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A temperature estimation algorithm (thermal observer) that provides accurate estimates of the thermal states of an electric machine in real time is presented. The thermal observer is designed to be a Kalman filter that combines thermal state predictions from a lumped-parameter thermal model of the electric machine with temperature measurements from a single external temperature sensor. An analysis based on the error covariance matrix of the Kalman filter is presented to guide the selection of the best sensor location. The thermal observer performance is demonstrated using a 3.8 kW permanent-magnet machine. Comparison of the thermal observer estimates and the actual temperatures demonstrate that this approach can provide accurate knowledge of the machine's thermal states despite modeling uncertainty and unknown initial machine thermal states.

Detailed computer models of system components for More Electric Aircraft have been developed using the Advanced Control System Language (ACSL) and its graphical front-end, Graphic Modeller. Among the devices modeled are a wound-rotor synchronous generator with parallel bridge-rectifier outputs, a switched-reluctance generator, and various loads including a DC-DC converter, an inverter-driven induction motor, and an electro-hydrostatic actuator. Results from the simulations are presented together with corroborating experimental test results.