This paper deals with on-line parameter identification of induction motors (IM) by means of least square techniques .Using stator voltages, stator currents and velocity as input-output data. For analytical identification by recursive least square (RLS) algorithms, filtering of experimental data is performed by means of anticausal filters. The simulation results show that error of the parameter estimation of the rotor resistance, self inductance of the rotor winding, as well as the stator leakage inductance are less than 5% .It demonstrate the practical use of the identification method.

The air gap flux density distribution in different radius of three conditions such as stator iron without slotting, stator iron slotting under no load condition and stator iron slotting under load condition is discussed using the 2-D finite element method. The effect of slotting on the distribution of air gap flux density of permanent magnet brushless motor is also analyzed.