Computer-aided Experimental Identification of Line-start Permanent-magnet Synchronous-motor Parameters Based on Dynamic Electrical Processes

Line-start permanent-magnet synchronous motors (LSPMSMs) are energy-efficient alternatives to induction motors. However, LSPMSMs are associated with synchronization difficulties when starting in cases of high inertia, heavy loads, or supply-voltage sags. Models with lumped parameters and parameter identification are used to study the starting processes. A novel approach for identifying the parameters of an LSPMSM is presented based on reduced experimental data that only include the recording of oscillograms of instantaneous currents and voltages when starting the LSPMSM from an idle state. The parameters of the lumped model are determined using the Nelder-Mead method while minimizing the root-mean-square error between the experimental and calculated waveforms. Multiple starts under different initial conditions are considered owing to uncertain initial conditions, and the initial conditions are excluded from the parameter space of the objective function. The proposed method is used to identify the parameters of a commercially available 0.55 kW, 1 500 r/min LSPMSM sample. The results obtained by modeling the starting processes of the LSPMSM using the identified parameters are similar to the experimental results.