This study presents a self-commissioning procedure for the estimation of the flux linkage curves of synchronous reluctance machines. The procedure exploits a quasi-standstill condition obtained by imposing fast torque oscillations. The flux linkage is calculated by means of a pure integration of the voltages and currents. With respect to the existing procedures, the proposed one tackles the problem of the limited knowledge of the core losses in the electrical machine, which is shown to induce erroneous estimation results for the case under investigation. A theoretical analysis supported by extensive laboratory measurements is shown, proving the effectiveness of the proposed approach.
This work discusses an online stator resistance estimation method for synchronous machines. Multiple improvements are provided with respect to a similar method already been used for induction machines. The method is based on the temporary injection of a DC voltage in the machine phases during normal operation. The stator resistance estimation is obtained by means of the Ohm's law. The proposed scheme works entirely in the stator fixed reference frame, without the need of any machine parameter.The selection of the DC injection level is discussed, as well as the countermeasures for reducing the spurious harmonics appearing in the currents and the torque when the machine is speed-and current-regulated. In particular, minimum electric loss and minimum torque ripple due to the injection is achieved. Moreover, as an alternative to conventional low-pass filtering of the measured signals, it is shown that the resistance estimation can be obtained by averaging the signals over few electric periods. Experiments prove the validity of the proposed approach.
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
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