Abstract
A new linear regression form is derived for a flux observer and a position observer is designed. In general, the observability of the permanent-magnet synchronous motor is lost at zero speed. In this work, the proposed regressor vector contains current derivative terms in both directions (dq-axis), and it gives the chance for the model-based flux observer to operate at zero speed. When an excitation signal is injected into d and q axes with the proposed flux observer, it helps to satisfy the persistent excitation condition in the low-speed range. Therefore, the sensorless performance of the model-based is improved greatly, even at zero speed. However, it appears with a disturbance term, which depends on the derivative of the d-axis current. Thus, the disturbance does not vanish when an excitation signal is injected. In this work, the disturbance term is also taken care of in constructing an observer. It results in an observer which allows signal injection. Thus, high frequency signal can be injected in the low speed region and turned off when it is unnecessary as the speed increases. This model-based approach utilizes the signal injection directly without recurring to a separate high frequency model. In other words, it provides a seamless transition without switching to the other algorithm. The validity is demonstrated by simulation and experimental results under various load conditions near zero speed.
Highlights
As the cost and reliability of the motor drive system are taken into account, a rotor position sensorless control and algorithms are being widely used in AC motor
The model-based method is applied in medium/high-speed range because it depends on the relative magnitudes of dq-axis electromotive force (EMF)
The dynamic model of a interior permanent-magnet synchronous motor (IPMSM) is more complex than surface-mount PMSM (SPMSM) in the stationary frame
Summary
As the cost and reliability of the motor drive system are taken into account, a rotor position sensorless control and algorithms are being widely used in AC motor. An additional feedback loop was constructed based on an observer of regression form It allowed the high frequency signal injection to increase the signal-to-noise ratio in the low speed range. The previous observer based on the linear regression model did not work properly at zero speed, even with the high frequency signal [29] This is because its regressor vector did not satisfy the PE condition. To enhance the low-speed sensorless performance, a new regression model is derived by a modified regressor vector It is derived from the square of the active flux after applying a high-pass filter. The gradient algorithm is applied to obtain a flux estimation Though it is a model-based observer, it can operate at zero speed with signal injection under loaded conditions.
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