M. S. Hosseini, H. Javadi, S. Vaez-Zadeh,
Volume 16, Issue 1 (3-2020)
Abstract
Linear flux switching motors with simple passive segmented secondary, referred as Segmented Secondary Linear Flux Switching Motors (SSLFSMs), have low cost secondary and therefore are applicable to transportation systems like Maglev. However, it is shown that the SSLFSMs suffer from high thrust ripples. In this paper, minimizing SSLFSM thrust ripples besides maximizing its developed thrust are performed by considering the motor dimensions as design variables. Since the optimization of the motor is a high dimensional problem, a multi-level optimization method is employed to improve the machine performances and efficiency. According to the effects of the design variables on the optimization objectives, a sensitivity analysis is carried out to divide the design variables into two levels: mild-sensitive level and strong-sensitive level. Then, the two levels of design variables are optimized based on a mathematical model. Two different optimization methods as the Design of Experiment (DOE) and the Response Surface Method (RSM) are used in mild-sensitive level and the Genetic Algorithm (GA) is also used in strong-sensitive level. Based on FEM analysis, electromagnetic performance of the original motor and the optimal one are compared and the validity of the proposed optimization method is verified. Also, the effectiveness of the mathematical model used in thrust and thrust ripples calculations is evaluated and verified.
Ali Zarghani, Pedram Dehgoshaei, Hossein Torkaman, Aghil Ghaheri,
Volume 20, Issue 1 (3-2024)
Abstract
Losses in electric machines produce heat and cause an efficiency drop. As a consequence of heat production, temperature rise will occur which imposes severe problems. Due to the dependence of electrical and mechanical performance on temperature, conducting thermal analysis for a special electric machine that has a compact configuration with poor heat dissipation capability is crucial. This paper aims to carry out the thermal analysis of an axial-field flux-switching permanent magnet (AFFSPM) machine for electric vehicle application. To fulfill this purpose, three-dimensional (3D) finite element analysis is performed to accurately derive electromagnetic losses in active components. Meanwhile, copper losses are calculated by analytic correlation in maximum allowable temperature. To improve thermal performance, cooling blades are inserted on the frame of AFFSPM, and 3D computational fluid dynamics (CFD) is developed to investigate thermal analysis. The effect of different housing materials, the external heat transfer coefficient, and various operating points on the components' temperature has been reported. Finally, 3-D FEA is used to conduct heat flow path and heat generation density.
