Comparative analysis of features of online numerical methods used for parameter estimation of PMSM

As permanent magnet synchronous motors (PMSM) have high power density, efficiency, good dynamic performance, and small size they are becoming popular in electric vehicle (EV) applications. Control performance the efficiency of system get affected due to electrical, mechanical parameters. Parameters value gets by voltage source inverter (VSI) non-linearities, temperature magnetic saturation effects. If exact parameters for particular torque speed requirement found, increases. There various offline online methods finding Offline easy implement but requires extra setup estimate steady state. Because effects transient conditions taken into account during identification, obtaining real-time data under running more popular. An overview about numerical electrical PMSM is given. It discusses difference between terms computational cost, convergence speed, noise identification error. Choosing method will be using this work. For inductance estimation, extended Kalman filter (EKF) algorithm has an error 0.24% effect -0.3% VSI non-linearities effect. The Rs ψf recursive least square (RLS) 0.5% 0.02%, respectively, when considered. EKF RLS algorithms proposed.