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.
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.
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.
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.
In this paper, based on the comparisons of the stator pole flux density and phase current with corresponding rotary switched reluctance machine, the original design scheme of a 1-kW single-side ...switched reluctance linear launcher (SRLL) is obtained by a traditional method. To get higher efficiency and smaller force ripple, the genetic algorithm, which is improved to enhance the convergence rate and global accuracy, is applied to optimize the original design scheme. The global optimum values of key dimensions and control parameters are obtained, and the detailed structure of whole SRLL is given as well. Then a detailed equivalent lumped-parameter thermal network (LPTN) model of the considered SRLL is built, and temperature rises of some parts are obtained. To test the feasibility of the LPTN model, a 2-D finite element thermal model of the SRLL is built, and the temperature rises are obtained. The results from LPTN model match those from the finite-element method very well. Finally, the preliminary tests of the prototype of designed SRLL are carried out and the experimental results are presented.
To effectively find a valid solution in the development process of electrical machines, it is essential to predict machine iron loss in the pre-design stage. In guidance on the choice of the most ...suitable configuration of the switched reluctance machine (SRM) is given, but iron loss prediction is neglected. Based on the study of Burkhart et al., this study proposes a simplified model to efficiently calculate iron loss in the design procedure of SRMs. For this purpose, a maximum co-energy loop control method is implemented to facilitate the estimation of flux waveform and machine torque. Three different iron loss calculation methods are compared in terms of accuracy and time. The accuracy of the simplified model is verified by comparison with finite element simulation results. Furthermore, the impact of different parameters on the iron loss is discussed, and the iron loss of various machine geometries is comparatively analysed.
According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network ...(WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.
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