Overview of Fundamental Frequency Sensorless Algorithms for AC Motors: a
Unified Perspective
Abstract
This paper uses active flux concept to review fundamental frequency
sensorless algorithms for both induction and permanent magnet motors in
one framework. Fundamentally, sensorless torque estimation can be
directly solved using voltage model (VM) estimator, or indirectly solved
using current model (CM) estimator. The latter turns the torque
estimation problem into a speed estimation problem. The stator flux in
VM and the d-axis angle in CM are deemed as the two sets of original
states for sensorless drive. Through change of states, the direct torque
estimation can be realized via observer designs; whereas the speed
dependency of the unknown state (e.g., active flux and emf) gives rise
to a class of speed estimation methods, known as model reference
adaptive system (MRAS). The idea of a general speed observer is proposed
to summarize various separate speed estimation methods needed for direct
torque estimation. It is suggested to adopt inherently sensorless
designs such that two-way coupling between torque estimation and speed
estimation is avoided. For induction motors, it turns out the unmodelled
voltage in the active flux dynamics reveals current flowing in rotor
bars and can be further modelled, for which the solutions to
regeneration instability problem are discussed, and change of states is
recommended to attain global stability. Finally discussed are the
results of slow reversal test, where local weak observability of ac
motors can be potentially preserved.