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A comprehensive diagnostic and prognostic method is introduced for assessing the condition of stator winding insulation and predicting its failure time. A diagnostic method is developed by building an analytical model of the stator winding. Degradation is simulated by altering the permittivity and conductivity of the insulation in a finite element model simulation and changing the analytical model accordingly. The diagnostic method is performed with an oscilloscope and other common hardware. A prognostic method is introduced which is used to predict the remaining useful life of the insulation based on fitting insulation current measurements to an exponential decay model. The diagnostic method is verified with the analytical model for multiple levels of degradation and experimentally for the healthy case. The prognostic method is verified with simulated degradation data.

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This paper proposes a multiple lookup table basedcontroller for operation in the complete torque and speed range of an IPM machine. A complete characterization is carried out to determine the machine fluxes for any given current. The fluxes are then used to calculate the nominal controller. A controller is then calculated for each of four sets of flux linkage data with a small flux error introduced; this is to account for small parametric error. An algorithm using airgap power and voltage is used to select a lookup table which reduces error in developed torque. Sensitivity is then used to determine the effectiveness of the proposed controller. From this, the proposed controller leads to reduced torque error and reduced sensitivity of the torque to flux error. Actual characterization data from a 10kW IPM machine is used to develop all controllers and simulations. The nominal and proposed controller is then applied to the actual IPM machine to validate the proposed controller.