Flux-Weakening Control of Switched Reluctance Machines in Rotating Reference Frame

Husain, Tausif; Elrayyah, Ali; Sözer, Yilmaz; Husain, Iqbal

doi:10.1109/tia.2015.2469778

Cited by 23 publications

(4 citation statements)

References 27 publications

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“…However, iterative calculation is required in the reference current generation for the saturated SRM. In [127], [128], the authors directly map a synchronous reluctance machine to the SRM, by maintaining equal torque. From the perspective of control variables, the SRM is controlled in a vector torque control like method.…”

Section: ) Vector Controlmentioning

confidence: 99%

Advanced Control of Switched Reluctance Motors (SRMs): A Review on Current Regulation, Torque Control and Vibration Suppression

Fang

Scalcon

Xiao

et al. 2021

IEEE Open J. Ind. Electron. Soc.

113

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With the increasing environmental concerns, a paradigm shift towards electric and hybrid electric vehicles is expected. Switched Reluctance Motors (SRMs) have emerged as a viable competitor to other established electrical machines. SRMs are known for their simple construction, robustness, inherent fault tolerant structure and low production and maintenance costs. Moreover, the machine has gained interest due to the absence of permanent magnets or windings in the rotor structure, which significantly reduces production costs when compared to other electric motors. The SRM, however, present some known drawbacks, such as increased torque ripple and acoustic noise production, as well as a highly nonlinear behavior. Through the use of adequate control strategies, however, the main challenges of the machine can be overcome. Thus, this paper presents a state-of-the-art review of the advanced control of SRMs, encompassing current regulation strategies, torque control strategies and vibration suppression techniques. First, two-categories of current controllers are reviewed: model-independent and model-based. Next, indirect and direct torque control methods are explored. Then, three approaches to vibration suppression are discussed, namely active cancellation, current profiling and direct instantaneous force control. Lastly, a summary of each topic is presented and suggestions of future research topics are listed.

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Section: ) Vector Controlmentioning

confidence: 99%

Advanced Control of Switched Reluctance Motors (SRMs): A Review on Current Regulation, Torque Control and Vibration Suppression

Fang

Scalcon

Xiao

et al. 2021

IEEE Open J. Ind. Electron. Soc.

113

View full text Add to dashboard Cite

show abstract

“…In [24], an adaptive flux‐weakening control method being suitable for the wide speed range of SRM is proposed under the d–q rotating reference coordinate. A flux‐weakening control method for SRM under the rotating reference coordinate is proposed [25], which offers the smooth torque at the low‐speed operation of SRM. Unfortunately, the flux‐weakening control method for SRM increases the complexity of calculation and the difficulty of implementation due to the introduction of the d–q rotating reference coordinate.…”

Section: Introductionmentioning

confidence: 99%

Torque–flux linkage recurrent neural network adaptive inversion control of torque for switched reluctance motor

Dang

Shi

Peng

2020

IET Electric Power Applications

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In order to reduce the torque ripple for switched reluctance motor (SRM), the learning error preprocessing‐based torque–flux linkage recurrent neural network adaptive inversion control (TFRNNAIC) for SRM torque is proposed by the filter preprocessing and the non‐linear mechanism characteristics for SRM. In TFRNNAIC with the advantages of parallel and series–parallel structure, the torque feedback error learning method is employed to update the weights of the torque–flux linkage recurrent neural network. To suppress the ripple effectively in torque error used for the weight learning of the torque–flux linkage recurrent neural network and obtain an accurate TFRNNAIC, namely the torque–flux linkage model for SRM, the low‐pass filter preprocessing for the torque error is used. Moreover, the other low‐pass filter is executed to reduce the ripple in the output for the PD torque control. The superposition of outputs for TFRNNAIC and PD torque control is taken as the reference flux linkage. Compared with other control strategies, such as the classical parallel neural network control, the classical series–parallel neural network control and TFRNNAIC, the simulation results show that the learning error preprocessing‐based TFRNNAIC for SRM torque is capable of effectively reducing the torque ripple for SRM with the good recurrent performance.

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“…Therefore, parameters that affect the performance measures such as turn-on/off angles (commutation), current regulation, DC bus voltage adjustments should be treated properly [5,6]. During the last decades, numerous research has been reported on converter topologies and control methods for improving the performance and operating range, as well as the torque ripple and acoustic noise reduction [2,7,8]. Among many SRM converter structures, asymmetricbridge converter topology is considered as the traditional SRM drive.…”

Section: Introductionmentioning

confidence: 99%

“…Due to the nonlinear magnetic characteristics of the SRM, it is a challenge to conduct an accurate current regulation. Simple average PI control [14], hysteresis control, DQ control [7], [25], sliding mode control [26], back emf predictive control [27] are some of these structures.…”

Section: Introductionmentioning

confidence: 99%

Tork Salınımı Minimizasyonu İçin Modüler Yükseltici-Alçaltıcı Anahtarlamalı Relüktans Makinası Sürücü Sistemi

Tekgün¹

2020

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

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In this paper, a modular three-phase buck-boost switched reluctance machine (SRM) drive system is proposed. In this topology, the three-phase SRM drive is composed of three single-phase modules that are connected in parallel where each single-phase inverter module is formed with a bidirectional buck-boost DC/DC converter and a cascaded H-bridge inverter. The DC/DC converter generates the rectified form of the phase voltage and the H-bridge inverter alternates and controls the polarity of the output voltage. This structure allows one to adjust the phase voltages independently, which provides faster excitation and demagnetization for a wide range of operating conditions. Since the voltage is always regulated dynamically, the need for bulky DC-bus capacitors is eliminated; hence, the size and the cost of the drive system are reduced. To validate the superiority of the proposed system and compare it with the traditional one, a set of simulations are done in MATLAB ® /Simulink ® . Not only the torque ripple is reduced, but also a higher torque per ampere ratio is achieved with the proposed system. Bu makalede modüler yapıda olan üç fazlı bir alçaltıcı yükseltici anahtarlamalı relüktans motoru sürücü (ARM) sistemi önerilmiştir. Bu topolojide üç fazlı ARM sürücü üç adet tek-fazlı modülün paralel bağlanmasıyla oluşturulmuş olup, her tek-fazlı sürücü bir çift yönlü çalışan alçaltıcı-yükseltici DA/DA dönüştürücü ve bunun sonrasına bağlanmış bir H-köprü eviriciden oluşmaktadır. DC/DC dönüştürücü faz geriliminin doğrultulmuş formunu oluşturmakta ve H-köprülü evirici de oluşturulan gerilimin yönünü değiştirerek çıkış geriliminin polaritesini kontrol etmektedir. Bu yapı faz gerilimlerinin birbirinden bağımsız olarak ayarlanmasına önayak olarak, hızlı enerjilenmeyi ve demagnetizasyonu mümkün kılmaktadır. Bunun sonucunda komütasyon performansı iyileştirilmiş ve moment salınımı azaltılmıştır. Gerilim dinamik olarak sürekli regüle edildiğinden büyük DC-bara kondansatörlerine olan ihtiyaç ortadan kalkmış ve böylece sürücü boyutu ve maliyeti azaltılmıştır. Önerilen sistemin üstünlüğünü doğrulamak ve bu sitemi geleneksel sistemle karşılaştırmak üzere MATLAB ® /Simulink ® ortamında bir dizi benzetim çalışması yapılmıştır. Önerilen sistem ile sadece moment salınımı azaltılmamış daha yüksek bir amper başına moment oranı da elde edilmiştir.

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Flux-Weakening Control of Switched Reluctance Machines in Rotating Reference Frame

Cited by 23 publications

References 27 publications

Advanced Control of Switched Reluctance Motors (SRMs): A Review on Current Regulation, Torque Control and Vibration Suppression

Advanced Control of Switched Reluctance Motors (SRMs): A Review on Current Regulation, Torque Control and Vibration Suppression

Torque–flux linkage recurrent neural network adaptive inversion control of torque for switched reluctance motor

Tork Salınımı Minimizasyonu İçin Modüler Yükseltici-Alçaltıcı Anahtarlamalı Relüktans Makinası Sürücü Sistemi

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