Magnetizing inductance measurement system for electric machines using static rotor positioning

Abstract

This thesis focuses on developing a novel inductance measurement technique for electric machines, termed the quasi-static method. The approach is broadly applicable to various machine types and is particularly effective for measuring the inductance of machines with highly electrically conducting rotors, for which AC-signal-based measurement approaches are not applicable. The Axially Laminated Anisotropic Synchronous-Reluctance Machine (ALASynRM) is a typical instance of machines with highly conducting rotor. Alternating flux induces eddy currents in a conducting rotor. They interfere with the measurement, and therefore conventional AC-based techniques cannot yield precise inductance values. The investigation is motivated by the demand for the actual accurate measured inductance as function of different rotor positions of a newly developed motor which can be used as a feedback for further motor design optimization, adjustment of the control algorithm and for more precise understanding of the motor performance characteristics and load capabilities.

To address this, a new accurate inductance measurement system, which operates at standstill using quasi-static current injection, thereby mitigating eddy-current effects, has been developed. Inductance is obtained for various rotor angles spanning an entire mechanical cycle, enabling harmonic spectral analysis of the inductance variation. The method includes a comprehensive uncertainty evaluation that improves the reliability and precision of the results by taking into account various sources of measurement error.

First, the new technique is simulated with an identical FEM model in the Altair Flux simulation platform, and then it is experimentally confirmed on a 27 kW high-speed SynRM prototype with an axially laminated anisotropic high electrically conducting rotor. By highlighting the relationship between inductance, rotor position, and measurement uncertainty, this paper contributes valuable insights that can inform the design and optimization of future motor systems.