Secondary Dynamic Coordinated Optimization of Tooth Profile for the Cycloid Gear in RV Reducers under Multi-factor Coupling

Authors

  • Zhenyu Wu
  • Siyuan Liu
  • Tianxiang Zhang
  • Hang Deng
  • Zhiyu Dai

Keywords:

RV speed reducer, Cycloid gear, Modification, Optimization

Abstract

The cycloid gear modification affects the meshing quality and transmission accuracy of RV speed reducers. However, there are few effective methods to find the optimal modification value. This paper adopts a secondary dynamic coordinated optimization method to obtain the optimal modification value. Firstly, by analyzing the meshing characteristics of the cycloid gear in RV speed reducers, the various factors which influence the RV speed reducers’ transmission characteristics was established, and then the design variables were extracted. Secondly, on the constraints that transmission accuracy, contact stress, transmission smoothness and other transmission characteristics be satisfied, the maximum transmission torque was taken as the optimization objective and the meshing range of the cycloid gear was dynamically selected. Consequently, the maximum transmission torque and corresponding design variables can be obtained utilizing optimal algorithm. Finally, the meshing number and position of the cycloid gear can be adjusted, and the optimal solution satisfying all the constraints can be obtained after a second optimization. It is found that the cycloid gear profile modification obtained in this way can increase the rated load torque of RV reducers compared to existing products, and the transmission accuracy can also be enhanced. Consequently, a new solution can be provided for the profile modification of cycloid gears.

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Published

2025-09-13

How to Cite

Wu, Z., Liu, S., Zhang, T., Deng, H., & Dai, Z. (2025). Secondary Dynamic Coordinated Optimization of Tooth Profile for the Cycloid Gear in RV Reducers under Multi-factor Coupling. Journal of Intelligent Machinery and Equipment, 1(1). Retrieved from https://www.masonpublish.org/index.php/Journal-of-Intelligent-Machinery/article/view/376

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