Experience in Design Optimization of Induction Motor Using 'SUMT' Algorithm

Design optimization of an induction motor is considered as a nonlinear multivariable constrained programming problem. A set of nine basic variables is identified and suitable constraints are imposed to meet the thermal, starting and other performance requirements of the machine. Six different objective functions are considered to facilitate the selection of suitable optimized designs for any given application. The optimization is achieved through Rosenbrock's method of direct search in conjunction with the sequential unconstrained minimization technique (SUMT). For a typical 3.7kw cage motor, the optimized design results with different objective functions are presented.