Multi-Objective Optimization of Planetary Gear Train Using Genetic Algorithm | ||
| Journal of International Society for Science and Engineering | ||
| Volume 4, Issue 3, September 2022, Pages 74-80 PDF (367.09 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/jisse.2022.144284.1059 | ||
| Authors | ||
| Mohamed Fawzy Nasr* 1; Karam Youssef Maalawi1; Khaled Yihia2 | ||
| 1Mechanical Engineering Department, National Research Centre, Giza, Egypt | ||
| 2National Research centre | ||
| Abstract | ||
| Planetary gearboxes are used in different industrial fields such as automobiles, helicopters, heavy machinery and wind turbines. They have many advantages such as compact dimensions, less noise, high gear ratio and higher torque-to-weight ratios, compared to standard parallel axis gearboxes. This paper presents a multi-objective optimization model for minimizing the mass of a planetary gear train and maximizing gear ratio under the constraints of gear teeth bending stress, contact stress and side constraints .The selected design variables are the module, gear teeth width, number of teeth for both sun and planet gears, inner diameter of both sun and planet gears and the outer diameter of the ring gear. Different types of materials for the planetary gears have been studied. The optimization problem has been formulated and solved using the Genetic Algorithm (GA). The obtained results indicated that the optimum mass of the planetary gear train has maximum values in case of stainless steel while has relatively equal values in case of plastic material. The maximum gear ratios were observed in case of 1.1 KW input power | ||
| Keywords | ||
| Multi-Objective Optimization; Planetary gear train; Module; Tooth bending stress; Contact stress | ||
|
Statistics Article View: 274 PDF Download: 159 |
||
