volume | PIER Journals

Abstract

A parameter identification method based on an improved hunter prey algorithm is proposed to address the issues of poor accuracy and speed in traditional permanent magnet synchronous motor parameter identification methods. By using the Fuch infinite folding chaotic strategy to evenly distribute the initial individuals to enrich their diversity and using the golden sine algorithm to optimize the population search path, the algorithm's local development ability and global search ability are improved. The reasons for the dead time effect of the inverter are analyzed, and the input voltage is compensated for through the rotation coordinate method. SIMULINK simulation and physical experiment indicate that the improved algorithm has faster rate of convergence and higher recognition accuracy than the unmodified algorithm, and can effectively identify motor parameters. On this basis, adding dead time compensation effectively eliminates partial harmonics of the phase current and suppresses the occurrence of zero current clamping phenomenon. Compared with the situation without dead time compensation, the identification error of the four parameters has decreased from below 4.23% to below 2.21%.

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Mr. Chengmin Wang

Dr. Aiyuan Wang