Paper Title
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.