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| Parameter Identification of Permanent Magnet Synchronous Motor Based on Hybrid Variation RAO Algorithm |
| LI Hong-ji,JIAN Xian-zhong,WANG Zu-jian |
| School of Opto-Electronic Information and Computer Engineering, University of Shanghai for Science and Technology,Shanghai 200093,China |
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Abstract Aiming at the problem that PMSM parameter identification is prone to fall into local optimum, which leads to low accuracy and slow identification speed, a hybrid Variation RAO algorithm (GCRAO) was proposed to be applied to PMSM parameter identification. According to the distribution characteristics of Gauss and Cauchy functions, the raO-1 algorithm was improved by introducing the strategy of self-selecting the optimal individual variation in three running stages in real time. A permanent magnet synchronous motor model based on vector control (SVPMSM) was built by matlab/Simulink under the dq axis coordinates, and the standard test function test and simulation experiment were carried out. The test results show that the local mining ability and global exploration ability of GCRAO algorithm are improved, which verifies the effectiveness of the improved RAO-1 algorithm. Simulation results show that compared with RAO-1 and PSO algorithms, GCRAO algorithm can identify electromagnetic parameters faster and has better convergence accuracy.
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Received: 25 April 2022
Published: 21 September 2023
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| Fund:National Natural Science Foundation of China |
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2023, Vol. 44 
