Usman Ali

The Switched Reluctance Motor (SRM) is recognized for its lightweight construction, high torque-to-inertia ratio, and rotor design without windings, making it well-suited for Electric Vehicles (EVs). However, its widespread use is hindered by the intricate motor drive circuitry, which utilizes an asymmetric-half-bridge (AHB) configuration, struggling with speed/voltage regulation, and generating torque ripples. This paper introduces a modified asymmetric-half-bridge drive (MAHD) circuit for the SRM, designed to reduce the number of components, lower costs, and decrease power loss. To mitigate torque ripples, a sensorless variable-frequency drive (VFD) is incorporated into the proposed circuit. The techniques of sine pulse width modulation (SPWM) and third harmonic injection PWM (THI-PWM) were implemented in a MATLAB-Simulink environment and tested on an SRM hardware driver setup using TMS320F28027. The results show that THI-PWM provides a rapid transient response and high starting torque. This work presents an efficient and compact sensorless drive circuit with a control technique optimized for high-power SRM applications.

High harmonic distortion, increased and uncertain torque ripples factor, and speed ripples have been the reason for reduced efficiency of three-phase induction motor drives. This article proposes an Extended Sine-Wave Pulse Width Modulation (ESPWM) based inverter with lesser THD, low speed ripples, and reduced torque ripple factor. Hence, high operational efficiency of three phase induction motor drive is achieved. Results of the proposed approach are validated and analyzed using MATLAB/Simulink. Additionally, the efficacy of the proposed ESPWM is justified by comparing it with Space Vector Pulse Width Modulation (SVPWM) and Sinusoidal Pulse Width Modulation (SPWM). Proposed ESPWM outperforms both SVPWM and SPWM.

A power conversion system needs high efficiency for modern-day applications. A DC–DC isolated bidirectional dual active bridge-based converter promises high efficiency and reliability. There are several converter topologies available in the market claiming to be the best of their type, so it is essential to choose from them based on the best possible result for operation in a variety of applications. As a result, this article examines the characteristics, functionality, and benefits of dual active bridge-based DC–DC converter topologies and the other members of the family, as well as their limits and future advances. A high-frequency transformer is also an important device that is popular due to high leakage inductance in dual active bridge (DAB) converters. Therefore, a detailed review is presented, and after critical analysis, minimized leakage inductance in the toroidal transformer is obtained using the ANSYS Maxwell platform. Furthermore, this work includes a comprehensive examination of the control approaches for DAB converters, which is important for selecting the most appropriate technique for a certain application. The outcome of ANSYS Maxwell is integrated with a DAB-based boost inverter in the MATLAB/Simulink environment, and the results are validated with the help of an experimental prototype.

In the above article [1] , two relevant references [2] , [3] were missing. The last sentence of Section I-C. should read “Proposed technique deals with frequency weighted and limited Gramians based MOR approach for the discrete-time systems. The frequency weighted version of proposed work appears in [2] while frequency limited work appears in [3] for continuous time systems. Compared to [2] , [3] , mathematical model and simulations in [1] are done for frequency weighted and limited scenarios for discrete time systems.”

The state-space representations grant a convenient, compact, and elegant way to examine the physical systems, e.g., induction and synchronous generator-based wind turbines, with facts readily available for stability, controllability, and observability analysis. In this article, the model order reduction of a stable doubly fed induction generator based variable-speed wind turbines model is performed with the aid of the proposed stability preserving balanced realization algorithm based on discrete frequency weights and limited frequency-interval. The frequency weighting and limited frequency-intervals-based model order reduction techniques presented by Enns’s and Wang & Zilouchian produce an unstable reduced-order model at certain frequency weights and frequency intervals, respectively. To overcome this main drawback, many researchers provided a solution to preserve the stability of the reduced-order model. However, these existing approaches also produce an unstable reduced-order model in some conditions and produce a large variation to the original system; consequently, they provide a large approximation error. The proposed approach not only ensures the stability of the reduced-order model but also provides low approximation error as compared with other existing approaches and also provides an easily calculable a priori error bound formula. The proposed work produces steady and precise outcomes in contrast to conventional reduction methods, which shows the efficacy of the proposed algorithm.

The state-space representations grant a convenient, compact, and elegant way to examine the induction and synchronous generator-based wind turbines, with facts readily available for stability, controllability, and observability analysis. The state-space models are used to look into the functionality of different wind turbine technologies to fulfill grid code requirements. This paper deals with the model order reduction of the Variable-Speed Wind Turbines model with the aid of improved stability preserving a balanced realization algorithm based on frequency weighting. The algorithm, which is in view of balanced realization based on frequency weighting, can be utilized for reducing the order of the system. Balanced realization based model design uses a full frequency spectrum to perform the model reduction. However, it is not possible practically to use the full frequency spectrum. The Variable-Speed Wind Turbines model utilized in this paper is stable and includes various input-output states. This brings a complicated state of affairs for analysis, control, and design of the full-scale system. The proposed work produces steady and precise outcomes such as in contrast to conventional reduction methods which shows the efficacy of the proposed algorithm.

Fault diagnosis in photovoltaic (PV) arrays is essential in enhancing power output as well as the useful life span of a PV system. Severe faults such as Partial Shading (PS) and high impedance faults, low location mismatch, and the presence of Maximum Power Point Tracking (MPPT) make fault detection challenging in harsh environmental conditions. In this regard, there have been several attempts made by various researchers to identify PV array faults. However, most of the previous work has focused on fault detection and classification in only a few faulty scenarios. This paper presents a novel approach that utilizes deep two-dimensional (2-D) Convolutional Neural Networks (CNN) to extract features from 2-D scalograms generated from PV system data in order to effectively detect and classify PV system faults. An in-depth quantitative evaluation of the proposed approach is presented and compared with previous classification methods for PV array faults – both classical machine learning based and deep learning based. Unlike contemporary work, five different faulty cases (including faults in PS – on which no work has been done before in the machine learning domain) have been considered in our study, along with the incorporation of MPPT. We generate a consistent dataset over which to compare ours and previous approaches, to make for the first (to the best of our knowledge) comprehensive and meaningful comparative evaluation of fault diagnosis. It is observed that the proposed method involving fine-tuned pre-trained CNN outperforms existing techniques, achieving a high fault detection accuracy of 73.53%. Our study also highlights the importance of representative and discriminative features to classify faults (as opposed to the use of raw data), especially in the noisy scenario, where our method achieves the best performance of 70.45%. We believe that our work will serve to guide future research in PV system fault diagnosis.

A proper and efficient system for clean and harmonic free power transfer between a generating plant and non-ideal distribution system has diverted the attention of power engineers. Nowadays the challenge being faced while designing grid connected inverter is to efficiently handle the unknown distortions and disturbances caused by non-ideal utility grid. Different filter topologies can be adopted in case of inverter design but to tackle the unknown noise and disturbance parameters, in case of distorted grid, needs significantly more than basic synchronization procedures. This paper introduces a new method for grid synchronization with three phase Voltage source inverter (VSI), in which synchronous reference frame Phase Lock Loop (SRF-PLL) followed by an adaptive technique Recursive Least Square (RLS) is presented. The main objective of using adaptive filters is to adapt the output signal of the inverter by noise cancellation with respect to the corresponding grid. Comprehensive study on Harmonic mitigation and efficient synchronization with Adaptive RLS filter design is presented in this paper. The whole system is designed and implemented in Matlab/Simulink.

As most of the electronic appliances use DC power so improvement in AC-DC converter is always at large by the researchers. The factors of improvement of power quality are reduction in total harmonic distortion and improvement in power factor at input ac, and tight output dc regulation. In such context, the AC-DC boost converters have gained significant importance, especially when they are used in Continuous Conduction Mode (CCM). This work presents a bridgeless AC-DC boost converter operating in CCM. The implementation of input current and output voltage controller is also discussed. Then a comparative analysis based on simulation results of bridgeless and bridge boost rectifier is presented. Bridgeless boost AC-DC converter has outperformed the conventional techniques due to lower conduction losses, lower THD of input current and improved input power factor.