Parameter Identification of Permanent Magnet Synchronous Motor Based on Improved Beetle Swarm Algorithm

In this paper, a method of parameter identification of Permanent Magnetic Synchronous Machine (PMSM) based on improved Beetle Swarm Optimization Algorithm (BSO) is proposed. The idea is to combine Beetle Antennae Search Algorithm (BAS) and Particle Swarm Optimization (PSO). The algorithm adopts adaptive weights and adaptive learning factors to optimize parameters, and adopts variable step search strategy and nonlinear inertia factor to form an improved BSO optimization algorithm. The simulation results show that the improved BSO algorithm can identify PMSM parameters faster, has faster convergence speed, higher identification accuracy, good dynamic performance and small identification error.