• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2019, Vol. 55 ›› Issue (19): 154-166.doi: 10.3901/JME.2019.19.154

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Optimum of Electromagnetic Active Suspension Actuator Using Multi-objective Particle Swarm Optimization Algorithm

YANG Chao1, LI Yinong1,2, ZHENG Ling1, HU Yiming1   

  1. 1. College of Automotive Engineering, Chongqing University, Chongqing 400030;
    2. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400030
  • Received:2018-10-06 Revised:2019-03-02 Online:2019-10-05 Published:2020-01-07

Abstract: For aiming at reducing the influence of the thrust ripple in electromagnetic active suspension, magnetic field theoretical model of the actuator is established, total harmonic distortion (THD) is taken as the evaluation to actuator EMF, harmonic components of EMF which effective to the electromagnetic force are analyzed. On this basis, a suspension dynamics model considering suspension electromagnetic force fluctuation is established, and the vehicle dynamic response characteristics are analyzed. And then, taking the maximum EMF amplitude and the minimum THD as optimization objective, the actuator structure parameters are optimized with intelligent multi-objectives particle swarm optimization. The best Pareto optimal solution is selected based on the fuzzy set theory. After optimization, the ripple of electromagnetic force is reduced by 53.8%, and the value of electromagnetic force is increased by 8.5%, the influence of the thrust ripple in electromagnetic active suspension system is basically eliminated. Finally, actuator prototype is experimented on test bench. The results show that there are a series of harmonics including the 3rd, 2rd, 4rd and 5rd in the EMF wave, the THD is 5.6%, and the ripple of electromagnetic force is 7.8 N. Optimization results are verified by experiment.

Key words: electromagnetic active suspension, linear actuator, electromagnetic force fluctuation, multi-objective optimization, particle swarm algorithm

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