Overview of Fundamental Frequency Sensorless Algorithms for AC Motors: A Unified Perspective
Jiahao Chen, Xin Yuan, Frede Blaabjerg, Christopher H. T. Lee
Abstract
This article uses the 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-current model (VM) estimator or indirectly solved using current-speed model (CM) estimator. The latter turns the torque estimation problem into a speed estimation problem. The stator flux in VM and the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> -axis angle in CM are deemed as the two sets of original states for the sensorless drive. Through the change of states, the direct torque estimation can be realized via observer designs, whereas the speed dependency in the dynamics of the unknown state [e.g., active flux and electromotive force (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 that the unmodeled voltage in the active flux dynamics reveals current flowing in rotor bars and can be further modeled, 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 the slow reversal test, where local weak observability of ac motors can be potentially preserved.