Collective Behavior based Slime Mold Optimization with application to UAV Energy conversion device analysis

As an extensively used traction component of unmanned aerial vehicles (UAV), outer-rotor-permanent- magnet-synchronous-motor with inner-periphery-inset- magnet structure (OR-PMSM-IPIM) has eminent advantages with respect to its electromagnetic performance. In order to achieve light weight, high efficiency, efficient speed-torque and low turbulence in UAV, a novel method for optimizing design parameters of OR-PMSM-IPIM is proposed in this paper. A modified slime mold inspired optimization (SMO) algorithm is designed by introducing its collective behavior and swarm intelligence in the environment. In order to avoid collapsing for local optimal spots and enhance diversity in the population, the modified framework of SMO is proposed in this work by introducing complex group interaction patterns in the traditional SMO algorithm. In order to verify the effectiveness and convergence speed of proposed methodology, few comparative experiments are administered. The application of proposed method is tested by developing design-parameter-optimization (DPO) problem for OR-PMSM-IPIM. The analysis results show that the performance of optimized model of OR-PMSM-IPIM has been improved through proposed SMO design optimization.