The article deals with the flux linkages estimation of a synchronous motor during either speed or load transients. The nonlinear magnetic model is obtained by a radial basis function neural network (NN), which yields a differentiable function as link among currents and flux linkages. As a distinctive feature, the training of the NN is performed by an innovative algorithm that operates both at steady state and during speed and load transients. The method has been validated experimentally by several tests performed on different synchronous reluctance and interior permanent magnet motor drives.
Magnetic Model Identification of Synchronous Motors Considering Speed and Load Transients
Ortombina L.;Pasqualotto D.;Tinazzi F.
;Zigliotto M.
2020
Abstract
The article deals with the flux linkages estimation of a synchronous motor during either speed or load transients. The nonlinear magnetic model is obtained by a radial basis function neural network (NN), which yields a differentiable function as link among currents and flux linkages. As a distinctive feature, the training of the NN is performed by an innovative algorithm that operates both at steady state and during speed and load transients. The method has been validated experimentally by several tests performed on different synchronous reluctance and interior permanent magnet motor drives.
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