Abstract
The surface-mounted and interior permanent magnet synchronous motor(SIPMSM) has the characteristics of multiple variables, strong coupling and nonlinearity. In order to improve the performance of SIPMSM, this paper presents a multi-objective optimal design process using Taguchi and response surface methodology(RSM). The peak value of cogging torque(PVCT), ratio value of average torque and permanent magnet weight(RTW), torque ripple and back-EMF total harmonics distortion(ETHD) are selected as optimization goals. The experiment matrix is established by Taguchi method, and analyzed the tendency and proportion of the effect of the optimization parameters on SIPMSM performance. The rules of choosing multi-objective optimization parameters are obtained. The least-squares method is used to establish the optimal objective function, and RSM is used to obtain the resolutions of the optimization objective function. Comparing the initial performance with optimized performance verifies the effectiveness of the proposed method.
Highlights
The traditional surface-mounted permanent magnet motor owns faster dynamic response and smaller torque ripple, but its power density is lower
The basic electromagnetic characteristics of the SIHPMSM are analyzed by the magnetic circuit method and the finite element(FE) method, and the optimal parameters are obtained by Taguchi method
To overcome the weaknesses of the RSM and Taguchi method, this paper proposes the optimization process using the combination of Taguchi and the RSM
Summary
The traditional surface-mounted permanent magnet motor owns faster dynamic response and smaller torque ripple, but its power density is lower. Ref.[4] proposes another kind of surface-mounted and interior permanent magnet synchronous motor(SIPMSM). While adopting the single variable optimization method, the mutual influence among various parameters is not considered[5]. In Ref.[6-9], the global optimization methods such as genetic algorithm, simulated annealing method and particle swarm optimization are adopted in the motor optimization design The advantages of these optimization methods are that all the uncertainties can be included in the optimization goal. The local optimization methods include the deterministic methods such as magnetic network method, complex shape method and simple method These optimization methods have very good convergence effect for single-objective optimization, but they cannot realize multi-objective optimization design. Taguchi has the advantages of fast convergence and high efficiency In recent years, this method has been widely used in optimal design of the motor[10-15].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
