Research on the Optimization of Asynchronous Motor Slot Type Aiming at Efficiency

Three-phase asynchronous motors are widely used in the industrial field due to their simple structure, high reliability, strong adaptability, low cost, and easy control of weak magnetism. Motor optimization can improve motor performance, efficiency, and reliability, thereby achieving lower energy co...

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Bibliographic Details
Published in2024 7th International Conference on Mechatronics and Computer Technology Engineering (MCTE) pp. 5 - 10
Main Authors Lu, Daixing, Zhou, Xia, Shen, Ye
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.08.2024
Subjects
Ansys Maxwell
Finite element analysis
Genetic Algorithm
Genetic algorithms
Motors
Optimization
Python
Rotors
Shape
Slot Optimization Design
Software
Software reliability
Stators
Three-phase Asynchronous Motor
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DOI10.1109/MCTE62870.2024.11117993

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Summary:Three-phase asynchronous motors are widely used in the industrial field due to their simple structure, high reliability, strong adaptability, low cost, and easy control of weak magnetism. Motor optimization can improve motor performance, efficiency, and reliability, thereby achieving lower energy consumption. By combining the finite element method, initial three-phase asynchronous motor models are established and simulated using both Python and Ansys Maxwell software. With the aid of Genetic Algorithm, the optimization target is to reduce losses, with stator and rotor slot parameters as variables. The stator and rotor slot dimensions are optimized simultaneously. The motor models before and after optimization in Python and Ansys Maxwell are compared, and the results show that the energy loss of the motor after slot optimization is reduced by 29.17%, and the motor efficiency performance is improved, verifying the effectiveness of the induction motor slot optimization design method based on genetic algorithms.
DOI:10.1109/MCTE62870.2024.11117993