An approach to weight optimization of a spur gear

Abstract

Lightweight is one of the most important criterion in the optimum design of gear set for motorsport and aerospace application. A tradeoff between optimum weight and failure modes of gear is a subject of interest for researchers and the industry. In the present work weight of a single-stage spur gear set is optimized. This nonlinear constrained optimization formulation has been solved by using differential evolution algorithm. A total of six design variables corresponding to gear geometry and material property are considered. The results obtained are compared with those of published heuristics like genetic algorithm, simulated annealing, and particle swarm optimization algorithm, respectively. The optimization is performed in such a way that the design variables satisfy all constraints at optimum solution. Apart from this, several constraints related to scoring are included in the optimization. The constraint violation study is performed to prioritize the constraints. The sensitivity analysis is carried out to see the effect of manufacturing tolerances of design variables on weight of the gear set. The optimality of the solution has been ensured through the convergence study. The optimization reveals that the reported results are also encouraging in terms of objective function values and CPU time. In addition, the optimum design variables obtained through the weight optimization of spur gear set are used for preparation of a CAD model. Then the stress analysis using finite element analysis is performed on the gear set to identify the critical stress region in the optimized gear set.