Realization of fault tolerant capability in a multiphase SRM drive using wavelet transform
Introduction
In the recent past, the research in the Switched Reluctance Motor (SRM) plays a key measure to find an alternative to the Induction Motor (IM) drive in the industrial applications as well as in the variable speed drive market. The SRM has numerous advantages over the IM and Permanent Magnet Brush Less DC (PMBLDC) motor due to its minimal maintenance, wide speed range, and operates in high temperature environment [1]. The adjustable speed of single phase IM drive with reduced number of switches requires frequent maintenance and faces power quality issues is explained in [2]. The scholars has chosen SRM with integration of charging capacity for hybrid electric vehicle to reducing CO2 emission in the atmosphere [3], and numerical analysis experiment in the invention of new double layer SRM drive system [4].
The drawbacks of SRM drive in the hybrid electric vehicles are noise and vibration produced by the motor. The prediction of noise and control measures and vibration control of switched reluctance motor are discussed in [5,6]. The torque ripple production, acoustic noise and vibration of motor during operation are prime causes to discard of the SR motor in the industrial areas. The torque ripple production makes fast switching in the excitation of phase windings and forced commutation thus fault occurs in the motor.
To mitigate, the torque ripple content at the output, the new methods are proposed in the paper [6], [7], [8]. The power converters play a vital role in the SRM operation, the new topologies are proposed to nullify the drawbacks in [9], [10], [11]. The conventional controller and vector control techniques are used to control SRM in [12,13]. The advanced controller designs and techniques such as Fuzzy Logic Controller (FLC), open loop control, Artificial Neural Network (ANN) controllersare introduced to control the motor drive in [14]. The electromagnetic energy efficient conversion of SRM motor is presented in [15].
The fault existence possibilities in SRM drives are more than the other drives. Because the SR drives operation consists of high number of stages from input supply to the output. The fault detection methods using K-means clustering algorithm that are explained in [16]. A new method to diagnosis the power converter faults and flexible fault tolerance topologies are proposed to diagnosis the fault occurrence in the system are discussed in [17,18] respectively. The other fault investigation methods using rotor structure [19], inter turn faults diagnosis using Space Vector Modulation (SVM) technique [20], fault tolerance analysis of SRM with distributed inverter [21] are presented. In this work, Wavelet Transforms (WT) based, fault analysis method is implemented to find the various faults in the SRM drive. The various faults in the SRM drive are illustrated, in the Fig. 1. The proposed converter with WT based fault identification method is realized using MATLAB simulink tool and the same is validated through experimental results.
Section snippets
SRM drive specification and classification of fault
In this work, 5-phase(10/8 pole) SRM is considered where, the input dc supply (Vdc) to SRM drive is obtained from the 230 VAC supply and with the uncontrolled diode bridge rectifier unit. The speed of a motor can be varied from 0 to 5500 rpm. The power converter circuits consist of two semiconductor switches and two power diodes, at each phase model. For 5-phase motor, 10-IGBT switch along with 10- diodes are used as shown, in the Fig. 2.
The Pulse Width Modulated (PWM) signals are generated by
Wavelet transform for faults identification
Wavelet transform (WT) is widely used in signal processing for the prediction of changing events. Wavelet transforms results in the representation of original signal with respect to time and frequency as well. This feature can be utilized for identifying the faults in a system/circuit by comparing the changes with steady state response [22]. The faults in the electronic circuit system associated with the sensors, detects the change at circuit parameter. The fault from the circuit or system
Results and discussion
The modeling of 5-Phase SRM motor and its power converter circuit is done using MATLAB simulink tool. The various faults like freewheeling diode failure, phase-phase short circuit, DC link filter capacitor failure, and IGBT switch failure are scrutinized to validate the WT based fault identification system. The SRM performance parameters like phase current, electromagnetic torque and speed characteristics are meticulously analyzed and presented for both the simulation and the hardware model.
Conclusion
The fault and high temperature tolerance are the major concern to choose a drive for the industrial purpose. The proposed technique can early detect fault occurrences and to identify not only the affected motor phase but also the faulty element. In the phase current analysis, under fault condition is relatively equal to 12.84A. From the analysis of results, phase to phase short fault leads to more deviation in iph current. Other faults are acceptable to run the SRM without much loss. In the
Declaration of Competing Interest
This paper has not communicated anywhere till this moment, now only it is communicated to your esteemed journal for the publication with the knowledge of all co-authors.
Ethical approval
This article does not contain any studies with human participants or animals performed by any of the authors.
L. Senthil Murugan received the B.E degree in Electrical and Electronics Engineering from Park College of Engineering and Technology, Coimbatore, India, in 2006, and the M.E degree in Embedded System Technologies from Anna University, Coimbatore, India, in 2009. He is pursuing his PhD degree at Anna University Chennai, India. He is currently working as an Assistant Professor with Department of Electrical and Electronics Engineering. He is pursuing his PhD degree at Anna University Chennai,
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L. Senthil Murugan received the B.E degree in Electrical and Electronics Engineering from Park College of Engineering and Technology, Coimbatore, India, in 2006, and the M.E degree in Embedded System Technologies from Anna University, Coimbatore, India, in 2009. He is pursuing his PhD degree at Anna University Chennai, India. He is currently working as an Assistant Professor with Department of Electrical and Electronics Engineering. He is pursuing his PhD degree at Anna University Chennai, India. His current interest include Embedded Systems, Electric Drives and Control.
Dr. P. Maruthupandi received the B.E degree in Electrical and Electronics Engineering from Government College of Engineering, Tirunelveli, India, in 1995, and the M.E degree from College of Engineering, Guindy, Chennai, India, in 2002, and Ph.D. degree from Faculty of Engineering, Anna University Chennai. He has twenty four years of experience in teaching and research. He is currently working as an Assistant Professor with Department of Electrical Engineering, Government College of Technology, Coimbatore, India. He has published more than forty papers in national and international journals. He has attended more than thirty national and international conferences. He is a reviewer of many International reputed journals. He is an active member of many professional societies. His current interest include Power Electronics, Power Quality, Renewable Energy, Embedded system, Electric Drives and Control.