Sukanta Das

Reduced-graphene-oxide-and-strontium-titanate-based double-layered composite: an efficient microwave-absorbing material

Microwave-absorbing materials based on reduced graphene oxide (r-GO)/strontium titanate were prepared by embedding in epoxy matrix. R-GO and strontium titanate were synthesized and characterized before composite fabrication. Microstructures of the constituent elements were studied by scanning electron microscopy and X-ray diffraction (XRD). Microwave absorption capabilities of the composite absorbers were investigated using a Vector Network Analyser in the range 8–12 GHz. A maximum reflection loss of −7.5 and −16.4 dB was obtained at 9.3 and 12.08 GHz, respectively, for 2% (w/w) r-GO-loaded epoxy composites. A maximum attenuation of −12.8 dB at 9.3 GHz was obtained for the strontium titanate/epoxy composite. However, double-layer composite with r-GO/strontium titanate/epoxy composition showed the maximum reflection loss of −15.1 dB at 9.47 GHz and −9.65 dB at 12.3 GHz. All the results are discussed in terms of complex permeability and permittivity. The study revealed that intrinsic conductivity and polarization of the r-GO particles and dielectric polarization of the strontium titanate within epoxy matrix contribute to the microwave absorption.

Current Sensor Fault-Tolerant Control for Direct Torque Control of Induction Motor Drive Using Flux-Linkage Observer

This paper proposes a novel fault-tolerant control (FTC) scheme for direct torque control of induction motor (IM) drives against the line current sensor failures. Three major steps involved in the proposed FTC scheme are the detection of sensor fault, isolation of the same, and finally, the reconfiguration by proper estimation. Third-difference operator employed in the motor line current is found suitable for the detection of the sensor fault, while flux-linkage observer-based current estimation scheme performs the task of estimation of line current post the occurrence of the fault. Furthermore, a decision-making logic circuitry isolates the faulty signal and simultaneously selects the appropriate estimated current signal to make the drive fault-tolerant. The proposed current sensor FTC scheme is simple and unique in nature. Moreover, it can be universally applied with any speed control schemes involving IM drive. The proposed scheme is simulated and extensively tested in MATLAB/Simulink. The obtained simulation results are also verified using a dSPACE-1104-based IM drive laboratory prototype to show the effectiveness of the scheme.

Empirical relation for broken bar determination in SCIM

Purpose Condition monitoring of squirrel cage induction motors (SCIMs) is indispensible for achieving fault-free working environment. As broken rotor bars (BRBs) are one of the more frequent faults in a SCIM especially where direct-on-line starting is indispensible, as in underground mines, a priori knowledge of fault severity in terms of the number of BRBs assists in effective fault monitoring. In this regard, this paper aims to propose a unique empirical relation to facilitate the determination of number of BRB. Design/methodology/approach Fast Fourier transform is used to obtain fault sideband amplitudes under varying number of BRBs and load torque for 5.5 kW, 7.5 kW, 10 kW, three-phase, 415 V, 50 Hz SCIMs in MATLAB/Simulink. The nature of variation is decided by an appropriate curve fitting technique for comprehending a unique empirical relation. The proposed empirical relation is validated by bootstrapping and z-test. Furthermore, hardware validation is done using 1 kW laboratory prototype with Labview interface. Findings The analytical study reveals the dependence of lower and upper sideband amplitudes on the number of BRBs, load torque and machine rating. Therefore, fault severity in terms of number of BRBs is accurately calculated using the proposed empirical relation if load torque, machine rating and amplitudes of lower and upper sidebands are known. Originality/value The unique empirical relation proposed in the present work provides accurate knowledge of fault severity in terms of the number of BRBs. This facilitates maintenance scheduling which shall reduce effective downtime and improve production.

An Improved Rotor Flux Space Vector Based MRAS for Field-Oriented Control of Induction Motor Drives

The paper proposes an improved low speed performance of classical rotor flux (RF)-based model reference adaptive system (MRAS) for field oriented controlled induction motor (IM) drives. The improved performance of the RF-MRAS estimator is obtained by using voltage reference vector to compute the rotor flux vector in the reference model instead of actual voltage signal vector in the process of speed estimation. The voltage reference vector is estimated by using proportional integral controller over the error signal vectors obtained from the difference between the reference and the measured current vectors. This modification allows satisfactory low or zero speed estimation of IM drive using RF-MRAS-based estimator. The proposed drives performance is compared with classical RF-MRAS and its performance for the low-speed operation is also authenticated with

Adaptive quadratic interpolation for loss minimization of direct torque controlled induction motor driven electric vehicle

{\vec{V}^ * } \times \vec{I}

Sensorless control of grid-connected doubly-fed induction machine drive using model reference adaptive controller

based MRAS in MATLAB/ Simulink. Stability and sensitivity studies are further carried out to ensure the robustness of the drive system. Experimental results as obtained by a dSPACE-1104 based IM laboratory prototype are also presented to validate the simulation study.

Sensorless speed estimation and control of brushless doubly-fed reluctance machine drive using model reference adaptive system

This paper proposes a search control based loss minimization approach for direct torque control (DTC) of induction motor (IM) drive suitable for electric vehicle application. The proposed scheme directly regulates the stator flux level using an optimal stator flux reference generated by adaptive quadratic interpolation (AQI) to meet the desired torque demand. The search controller is implemented in the outer loop of the control scheme to decide an optimum flux level for the drives operation. Consequently, the core loss of IM reduces significantly, thereby improving the efficiency of the drive system. The proposed algorithm is simple in computation and does not involve any additional hardware circuitry for its practical realization. Furthermore, it provides faster convergence without compromising the dynamic response of the speed control loop. All the relevant studies, in this context, are carried out in MATLAB/Simulink. Finally, the scheme is validated experimentally in a dSPACE-1103 based IM drive laboratory prototype.

Wavelet Transform Based Ball Bearing Fault Detection Scheme for Heavy Duty Mining Electrical Motors under Supply Frequency Regulation using MCSA

This paper proposes a new sensorless method for the vector control of grid-connected doubly-fed induction machine (DFIM) drive. The proposed sensorless method is based on the model reference adaptive controller (MRAC) which utilize instantaneous and steady state values respectively of a fictitious quantity obtained as the difference between two fictitious ratios of rotor voltage to current along the d-and q-axes for the reference and the adaptive models. The dimension of this fictitious quantity is ohm (Ω) and has no physical significance. The proposed method does not require any estimation of flux and is also independent of stator and rotor resistance variations. The proposed sensorless method also shows stable performance in the regenerating mode of operation of DFIM. All the detailed simulation study is done in MATLAB/Simulink and experimentally validated through adSPACE-1104-based DFIM laboratory prototype.

Wavelet Transform Based Filter to Remove the Notches from Signal Under Harmonic Polluted Environment

The contributions of this paper are towards the successful implementation of secondary flux based model reference adaptive system (SF-MRAS) for the speed estimation and primary field oriented control of brushless doubly-fed reluctance machine (BDFRM) in motoring and generating modes of operation. The speed estimation arrangement uses two pairs of independent secondary flux equations in reference and adaptive models. Comprehensive simulation study, hardware validations and stability analysis using Bode plots confirm the satisfactory performance of the proposed estimation algorithm.