Position sensorless technology of switched reluctance motor drives including mutual inductance

Kuai, Songyan; Zhao, Shuai; Heng, Feng-ping; Cui, Xin

doi:10.1049/iet-epa.2016.0490

Cited by 35 publications

(8 citation statements)

References 19 publications

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“…where, A is the flux of phase A. Therefore, the current of phase A can be calculated by equation 1to (5), which can be expressed as equation (6). It should be noted that the phase current of phase B is similar with phase A.…”

Section: Mathematical Modelmentioning

confidence: 99%

Modeling, Simulation and Experimental Verification of Four-Phase 8/6 Switched Reluctance Motor Considering Interactive Excitation

Zhu

Jia

2020

IEEE Access

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In the single-phase excitation mode of a four-phase 8/6 switched reluctance motor (SRM), the switch angle for each phase is usually high enough to improve the performance of the SRM, which can directly result in overlapping in excitation periods of each adjacent phase. Ignoring the torque variation caused by magnetic coupling between adjacent charged phases during excitation overlap period, which is a general method to establish the model of SRM currently, would greatly influence the accuracy of the simulation model. Aiming at the problem of the general modeling method, a new SRM ontology modeling method is proposed by considering overlapping excitation, based on nonlinear mathematical model established by means of mutual inductance which could influence the electromagnetic characteristics of SRM. Firstly, the reason of interactive excitation and the distribution of the magnetic field are analyzed by (FEM), and the mathematical model is also developed. Then, the detailed static characteristics including mutual inductance and torque are analyzed based on the results of FEM, which are compared with those of the model without considering the effects of interactive excitation. Furthermore, the dynamic simulation model of SRM drive system (SRD) is built, and the simulation results are analyzed and compared with those of the traditional model. Finally, a static experiment is designed and performed to verify the mutual inductance and static torque under long magnetic circuit (LMC) and short magnetic circuit (SMC) in interactive excitation. The comparison results show that the data from experiment are greatly consistent with those from FEM, and the characteristics of mutual inductance and torque under interactive excitation should be considered when establishing the model of SRM. INDEX TERMS Switched reluctance motor, modeling method, interactive excitation, electromagnetic characteristics.

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Section: Mathematical Modelmentioning

confidence: 99%

Modeling, Simulation and Experimental Verification of Four-Phase 8/6 Switched Reluctance Motor Considering Interactive Excitation

Zhu

Jia

2020

IEEE Access

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“…On the analysis of the variation of the flux linkages among the phases, the sensorless control algorithm can be accomplished [45]. Recently, the utilisation of the mutual inductance between the two excited phases has been realised for position sensorless control [46].…”

Section: Switched Rmmentioning

confidence: 99%

Overview of magnetless brushless machines

Lee

Chau

Liu

et al. 2017

IET Electric Power Applications

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Owing to the definite merits of high-efficiency and high-power density, the permanent-magnet (PM) brushless machines have been dominating the high-performance industrial applications. However, the problems of high PM material cost, fluctuating supply of rare-Earth materials and ineffective PM flux control have hindered the widespread applications of the PM brushless machines. In recent years, many attentions have been shifted to the magnetless candidates, while the focuses are mainly placed on the classical candidates. In this study, an overview of magnetless brushless machines including both the classical and advanced types is presented, with emphasis on their machine topologies, features and performances. In addition, the upcoming trend of these machines is reviewed and discussed.

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“…Fuzzy logic is a useful technique for modelling and control of non-linear systems [15,16]. Some control strategies are based on position sensors while some others are based on sensor-less methods [17]. Using a type-1 Takagi-Sugeno (T-S) fuzzy system, a non-linear system can be modelled as a set of linear systems with corresponding membership functions [18,19].…”

Section: Introductionmentioning

confidence: 99%

New adaptive fuzzy sliding mode scheme for speed control of linear switched reluctance motor

Azadru

Masoudi

Ghanizadeh

et al. 2019

IET Electric Power Applications

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This study presents a new control system for a linear switched reluctance motor (LSRM). Type-2 Takati-Sugeno fuzzy system is used for the motor approximation. The uncertain parameters of the motor are described by the lower and upper membership functions. By constructing an integral sliding mode surface, an adaptive sliding mode controller is designed and dynamic stability of the sliding motion is verified using the Lyapunov function. The design of the proposed sliding mode surface is independent of the number of fuzzy rules and thus, computational complexity is significantly decreased. The control system is implemented on a double-sided four-phase LSRM and its performance is demonstrated by means of modelling and experimental results.

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Position sensorless technology of switched reluctance motor drives including mutual inductance

Cited by 35 publications

References 19 publications

Modeling, Simulation and Experimental Verification of Four-Phase 8/6 Switched Reluctance Motor Considering Interactive Excitation

Modeling, Simulation and Experimental Verification of Four-Phase 8/6 Switched Reluctance Motor Considering Interactive Excitation

Overview of magnetless brushless machines

New adaptive fuzzy sliding mode scheme for speed control of linear switched reluctance motor

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