In the control of electric drives, inaccurate estimation of the motor parameters affects the robustness of the control. This effect is observed particularly when the linear lumped parameter-based models are employed to represent a machine composed of nonlinear magnetic materials. Finite-element (FE) models consider the material nonlinearity accurately. However, implementing these models in a real-time system is challenging due to the computational burden. In this article, we propose a fast-dynamic model, based on a model order reduction method, to control a permanent magnet synchronous machine in a wide range of speed. The stator currents in the rotor frame of reference are given as inputs to a reduced FE model, which computes the nodal values of the magnetic vector potential and thereafter the flux linkages. A discrete-time model is used to control the rotor speed and the stator current components. Experiments on a 2.2 kW interior permanent magnet synchronous machine verify the viability of the proposed model.
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Far et al. (2020) studied this question.
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