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Accurate rotor time constant (<inline-formula> <tex-math notation="LaTeX">$T_{r}$ </tex-math></inline-formula>) value is necessary to ensure an acceptable performance of the indirect field-oriented control (IFOC) strategy, where a detuned <inline-formula> <tex-math notation="LaTeX">$T_{r}$ </tex-math></inline-formula> affects rotor flux orientation and, in turn, results in poor dynamic and steady-state response of torque. The problems associated with detuned <inline-formula> <tex-math notation="LaTeX">$T_{r}$ </tex-math></inline-formula> will be exacerbated in sensorless drives when a model-based speed estimation algorithm is employed. This article investigates the problem of simultaneous identification of the rotor time constant and rotor speed for sensorless IFOC of six-phase induction motor (6PIM) drives. First, an adaptive observer is proposed for online detection of the low-frequency sinusoidal signal, which is intentionally injected into the rotor flux command. Then, a novel model reference adaptive system (MRAS)-based <inline-formula> <tex-math notation="LaTeX">$T_{r}$ </tex-math></inline-formula> estimator is proposed using the detected signal. The Lyapunov stability theorem is used to ensure the asymptotic stability of the proposed identification system. The proposed method is based on the induction machine (IM) model in primary subspace, i.e., <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>&#x2013;<inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> subspace. Hence, it is usable for other multiphase IM (three phases and higher). Nevertheless, the 6PIM is adopted here as a case study. The simulation and experimental results clarify the effectiveness of the proposed parallel estimation system.

An Adaptive Identification of Rotor Time Constant for Speed-Sensorless Induction Motor Drives: A Case Study for Six-Phase Induction Machine