Inductance Polynomial Fits in Sequential Quadratic Programming for Maximum Torque Per Ampere

Efficient control of permanent magnet synchronous motor drives requires accurate knowledge of its characteristic parameters. However, the inclusion of these highly nonlinear parameters can increase control complexity. In this work, polynomial fits are used to model inductances in the torque equation for the maximum torque per ampere optimization problem in order to capture the self and cross saturation that is inherent in interior permanent magnet synchronous machines (IPMSMs). The sequential quadratic programming (SQP) optimization algorithm is used since it can handle more highly nonlinear models. The importance of goodness of fit for each inductance polynomial is investigated via design of experiments (DOE) and analysis of variance (ANOVA). The performance of the technique is evaluated using co-simulation of MATLAB Simulink and finite element analysis (FEA) software.