Study on optimal design and vibration characteristics of diaphragm spring based on Genetic algorithm

Authors

  • F J Wang
  • Y Z Cui
  • F X Xu
  • S Bai
  • P C Xia
  • J F Wang

DOI:

https://doi.org/10.21152/1750-9548.17.3.289

Abstract

The parameters of diaphragm spring are optimized and the dimensional parameters in this design are determined with careful derivation. The global optimization feature of the genetic algorithm is used to optimize the diaphragm spring and compared with the damping effect of the standard algorithms. The results show that the optimization design can significantly reduce the force and realize vibration control of the clutch when the design requirements are met. Due to the large error in calculating the vibration characteristics of diaphragm spring by the commonly used A-L method, the finite element method is used to study the influence of the separation finger structure on the load-deflection characteristics of diaphragm spring. To this end, three different window shapes of diaphragm springs are verified in real-life measurements, and the effective pressure test data for three types of diaphragm springs (type A, type B and type C) are selected. Finally, the load displacement of the peak and valley is obtained by summing their averages under loading and unloading of each diaphragm spring model. Moreover, a new method for calculating the vibration characteristics is obtained by introducing the genetic algorithms into the optimal design of diaphragm springs. Compared the A-L method, the finite element method and the proposed method with the measured data, it is verified that the proposed method has high accuracy in calculating the vibration characteristics of diaphragm springs.

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Published

2023-09-16

How to Cite

Wang, F. J., Cui, Y. Z., Xu, F. X., Bai, S., Xia, P. C., & Wang, J. F. (2023). Study on optimal design and vibration characteristics of diaphragm spring based on Genetic algorithm. The International Journal of Multiphysics, 17(3), 289-314. https://doi.org/10.21152/1750-9548.17.3.289

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Articles