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This article proposes a nonintrusive parameter identification procedure suitable for Internet-of-Things (IoT)-embedded isotropic permanent magnet synchronous machines (PMSMs). The method is designed for scenarios where only measurements collected without additional sensors, dedicated tests, or signal injection from in- service off-the-shelves motor drives are available. After automatic detection of the steady-state operating conditions (OCs) defined by the triplet current–speed–temperature, the rotor flux linkage, the stator resistance, the inductance, and the inverter distorted voltage term are estimated using two operating points. Particular emphasis is placed in defining the criteria of selecting these two optimal OCs to minimize the estimation errors. The latter are due to the inevitable difference between the parameters in different operating points. As a vessel to investigate the effectiveness of the proposed parameter identification, experimental and simulation tests carried out on a high-speed PMSM drive have been used for validation purpose. The proposed method is also compared with the existing methods from the literature to demonstrate its superiority in the considered scenario.

Surface permanent magnet synchronous machines are one of the most widely adopted machine topologies in high-speed applications where efficiency and power factor cannot be compromised. Although the design of such machine type has been extensively investigated in both industry and academia, this work aims at addressing its limitations when applied in high-speed applications. First, this paper proposes an accurate design methodology for continuous-duty high-speed surface-mounted permanent magnets synchronous machines, capable of accounting for the rise of the speed-dependent losses and structural needs with a limited impact on the computational burden. The outlined approach can be used to speed-up the initial design stage as it allows to reduce the number of solutions to evaluate before commencing the refinement stages required before the definition of the final design. Indeed, the introduced design approach is used to systematically assess the maximum power capability as function of the maximum speed and the airgap thickness for a given outer envelope and cooling system. The influence of the high-speed limiting factors is deeply investigated also considering their effects on the machine geometries providing the highest torque. The selection of the final design is discussed and justified. Experimental results of the 4.2 kW-80 kprm prototype validate the design methodology.

This article investigates an innovative modulation technique for a predictive control applied to a synchronous reluctance motor (SyRM) drive. The new formulation of the duty cycles, in both linear and overmodulation regions, relies on the identified flux-versus-current characteristics. Furthermore, integral terms have been introduced in the predictive control to achieve satisfactory reference tracking performance with zero steady-state error, even under model parameters mismatches. Low current ripple with smooth and fast dynamic responses are achievable at fixed switching frequency over the whole current operating range. Simulations and experimental evidence show the effectiveness of the proposed controller against standard controllers such as field-oriented current control (FOC) and deadbeat current control (DBCC), guaranteeing low current ripple, robustness against parameters variations, and fast dynamic performance.