In this letter, a transformed unsaturated inductance characteristic-based method is proposed for the rotor position of the switched reluctance machine. Due to the magnetic saturation effect, the ...phase inductance characteristics have a narrow linear region, which increases the difficulty of their analytical expression. To reduce the complexity of the analytical expression, the unsaturated inductance characteristic is transformed from the phase inductance characteristics. Then, a linear model is presented to explicitly describe the relationship between the rotor position and unsaturated phase inductance. Experimental verification is carried out to verify the effectiveness and accuracy of the proposed method. The proposed method can serve as a low-effort way to provide the accurate rotor position for the industry application at medium and high-speed ranges.
This paper proposes a new fast method to determine the entire flux-linkage characteristics of a switched reluctance machine (SRM), which are critical for performance estimation and advanced control ...of the machine. The proposed method mainly consists of two steps, namely, measuring and calculating. In the measuring step, the flux-linkage characteristics of the SRM are measured at four specific rotor positions by a new indirect method without rotor clamping devices and position sensors. The magnetic coupling among phases is considered to improve the accuracy of measurement. In the calculating step, based on the measured results, the analytical expression of the flux-linkage characteristics is proposed, which only needs a few coefficients. With the expression, the flux-linkage characteristics at any rotor position can be calculated. The entire flux-linkage characteristics of a 1-kW three-phase 12/8-pole SRM obtained by the proposed method and traditional rotor clamping method are compared, and a good agreement can be found, which verifies the feasibility and accuracy of the proposed method. Furthermore, with the entire flux-linkage characteristics calculated by the proposed analytical method, the dynamic performances of the SRM prototype under both motoring and generating modes are simulated and compared with those from other methods and experiments, which further verify the accuracy of the proposed method.
In this paper, the control performances of a modular power converter for a three-phase switched reluctance machine (SRM) are analyzed and improved. The converter is implemented by a dual and a ...six-pack IGBT module, and the phase windings of the SRM are Y-connected and bipolar excited. The performances of the existing control method for this converter are evaluated by simulation and compared with those for the traditional asymmetric half-bridge converter, and the drawbacks, such as big torque ripple and small average torque, are presented. With the new operating modes of phase branch, namely magnetization, freewheeling, and demagnetization, improved basic control methods are proposed, which can effectively enhance the performances, flexibility, and applicability of the converter. Furthermore, the direct instantaneous torque control, which can reduce the torque ripple, is realized with the converter as well. Several simulations and experiments under different working conditions are carried out to verify the performances of the improved control methods.
This paper proposes a novel accurate position estimation method for switched reluctance machine (SRM). The method requires only the flux-linkage characteristics at two particular rotor positions, ...which can be conveniently measured by the torque-balanced method. The interval which takes these two positions as endpoints is selected as the optimal interval due to the good linearity between the flux linkage and position and the low sensitivity to the errors of the flux linkage. The positions in the optimal interval are obtained by the linear flux-linkage model, and the positions that do not lie in this interval are estimated by the monadic linear regression analysis (MLRA). Furthermore, the rotational speed is also estimated based on MLRA. The accuracy of the proposed method is verified by detailed simulation and experiment under different operating conditions such as angle position control and current chopping control.
Pulsating high-frequency voltage injection can be used for the sensorless control of a surface-mounted permanent magnet synchronous motor (SPMSM) at zero- and low-speed ranges. However, the ...sensorless capability still faces challenges to the requirements of industrial application, especially at heavy load status. Aiming at this issue, this article proposes a sensorless capability expansion method for an SPMSM based on inductance parameter identification. Firstly, incremental inductances at the d-q-axis and cross-coupling inductance are identified offline by three steps combining the rotating high-frequency voltage injection and pulsating high-frequency voltage injection. Using a polynomial curve fitting algorithm, apparent inductances are calculated. Secondly, positive DC current injection at the d-axis is proposed to enhance the saliency ratio based on the analysis of parameter identification results. Compared with the conventional id = 0 or id < 0 method, the saliency ratio is enhanced obviously when a positive DC current is injected at the d-axis. Then, the convergence region of the sensorless control method at heavy load status is expanded and the accuracy of rotor position estimation is improved using the proposed method. Finally, the experimental results validate that the sensorless capability of the SPMSM is expanded.
This paper proposes a combined modeling method for switched reluctance machine (SRM) with few samples of flux linkage characteristics measured without rotor clamping devices and position sensors. The ...proposed method mainly consists of two steps, namely data reconstruction and characteristic description. In data reconstruction, the entire flux linkage characteristics are obtained by training support vector machine (SVM) with the measured few samples. The characteristics from the trained SVM are consistent well with those from the rotor-clamping measurement. In characteristic description, back-propagation neural network (BPNN) is adopted to describe the reconstructed flux linkage characteristics and calculated static torque characteristics. On this basis, the simulation model of the SRM prototype is built in MATLAB. The results from simulation under both motoring and generating mode are compared with those from experiments, and good agreements can be found, which prove the effectiveness of the proposed modeling method. To further demonstrate the accuracy and application of the entire flux linkage characteristics obtained from data reconstruction, BPNN is used again to build the mapping from flux linkage and phase current to rotor position for rotor position estimation, and some results are presented. The applicability of the proposed method to different SRM topologies is discussed as well.
In this paper, a novel analytical method is proposed for rotor position estimation of switched reluctance machine (SRM). The nonlinear reluctance characteristic of the SRM is divided into two parts, ...namely air gap and iron core, and analyzed in detail from the aspect of magnetic field. According to the inherent features of the reluctance characteristic, it is analytically expressed based on scaling. Two segments are considered, which are expressed as a linear function and a quadratic function, respectively. Then, the analytical expressions of rotor position are derived for each segment. The effectiveness of the proposed analytical estimation method is evaluated with detailed simulations and experiments under different operating conditions. The proposed method is accurate and just requires the reluctance characteristic at four or even two rotor positions, which can be conveniently measured by the torque-balanced method.
Accurate static electromagnetic characteristics are essential basic data in the modeling of switched reluctance machine (SRM) for performance analysis and advanced control purposes. Because of the ...doubly salient structure and deep magnetic saturation, the electromagnetic characteristics of SRM have highly nonlinear relations with phase current and rotor position, which make the determination of these characteristics a difficult task. This paper proposes a digital signal processor-based method to accurately measure the flux-linkage and static torque characteristics of SRM. First, theoretical derivation and practical realization of the proposed method are presented in detail, and its accuracy is preliminarily verified by three ways: coenergy method, finite element method, and inductance-capacitance-resistance meter. Then, the errors in measurements are analyzed and corresponding methods to reduce them are given. Finally, with the improved neural network, the nonlinear simulation model of a SRM prototype is built in MATLAB with the measured characteristics, and the simulation results have good agreements with those from experiments, which further verify the accuracy of the proposed method.
To achieve high precision and robust control of switched reluctance machines (SRMs), this paper proposes a novel rotor position estimation method based on gain-optimized sliding mode observer (SMO) ...with neural networks and whale optimization algorithm. For the SMO, this paper uses the easily measured phase current to constitute the error function of the SMO, which requires less pre-stored data. Using the neural networks’ powerful nonlinear mapping capability, the relationship between the sliding mode gains and speed estimation error and the position estimation error is obtained, and then the whale optimization algorithm is used to find the optimal sliding mode gains in the restricted range. The simulation and experiment results show that the accuracy of the SMO control system is significantly improved.
This paper proposes a new decoupled analytical modeling method for switched reluctance machine (SRM). The flux linkage is represented by a second-order Fourier series, and the coefficients of the ...series are position dependent, which can be further expressed by another second-order Fourier series. The proposed method only needs 21 data points from five rotor positions. Then, the static torque characteristics are analytically obtained based on the expression of the flux linkage. The accuracy of the method is verified by comparing the calculated flux-linkage and static torque characteristics with those from measurements. With the calculated flux-linkage and static torque data, the dynamic performance of SRM is simulated under both motoring and generating mode. The simulation results, such as phase current and mechanical characteristics, agree well with those from the experiment, which further proves the effectiveness of the proposed method.
