Design and optimization of electrical machines for electric vehicle (EV)
applications is a challenging task. In response to variable driving
circumstances, the machine should be designed to operate in a wide range of
speed and torque. This paper aims to optimize a surface-mounted axial-flux permanent-magnet
(AFPM) traction machine taking the influence of the driving cycle into account.
The AFPM motor is designed to maximize the overall efficiency over a predefined
driving cycle. EV requirements and geometric constraints are taken into account
in the design process. Hundreds of operating points in a driving cycle are
reduced to the limited number of representative points by calculating the
energy centre points in the energy distribution curve. Therefore, the number of
calculations during the design optimization is significantly reduced. An
analytical design procedure based on quasi-3D approach is used for accurate
modelling of AFPM machine and genetic algorithm (GA) is implemented to find out
the optimal design parameters. Functionality of the proposed approach is
validated via comprehensive three-dimensional (3D) finite-element analysis
(FEA).
Primary Language | English |
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Subjects | Engineering |
Journal Section | Electrical & Electronics Engineering |
Authors | |
Publication Date | June 1, 2019 |
Published in Issue | Year 2019 Volume: 32 Issue: 2 |