Two main classes for Maximum-Torque-Per-Ampère (MTPA) tracking in Interior Permanent Magnet (IPM) and Synchronous Reluctance (SynR) machines have been proposed in literature, namely Real Signal Injection (RSI) and Virtual Signal Injection (VSI). Unfortunately, a fair evaluation of the accuracy and performance of each class and a direct comparison between them is still missing, and is the first contribution of this paper. Validation and evaluation of the accuracy and performance is considered, by taking into account a non-linear model of a SynRM, based on an analytical representation of flux-linkage, in order to reduce the errors due to approximations, allowing therefore a quantitative comparison. A new technique is proposed, allowing both tuning and adaptation of the VSI tracking loop gains, therefore assuring both stability and the same dynamical performance in the whole machine torque/speed range. Finally, an original strategy to compensate for steady-state MTPA tracking errors due to non-linear flux maps is proposed, thus increasing the accuracy of VSI even in the case the machine flux maps are known with relatively low quantization. An IPM motor drive is considered to validate the proposed contributions.
MTPA Tracking Algorithms for IPMSMs and SynRMs: Accurate Evaluation and Adaptive Tuning of Real Signal Injection and Virtual Signal Injection
Calligaro S.;Petrella R.;Shahdadi A.
2020-01-01
Abstract
Two main classes for Maximum-Torque-Per-Ampère (MTPA) tracking in Interior Permanent Magnet (IPM) and Synchronous Reluctance (SynR) machines have been proposed in literature, namely Real Signal Injection (RSI) and Virtual Signal Injection (VSI). Unfortunately, a fair evaluation of the accuracy and performance of each class and a direct comparison between them is still missing, and is the first contribution of this paper. Validation and evaluation of the accuracy and performance is considered, by taking into account a non-linear model of a SynRM, based on an analytical representation of flux-linkage, in order to reduce the errors due to approximations, allowing therefore a quantitative comparison. A new technique is proposed, allowing both tuning and adaptation of the VSI tracking loop gains, therefore assuring both stability and the same dynamical performance in the whole machine torque/speed range. Finally, an original strategy to compensate for steady-state MTPA tracking errors due to non-linear flux maps is proposed, thus increasing the accuracy of VSI even in the case the machine flux maps are known with relatively low quantization. An IPM motor drive is considered to validate the proposed contributions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
