Offline Parameter Self Learning Method for General Purpose PMSM Drives With Estimation Error Compensation
Offline parameter identification of permanent magnet synchronous machines (PMSMs) is of great importance for general purpose drives with sensorless control. This paper proposes an amplitude auto adjusting signal injection (ASI) method for the parameter self learning of PMSMs at standstill considering inverter nonlinearities and the digital time delay effect. The ASI method achieves the inductance identification process under various dq axis currents and at the same time prevents the unexpected rotor rotation during the self commissioning process. For the test PMSM, the spatial inductance maps of dq axes and abc phases concerning the magnetic saturation and cross coupling effects are identified along with the stator resistance. To enhance the estimation accuracy, an error model of the inverter nonlinearities in dq axes is established, and a compensation method independent of inverter parameters is proposed based on the Hermite interpolation. In addition, the influence of the digital time delay effect is analyzed and compensated based on the transient model of the circuits. The effectiveness of the proposed parameter self learning scheme is confirmed on a 2.2 kW PMSM drive. The accuracy of the experimental results is validated by finite element analysis on the test machine.
IEEE Transactions on Power Electronics