Particle swarm optimization approach to optimal design of an AFPM traction machine for different driving conditions

Authors : Naghi ROSTAMI

Pages : 3234-3246

View : 10 | Download : 5

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :Axial flux permanent magnet insert ignore into journalissuearticles values(AFPM); machines can be employed as the traction motor of electric vehicles due to their high torque capability, high efficiency, modular and compact construction, and capability of integration with other mechanical components in integrated systems. Besides, the system efficiency can be further improved by optimal design of the selected electric machine. In this paper, an AFPM machine is optimized against two well-known driving cycles called the New European Drive Cycle insert ignore into journalissuearticles values(NEDC); and US06 and the influence of the driving cycle on the obtained machine parameters is evaluated. US06 is the more demanding driving cycle and thus the machine designed for this driving cycle demands more electrical loading compared to the machine designed for NEDC. Therefore, the copper loss minimization becomes more important for the US06-optimized machine compared to the NEDC-optimized machine. Consequently, the machine design parameters optimized for different driving cycles would be quite different. Compared to the NEDC-optimized machine, the US06-optimized machine has a lower number of coil turns, lower height of teeth, and lower diameter ratio to limit the copper losses. Furthermore, fewer magnets are needed for the motor optimized for the NEDC compared to the motor optimized for US06. A quasi-3D approach and particle swarm optimization algorithm are used in the semianalytical design optimization process. Additionally, computationally efficient 3D finite-element analysis and measurements made for the prototype AFPM machine are carried out to validate the accuracy of the quasi-3D approach.
Keywords : Electric vehicle, axial flux permanent magnet machines, traction motor, driving cycle, design optimization