A novel flux-weakening approach suitable for Surface-Mounted Permanent Magnet Synchronous Machines (SPMs) is presented in this paper. It consists in directly synthesizing the square magnitudes of the current and voltage vectors on the basis of an accurate SPM sampled-data model and of the reference torque profile. This enables optimal and easy management of SPM operating constraints, i.e. current limitation and voltage saturation, on the basis of which the dq reference current profile can be achieved, whatever the SPM speed and Constant Power Speed Ratio (CPSR) is, i.e. finite or infinite. The effectiveness of the proposed flux-weakening approach is highlighted by both simulation and experimental results, which refer to SPMs with finite and/or infinite CPSR and driven by a predictive control algorithm.
A novel flux-weakening approach for Surface-Mounted Permanent Magnet Synchronous Machines / A., Damiano; G., Gatto; I., Marongiu; Perfetto, Aldo; A., Serpi. - (2013), pp. 2547-2552. (Intervento presentato al convegno IECON 2013 – 39th Annual Conference of the IEEE Industrial Electronics Society tenutosi a VIENNA nel 10-13 Novembre 2013).
A novel flux-weakening approach for Surface-Mounted Permanent Magnet Synchronous Machines
PERFETTO, ALDO;
2013
Abstract
A novel flux-weakening approach suitable for Surface-Mounted Permanent Magnet Synchronous Machines (SPMs) is presented in this paper. It consists in directly synthesizing the square magnitudes of the current and voltage vectors on the basis of an accurate SPM sampled-data model and of the reference torque profile. This enables optimal and easy management of SPM operating constraints, i.e. current limitation and voltage saturation, on the basis of which the dq reference current profile can be achieved, whatever the SPM speed and Constant Power Speed Ratio (CPSR) is, i.e. finite or infinite. The effectiveness of the proposed flux-weakening approach is highlighted by both simulation and experimental results, which refer to SPMs with finite and/or infinite CPSR and driven by a predictive control algorithm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.