Iron loss of stator is one of the main losses of interior permanent magnet synchronous motor (IPMSM). Therefore, effectively reducing iron loss is of great significance for improving operating efficiency. The air gap flux density is analyzed under various operating conditions, and three models for calculating iron loss are analyzed and compared. Among these, the orthogonal decomposition model demonstrates greater accuracy and is relatively straightforward to apply. Consequently, this paper utilizes the orthogonal decomposition model for iron loss calculations. Iron loss is primarily influenced by the operating frequency, as well as the amplitude and harmonic content of the air gap flux density. Thus, at a specific frequency, enhancing the sine degree of the air gap flux density can significantly decrease iron loss. A three-layer I2V type is proposed to further improve sine degree of air gap flux density, achieving high efficiency and low iron loss. V type, IV type and I2V type are selected as the comparative objects for optimization research, and air gap flux density and harmonic contents of three different rotor structures are analyzed and compared, the results show that I2V type have the lowest total harmonic distortion (THD) rates. Compared with V type, the THD rates of I2V type decreased by 27.2%. Iron losses of three different optimized rotor structures are analyzed and compared. Compared with the other two, the results show that I2V type is the smallest, and is significantly less than that of the other two especially under deep flux weakening conditions, which can improve operation range of high efficiency. The I2V prototype is processed and manufactured, and experimental platform is built. Experimental verifications are conducted on loss and efficiency. The test results are basically consistent with FEA results, proving the superior performance of I2V type proposed in this paper, as well as correctness of analysis method and effectiveness of simulation calculations.
Building similarity graph...
Analyzing shared references across papers
Loading...
Lianbo Niu
Scientific Reports
Xinxiang University
Building similarity graph...
Analyzing shared references across papers
Loading...
Lianbo Niu (Mon,) studied this question.
www.synapsesocial.com/papers/69d892886c1944d70ce03ed5 — DOI: https://doi.org/10.1038/s41598-026-46669-6