The use of heuristic optimization techniques on RV cycloid reducer design

In this study, heuristic optimization algorithms such as particle swarm optimization (PSO) and quantum particle swarm optimization (QPSO) have been used to optimize the weight of the cycloid reducer based on the values of some parameters. The algorithms were applied separately to the design problem, and their performances were compared. Initially, a basic design was performed using conventional approaches. Constraint conditions have been defined based on geometric features and the essential component of the reducer, the cycloidal gear, and then the existing basic design has been optimized in terms of size and weight. Finally, finite element analysis was conducted to validate the obtained parameter values and control the stresses in the contact areas of the cycloid gear profile. It has been determined that PSO reduced the weight of the basic design by 33.3 %, whereas QPSO reduced it by 33.8 %. Moreover, the results of the finite element analysis showed that the design obtained according to both optimization methods was safe in terms of the resulting stresses. Consequently, it has been demonstrated that the selected design parameters and constraint equations have been sufficient and that the basic designs could be enhanced using intuitive optimization methods.