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Magnetic characteristics of a switched reluctance motor (SRM) determine the modeling accuracy, the performance of a position sensorless control, and the torque ripple reduction control. Due to double saliency structure and core saturation, the magnetic characteristics of SRM is dependent on both the rotor position and the winding current amplitude, which makes it difficult to measure the actual incremental inductance or flux linkage. This article presents the magnetic characteristics identification method. A quad current sampling technique is proposed to capture the derivative of the winding current at a specific rotor position and current amplitude. The flux linkage, co-energy, and torque are calculated from the obtained incremental inductance profile. The proposed method can be easily implemented on digital signal processor–based SRM drive without any extra circuit. The LCR meter and torque sensor measurements are provided to validate the proposed incremental inductance measurement method. [ABSTRACT FROM AUTHOR]

Accurate estimation of the rotor position is essential for reliable start-up and sensorless control of switched reluctance motor drives. In this paper, a series of position estimation schemes based on phase inductance vector coordinate transformations are proposed. Using the rotating coordinate transformation and coordinate components normalization, the dc component and higher order harmonics of the normalized three-phase coordinate components can be eliminated effectively. According to the coordinate transformation theory, the rotating speed of the space vector is synchronized with the angular frequency of the three-phase inductance. Thus, through alpha–beta transformation, the synchronous rotating angle of the space vector and the rotor position can be estimated. Since the rotating angle can be arbitrary, it is possible to construct another coordinate system and find one of its normalized coordinate components that is perpendicular to the one in the former coordinate system. Based on the orthogonal coordinate transformation, the rotor position can also be estimated. Experiments have been implemented for verification. The proposed methods effectively solve the challenges in initial rotor position estimation and are also suitable for reliable sensorless starting under light-load conditions. However, these methods are not suitable for high-load driving–running conditions. To solve this problem, a combination of the phase current slope difference comparison-based method and the coordinate transformation-based method is developed in this paper. The experimental results verified the validity of this method. In addition, the proposed methods do not require additional hardware and complex computation, which simplifies the implementation. [ABSTRACT FROM PUBLISHER]