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This paper introduces a general mathematical model for the flux
density waveform in each segment of the switched-reluctance machine
(SRM). The model explicitly considers operational features such as
conduction angle control. Integration with an electromechanical
simulation would support flux density models under current-regulated
operation. The pap...
Contexts in source publication
Context 1
... a superpo- sition of flux pulses from the phases spaced by the supply switching frequency time period . These pat- terns depend on the physical location of each segment relative is the stator core waveform period ( ). The sign matrix indicates whether a flux pulse adds to, or subtracts from, the total flux seen by a segment of the stator core. Fig. 2 shows a five-phase 10/6 SRM with the stator poles and stator core segments numbered in sequential order. Flux conservation requires the flux in segments 1 and 1 to be equal in magnitude and opposite in sign; the same holds for the other similarly identified ...
Context 3
... When the rotor rotates one rotor pole pitch, the rotor core segments see flux patterns that depend on the phase switching order as shown in Fig. 2. Matrix is used to represent the flux patterns in each rotor core segment. Matrix has the following ...
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Citations
... Table I enlists the operation of motor phases in the appropriate sequence. One may observe (see in Fig. 1) that the stator yoke and the rotor core (hereafter called back iron) have an uneven flux/ flux density distribution due to (algebraic) addition (section lying between S 2 and S 1 ) and subtraction (section lying between S 1 and S 2 ) of the phase fluxes [25], [26]. This uneven distribution has an extremely significant effect on the dynamics of phase current. ...
The paper proposes a new “switched lumped reluctance network” based equivalent circuit for a switched reluctance motor under saturation. The proposed circuit incorporates the effects of the position-dependent switching of the phase windings and changing position of the rotor with respect to the stator. This feature enables the analysis of non-uniform and dynamic variation of flux in motor iron sections along with that in the air-gap and their effects on the phase current. The proposed model thus emulates the operation of a switched reluctance motor, more truly, through an equivalent circuit approach. The accuracy of the proposed model is verified by comparing the analytical results of five different stator-rotor sets (having different air-gap and tooth angular width) with the FEM simulated results and found to be in excellent mutual agreement. The static and dynamic performance obtained using the proposed model has been validated by experiments on a 4 phase, 1 kW, 300 V, 1000 RPM switched reluctance motor.
... Although the approximation is reasonable, there is some difference between the two profiles. The linear inductance profile in profile can be approximated as linear piecewise functions [48], [49]. Different piecewise functions can be developed at different rotor position ranges. ...
Switched Reluctance Machines (SRMs) are gaining more attention due to their simple and rugged construction, low manufacturing cost, and high-speed operation capability. An electromagnetic model of the machine is needed in the design and analysis processes. The required accuracy level of the model depends mainly on the application. A high-fidelity model is required to achieve a good design and predict the performance accurately. However, it requires high computational cost and longer simulation time. Other fast and less-comprehensive models with less computational burden could be utilized in the design and analysis of the motor drives. This paper extensively analyzes various electromagnetic modeling techniques of SRMs. Analytical, numerical, and hybrid models are considered. The paper investigates analytical models that are based on Maxwell's equations in addition to interpolation and curve fitting techniques. Numerical techniques such as Finite Element Method (FEM) and Boundary Element Method (BEM) are presented. Moreover, Magnetic Equivalent Circuit (MEC) method is discussed. Finally, potential research areas are proposed for the electromagnetic modeling of SRMs.
... During the transient analysis of SRG carried out in the developed simulation model, the stator pole flux waveform is also predicted. In addition, the flux waveforms in different parts of the machine including stator core, rotor pole and rotor core can be derived from the predicted stator pole flux waveform using the systematical algorithm introduced in [15]. Implementing this algorithm in APDL, the flux waveforms in different parts of the SRG are determined in the developed simulation model and then core loss in each part is estimated based on the following improved Steinmetz equation [8]: ...
Using ANSYS finite element package, an electromagnetic simulation model is developed for switched reluctance generator (SRG) in which dynamic characteristics are predicted precisely with finite element method (FEM). Carrying out 2D finite element (FE) transient analysis, instantaneous phase current and stator pole flux waveform are predicted when magnetic saturation is considered in the analysis. Based on a systematical algorithm, flux waveforms within the machine are derived analytically from predicted stator pole flux waveform and then core loss is estimated. The model is applied to an 8/6 SRG and simulation results are presented. Since the simulation model is developed as a parametric model in ANSYS parametric design language (APDL), it is possible to evaluate the effect of design data and the control parameters on SRG performance. Applying the developed simulation model to other types of conventional switched reluctance generators which are 6/4 SRG and 12/8 SRG, simulation results are presented and compared to those given for 8/6 SRG.
... For the single-phase excitation, these flux waveforms can be determined from the stator pole flux waveform that is derived from the transient analysis described the above. To do this, the mathematical flux model introduced in [22] is considered here and its algorithm is implemented in APDL. When the flux waveforms in different parts of the SRG are determined, the instantaneous flux density waveform in each part is then derived from dividing the amplitude of the determined flux waveform by the respective area. ...
In the present paper, a parametric electromagnetic model is developed for the switched reluctance generator (SRG) with the finite element method (FEM) using the ANSYS finite element (FE) package which can be considered appropriately for accurate analysis and optimal design of the SRG. The performance principles of the SRG are briefly explained and some important electromagnetic characteristics of the SRG including phase current and instantaneous input power are predicted using the developed electromagnetic model. Carrying out the transient analysis, there is this possibility to predict the flux waveforms within the machine and therefore a core loss model is then introduced for the SRG. Applying the developed electromagnetic model to an 8/6 SRG, simulation results are presented and some critical issues are identified which can be attended in design of the control system of the SRGs.
... For single-phase excitation of SRM, it is possible to determine the flux waveforms in different parts of motor from the stator pole flux waveform as follows in most core loss models [1– 6]. A systematic algorithm for this purpose has also been introduced in [7]. The stator pole flux waveform can be obtained through different methods: assuming a triangular waveform [2] [3], measurement [4], analytical models [5] and finite-element method (FEM) [6]. ...
... In [6], we introduced a core loss model for SRM in which the stator pole flux waveform was predicted by two-dimensional (2D) FEM. Then, the flux waveforms in other parts of the motor were obtained from this predicted flux waveform using the algorithm proposed in [7]. The flux waveforms in different parts of SRM can be also predicted by FEM [8]. ...
This paper describes a fully analytical approach for iron losses estimation. This method allows us to quantify hysteresis and Eddy current losses in each part of a Switched Reluctance Motor (SRM), the validation of this method is obtained by comparing analytical and experimental phase inductance, the other validation method is based on comparison of static flux densities between this method and finite element method. Analytical air gap permeance model is used in association with analytical expression of magneto motive force (MMF) and current. It allows calculating the flux linked in each part of the SRM. The temporal and frequency characteristics of these fluxes, using static material iron losses under sinusoidal flux density excitation, FFT and correction factors leads to estimate iron losses and their location in the machine. The results show that the major part of the losses are located in the stator especially in the teeths, Hysteresis losses are higher than Eddy current losses in the SRM. As soon as the speed of the SRM increases the Eddy current losses become more important. 8/6 2 kW SRM is used in experimental test bench, Infrared camera placed in front of the lateral face removed just after operation give the thermal signature of these losses and confirm the previous results. Copper losses are located in the winding.
This paper describes an analytical based method for iron losses estimation in switched reluctance motor (SRM), It is based on analytical flux calculation using airgap permeance. This method is compared to finite element method in term of phase inductance and static pole flux linkage calculation. FFT analysis is applied to each part of SRM flux waveforms to extract the amplitude of the flux density harmonics. Iron losses are estimated in each part of the SRM, the major part of the losses are located in the stator, Hysteresis losses are higher than Eddy current losses in the SRM. Infrared camera is used to locate experimentally the thermal signature of all losses.
A fast method to calculate the iron loss of switched reluctance motor (SRM) is proposed. The key of the method is that the flux density waveforms in different parts of the motor can be obtained quickly. First, the static flux density data varying with phase current and rotor position in various parts of SRM are obtained by finite element method (FEM). Then, the static flux density data are stored in 2D look-up tables in Matlab/Simulink to get the flux density waveforms by look-up table method, and the obtained flux density waveforms are verified by FEM results. Since the flux waveforms are nonsinusoidal and non-linear, an accurate and fast model for the iron loss prediction is presented, and different modified factors are applied to calculate the hysteresis loss according to the classification of flux density waveforms. Based on that, the calculation model is established in Matlab/Simulink, and iron losses of a three-phase 6/4 structure SRM under different turn-on and turn-off angles and load conditions are calculated and analysed. Finally, measured results are presented to verify the precision of the calculation model.
Zero-volt loop (ZVL) is known to be able to reduce peak flux linkages corresponding to iron losses while keeping the same average torque in average torque control of switched reluctance motors (SRMs). However, exploiting ZVL to minimize losses of SRMs has been challenging due to nonlinear correlations caused by extensive magnetic saturation. In this paper, an optimization method to minimize losses while utilizing ZVL is proposed. The Impact of ZVL was investigated by theoretical calculation using a 12 kW, 3820 rpm SRM. The results showed that the utilization of ZVL reduced losses at all speed and partial load. The loss reduction was large especially at medium speed and partial load. At this operating point, the loss reduction was verified by experiment.
