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This study proposes a model‐based control strategy for flux weakening operation of a synchronous reluctance machine, with a methodology that is extendible to any synchronous machine. The strategy leverages in the presence of digital non‐linear models that describe the relation between currents and flux linkages in the machine. Such models are usually needed for conventional maximum‐torque‐per‐ampere control and sensorless control, but here they are exploited to achieve flux‐weakening operation without the need of flux weakening regulators, ensuring a seamless transition between the operating regions of the machine. The external voltage regulation loop for flux weakening is thus eliminated and substituted by a combination of look‐up tables and binary searches, which are executed within one digital control period and which generate the required current and voltage references that fulfil the drive limitations. The method can also be coupled with mechanisms to compensate for magnetic parameter inaccuracies, to achieve an accurate tracking of the reference torque. The proposed solution is simulated and validated in a laboratory test bench on an 11 kW synchronous reluctance machine. [ABSTRACT FROM AUTHOR]

The paper analyses a combined current model–voltage model estimator for flux linkages in permanent magnet synchronous machines, with the capability of converging to exact flux estimation even in presence of mismatches because of magnetic saturation. As a trend in next‐generation electric drives, the whole algorithm, including both the flux estimator and the standard field‐oriented control, has been implemented in a field‐programmable gate array (FPGA) chip. Simulations and experimental tests, along with some figures for the FPGA selection, have been included in the study. [ABSTRACT FROM AUTHOR]