| Interior Permanent Magnet Synchronous Motor(IPMSM)is widely used in transportation,flywheel energy storage,aerospace and other fields because of its advantages of high power density,high efficiency and high torque density.With the development of power electronics technology,multiphase motors are gradually used in high power applications because of their ability to achieve low voltage and high power output,high reliability,and abundant control resources.In order to improve the reliability and operational performance of the motor for flywheel energy storage,a sixphase permanent magnet synchronous motor is designed and multi-objective optimized in this paper.Firstly,the mathematical model of the six-phase motor is analyzed,and the mathematical model of the six-phase permanent magnet synchronous motor is established in the natural coordinate system,and the mathematical models of the motor in the stationary coordinate system and in the rotating coordinate system are calculated by coordinate transformation,respectively.The VSD-based vector control simulation model of the six-phase motor is built in MATLAB/Simulink,and the current is analyzed.Secondly,the initial motor design scheme is determined.By analyzing the relationship between electromagnetic performance and motor structural dimensions,a1 MW six-phase dual Y-shift 30° built-in permanent magnet synchronous motor was designed.The motor’s cogging torque,load torque,torque pulsation,and no-load counter potential distortion rate were analyzed using the finite element software Maxwell.The performance of the motor is enhanced by the rotor diagonal pole segmentation method,and the diagonal pole angles corresponding to different numbers of segments are calculated to analyze the effects of different diagonal pole angles on the electromagnetic performance of the motor.Then,a multi-objective and multi-parameter optimization method combining parameter stratification and agent model is proposed to take output torque,loss,torque pulsation and the fifth and seventh harmonic values of no-load line BEMF as the optimization objectives,and seven optimization parameters such as pole arc coefficient,air gap size,permanent magnet thickness,isolation bridge length and isolation bridge width are selected,and the optimization variables are divided into three layers by calculating the sensitivity of the parameters to the optimization objectives.Taking the torque pulsation,electromagnetic torque,loss,no-load BEMF potential 5th and 7th harmonics of 1MW symmetrical V-type built-in six-phase permanent magnet synchronous motor as the optimization objectives,the agent model of the motor is established using BP neural network and polynomial response surface method,respectively,and the Multi-Objective Genetic Algorithm(MOGA)is used for the first layer parameters.The NSGA-II algorithm is used to find the optimal response surface for the second layer parameters to determine the optimal parameters corresponding to the minimum torque pulsation,the fifth and seventh harmonics of the no-load line BEMF and the maximum output torque,and the finite element software is used to verify the anisotropy of the optimized motor performance.Finally,the experimental platform of the six-phase permanent magnet synchronous motor is designed,and experiments are conducted under no-load conditions of the six-phase motor,and the correctness of the simulation is verified by relatively independent tests.The results show that the six-phase double Y-shift 30° permanent magnet synchronous motor designed in this paper can achieve high power output,and the optimized motor has improved efficiency,reduced torque pulsation,reduced no-load line BEMF distortion rate,increased electromagnetic torque by 4.7%,and excellent performance in all aspects.The proposed optimization method is verified to be correct and effective,which enriches the multi-objective optimization method for multiphase motors and provides a reference solution for the design of multiphase high-power motors. |
PDF Full Text Request