Optimal design of the flywheel using nature inspired optimization algorithms

This paper presents the optimal design procedure of a flywheel using a cubic B-spline curve. The flywheel plays a vital role in storing kinetic energy in modern machines. The kinetic energy evaluates the performance of the flywheel. In order to improve the kinetic energy of a flywheel, a shape optimization model of the flywheel, with maximization of kinetic energy, is formulated using a cubic spline curve under the constraints of the mass of flywheel, and the maximum value of Von Mises stresses at all points along the radial direction. The Von Mises stresses at all points are determined using the two-point boundary value differential equation. The control points of the cubic B-spline curve are taken as design variables. Then the formulated problem is solved using particle swarm algorithm (PSO), genetic algorithm (GA), and Jaya algorithm. The proposed approach is applied to the flywheel of an agricultural thresher machine. It is found that the Jaya algorithm gives better results compared to the other algorithms. The optimized shape of the flywheel is simulated using MSC ADAMS software