An inverse problem methodology for design and optimization of an interior permanent magnetic BLDC motor

In the theory of inverse problem, the parameters identification by optimization is considered as one of its main applications. This paper presents an optimal design of a slotted permanent magnet Brushless DC (BLDC) motor with surface mounted magnets. The inverse problem method is applied by using a thriving solver afforded by the nonlinear optimization toolbox of Matlab 'Fmincon', this function is based on Active-Set and Sequential Quadratic Programming approaches with calculation of the Hessian from Quasi-Newton algorithm. The optimal magnetic field density considered as the main objective is obtained by picking several parameters and analyzing their effects. The proposed approach is highlighted by using the obtained parameters in the design of the motor. The Finite element method is applied on the motor for numerical analysis by using FEMM magnetic coupled with Matlab code. Effectiveness and robustness of the proposed approach are verified by a comparison between the initial and optimized design.