) damper, non-probabilistic reliability, multi-objective optimization, dynamical programming

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