Abstract：Aiming at the difficulty of multi-parameter identification of permanent magnet synchronous motor (PMSM), this paper proposed a chaotic mutation niche particle swarm optimization algorithm with initial parameter optimization (NCOPSO), and designed a full-rank mathematical system with five parameters (stator winding resistance, stator cross-axis and direct-axis inductance, permanent magnet flux, moment of inertia) to be identified. Firstly, the particle swarm optimization was used to optimize the three initial parameters (inertia coefficient ω, learning factor c1, c2) of the basic particle swarm optimization algorithm. Then the niche strategy was applied to the optimized particle swarm: a niche population centering on the particles with small adaptive value changes in successive iterations was constructed. Finally, the chaotic mutation strategy is used: in each iteration process, a chaotic sequence was generated based on the optimal particles of each niche group. The optimal particles in the sequence were randomly replaced by a certain particle of the current niche population, and the worst particle of the niche mirror population was initialized at the same time. The feasibility and accuracy of the algorithm were verified by motor simulation and experiment.
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2020, Vol. 35 
