Modelling of Interior Permanent Magnet Motor and Optimization of its Torque Ripple and Cogging Torque Based on Design of Experiments and Artificial Neural Networks

Interior permanent magnet (IPM) motors are the class of synchronous motors. They are known for their high-power density and effective speed control performance along with efficient torque per rotor volume. They are also capable of giving wide constant power operating range which makes them best suitable for electric vehicle applications (EV sector). However, the major task in the design of any IPM motor is the optimization of torque ripple and reducing the undesirable cogging torques. Rotor geometry is the primary design criteria in reducing the torque pulsations. In this work, the orthogonal experimental design (OED) is used for optimizing rotor geometry to discover the ideal combination of geometric parameters to reduce torque pulsations and cogging torques. Artificial neural network (ANN) is then modelled to find the optimum design for rotor geometry using metaheuristic algorithms. Finally, the results of the optimization process are verified by the conventional finite element analysis (FEA) method. Torque ripple and cogging torque are reduced by 65% and 12% respectively on post-optimization.