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This paper presents a novel analytical model for a switched-reluctance machine (SRM) based on decomposition of its inherent double joint magnetic saliencies due to rotor and stator salient poles and saturation of magnetic field at high stator currents. With this method, the magnetic characteristics of the motor, such as flux linkage and incremental inductance, are decomposed to vector functions of rotor position and phase current. Dynamic state and torque equations for the SRM are derived on the basis of this representation. The proposed model is appropriate for online identification and for sensorless position control algorithms. It is easy to implement and computationally efficient. Comparison of the predicted motor magnetic characteristics to machine data from finite-element analysis verifies the accuracy of the model.