A Taguchi-Based Grey Relational and Principal Component Analysis For Optimal Design of Thrust Density and Temperature of Trapezoid Ironless Linear Motor
In this study, Taguchi based on the grey relational analysis (GRA) was integrated with principal component analysis
for a trapezoidal ironless linear motor to determine the significant design parameters, including the magnet baseline,
coil-winding width, coil-winding height and coil diameter, for the maximal thrust density and minimal temperature. Compared
with the original motor, the thrust density and temperature were increased by 14.10% and 9.24%, respectively. The simulation
results show that the proposed approach effectively improve the performance of ironless linear motors, and it could be used as
a critical reference for designing the linear motors.
Index Terms- Grey relational analysis, Taguchi method, Trapezoidal ironless linear motor.