Design Optimization of Induction Motors with Different Stator Slot Rotor Bar Combinations Considering Drive Cycle

In this paper, a sequential Taguchi method for design optimization of an induction motor (IM) for an electric vehicle (EV) is presented. First, a series of empirical and mathematical relationships is systematically applied to reduce the number of possible stator slot rotor bar (SSRB) combinations. Then, the admissible optimal combinations are investigated and compared using finite element (FE) simulation over the NEDC driving cycle, and the three best combinations are selected for further analysis. Each topology is optimized over the driving cycle using the k-means clustering method to calculate the representative working points over the NEDC, US06, WLTP Class 3, and EUDC driving cycles. Then, using the Design of Experiment (DOE)-based Taguchi method, a multi-objective optimization is carried out. Finally, the performance of the optimized machines in terms of robustness against manufacturing tolerances, magnetic flux density distribution, mechanical stress analysis, nominal envelope curve and efficiency map is carried out to select the best stator slot rotor bar combination. It is also found that the K-means clustering method is not completely robust for the design of electric machines for electric vehicle traction motors. The method focuses on regions with high-density working points, and it is possible to miss the compliant with the required envelope curve.