The electromotive force (EMF) observer-based sensorless algorithms are sensitive to temperature rise because it requires the stator resistance (R _s ) or the rotor flux linkage (ψ _r ). The temperature measuring of an operating motor can be difficult, therefore, adaptive sensorless algorithms with online R _s and ψ _r estimation are appreciated. However, existing methods require extra signal injections, transient operations or estimate R _s and ψ _r one at a time to overcome the rank-deficient problem. In this paper, an adaptive EMF observer which is able to estimate both R _s and ψ _r simultaneously without requiring any signal injections or transient operations is proposed. The method exploits the harmonic back EMFs (HBEMF) to serve as a novel reference model and regulates the R _s value in the EMF observer accordingly. The rank deficient problem is solved with the extra information provided by the HBEMFs. To make use of the HBEMFs, a parameter insensitive extraction method and an algorithm to calculate the rotor position from them are proposed. With the proposed reference model, an adaptive scheme to regulate R _s is proposed. To obtain the rotor flux linkage, a ψ _r estimator is also developed. The effectiveness of these proposed methods is verified with experiments and simulations.

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