Parameter identification of permanent magnet synchronous motor based on modified- fuzzy particle swarm optimization

被引:10
作者
Zhou, Shuai [1 ]
Wang, Dazhi [1 ]
机构
[1] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110819, Peoples R China
关键词
Permanent magnet synchronous motor; Online parameter identification; Modified-fuzzy particle swarm algorithm(MDFPSO);
D O I
10.1016/j.egyr.2022.11.124
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Accurate estimation of PMSM parameters is beneficial to the high performance operation of PMSM. In order to prevent PSO from falling into the local optimal solution in the PMSM parameter identification process, so as to improve the accuracy of identification results, a modified fuzzy particle swarm optimization (MDFPSO) is proposed, which changes the speed of each particle from only affected by the optimal particle to affected by the surrounding particles, This improvement guarantees the identification accuracy of the algorithm, and introduce the convergence factor to ensure that the MDFPSO can converge. Simulation results show that the MDFPSO algorithm is effective in PMSM parameter identification. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:873 / 879
页数:7
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