Recent Advances in Electrical & Electronic Engineering - Volume 16, Issue 4, 2023

Nowadays, the wind energy running cost is the cheapest renewable electrical energy. This study describes different static power converters for a doubly fed induction generator that are based on power quality solutions (DFIG). The latest isolated & grid-connected converter employed like AC-DC-AC bidirectional converter is used for active and reactive power compensation, without dc-link AC-AC converter for voltage swell and swag, Multilevel inverter for voltage improvement, and facts devices such as D-STATCOM, UPQC, UPS, STATCOM, SDVR mitigatory for the power quality problem. Various topologies are discussed for mitigation of power quality through the grid code. On the other hand, various controllers joined to the power electronics converter play an important role in solving sag, swell harmonics, flicker, noise, spinning reverse, and so on. This paper investigates various power converters and an electronic controller for DFIG. At the end, different power quality indices and problems are discussed for faulty operating conditions.

This paper focuses on better understanding the Indian Electric Vehicle (EV) market scenario based on battery and motor specifications. Electric two-wheelers, three-wheelers, and fourwheelers have different challenges and requirements at the efficient design level. This paper also provides a comprehensive review of brushed DC motors, brushless DC (BLDC) motors, permanent magnet synchronous motors (PMSM), induction motors (IM), switched reluctance motors (SRM), and flux switching motors (FSM) for EV application. Background: The market for EVs is growing rapidly in India as a developing country, and users are looking forward to highly efficient and cost-effective EVs due to the pollution and unavailability of petroleum. Objective: The main objective of this paper is to provide the right choice of EV motor based on vehicle type, driving cycle, and user requirement. Method: This paper comprehensively reviews DC and AC motor drive systems for EV application. Conclusion: Nowadays, manufacturing is mainly inclined towards the BLDC, PMSM, and IM. In contrast, SRM and FSM are in the early stage of development and are mainly used by the researcher. A brushed DC motor is not too famous due to its high running cost, frequent maintenance requirements, and comparatively bulky size.

Background: Due to their superior efficiency, stability, and ability to produce maximum power under various typical operating situations, wind turbines driving doubly fed induction generator systems are frequently utilized in wind power extraction. These systems face stability problems especially at severe faulty conditions. Objective: To protect the rotating parts of the system from over speeding when the fault occurs and to ensure that the generator does not deviate from stability by adjusting the aerodynamic torque of the wind turbine. In addition, to protect electrical parts of the system, especially DC bus voltage and power electronics converters. Methods: Using Adaptive Neuro-Fuzzy Inference System (ANFIS). The proposed ANFIS technique detects the faulty conditions from the measured voltages and currents at the terminals of the generator. In case of faulty cases, an ANFIS technology activates the wind turbine's pitch angle controller and the crowbar resistance. Results: A comparison between the behavior of DFIG at faulty conditions without any fault controller and with the proposed ANFIS technique is applied. When the ANFIS technique is used, the wind system's performance and response are improved. Conclusion: The proposed ANFIS control system has proven its effectiveness in protecting the DFIG in the event of a grid fault.

Introduction: Advanced low-power designs have been scaled down to the device parameters that increase single-event multi-node upset in memory elements. This degradation of the stability of the memory elements in aerospace applications is due to the high radiation environment and rapid temperature changes. Methods: Hence, this paper presents a comprehensive treatment model for hardened storage elements with a soft error resulting in multi-node upset. A novel 12T SRAM memory cell configuration has been proposed, analysed, and simulated using Cadence Virtuoso gpdk 45 nm CMOS technology. Results: The proposed design counteracts the positive feedback induced due to the charged ion strike, as in past technical literature. The radiation environment has been realized with double exponential current sources, and temperature analysis has been carried out under parametric analysis. Conclusion: The novel 12T achieves good stability and remains resilient to bit-flip due to ion strikes for a wider range of voltage when the temperature varies from -50°C to 200°C. Moreover, the proposed structure features a lower susceptibility to single event upset, less write and read time, and reduced area compared to the reported RSP 14T.

As the current calculation method of voltage/var sensitivity (VVS) could not reflect the temporal variations of power sources and load, the paper proposes a novel VVS calculation method to partition the distribution network containing renewable energy. Firstly, the defects of the existing VVS calculation methods are analyzed, and a novel VVS calculation method is proposed by adding reactive power output perturbation to the reactive power source. Secondly, the VVS matrix is fuzzified to obtain the membership matrix between each node. Based on the membership relationship between the reactive power source nodes, the nodes with a strong coupling relationship are merged to determine the initial number of partitioning. Then, the final partitioning result is determined according to the affiliation between each load node and each reactive power source. Finally, the partitioning result is evaluated based on the partitioning membership indexes. The proposed approach is tested on the IEEE 33-node distribution test system, and numerical simulations verify the high efficiency of partitioning. The simulation results show that the proposed method can reflect the temporal variations of power sources and load, and ensure the reasonable distribution of voltage and reactive power in each zone. Background: The voltage/var control of the power system is an important means to ensure the safe, economic and stable operation of the system. Objective: The paper proposes a novel VVS calculation method to partition the distribution network containing renewable energy. Methods: Firstly, the existing problems of electrical distance index are analyzed. A novel VVS matrix calculation method is proposed, which calculates the VVS of each reactive power source to the remaining nodes by adding voltage/var output perturbation to the reactive power source. Secondly, the VVS matrix is fuzzified to obtain the membership matrix between each node. Based on the membership relationship between the reactive power source nodes, the power supply nodes with strong coupling relationship are merged to determine the initial number of the partitioning. Then, the final partitioning result is determined according to the affiliation between each load node and each reactive power source. Finally, the partitioning result is evaluated based on the sensitivity index of membership degree. Results: The proposed approach is tested on the IEEE 33-node distribution test system and numerical simulations verify high efficiency of the partitioning. The simulation results show that the proposed method can reflect the temporal variations of power sources and load, and ensure the reasonable distribution of voltage and reactive power in each zone. Conclusion: The proposed method can reflect the temporal variations of power sources and load, and ensure the reasonable distribution of voltage and reactive power in each zone. This paper proposed a fuzzy clustering partitioning based on a novel calculation method of VVS, which is suitable for the problem of variable voltage /var running state of the system under high-proportion DG access.

Background: Vehicles have become one of the most important means of transportation, and license plate is the only identifying mark of vehicles. License plate recognition technologies are being applied to a series of occasions, such as supervising road traffic violations, recovering stolen vehicles, monitoring wanted vehicles, and dispatching special vehicles. The license plate tilt phenomenon caused by various reasons has brought great trouble to its own recognition. Objective: How to identify tilted license plates efficiently and accurately becomes the key to the automatic management of a large number of vehicles. Therefore, a real-time location, correction and segmentation algorithm based on the tilted license plate is proposed in this paper. Methods: Firstly, an end-to-end deep convolutional neural network (CNN) is proposed for the location detection of the tilted license plate. The developed CNN is optimized by the most advanced RefineDet algorithm. By improving the object detection module, the representation ability of the CNN for small features and the accuracy of the detector are improved, so as to make the location regression and label prediction of the detected object more accurate. Secondly, the optimized perspective transformation algorithm is applied to correct the tilted license plate. According to the vertices coordinates of the bounding box detected by our CNN, the license plate area cropped out from the original image has a certain tilt angle, and the perspective transformation algorithm achieves the correction. Finally, digital image processing technology is used to segment the characters of license plates. Results: The experimental results in the Chinese City Parking (CCP) dataset show that the proposed algorithm exhibits location average precisions improvements of 2.4-5.4% over the other algorithm. Conclusion: The proposed algorithm achieves high-accuracy correction and real-time segmentation.

Background: Coordinate Rotation Digital Computer (CORDIC) can be used for computing trigonometric functions like sine and cosine for which it iterates over a for loop and performs rotation of the input angle. Methods: On the basis of the condition, it decides addition and subtraction operations to compute the sine and cosine values. In general, for each iteration in the CORDIC algorithm, it produces 1 extra bit of accuracy. This paper presents an in-depth survey of the many changes to the CORDIC algorithm proposed over recent years. An efficient method to calculate the sine and cosine of an input angle using the CORDIC algorithm with minimum hardware requirement is presented here. Results: CORDIC algorithm is implemented for 8 bits, 16 bits and 32 bits input and the average percentage error obtained as the results are 1.67%, 0.003785% and 0.003290% respectively. Conclusion: It can be seen that by increasing the number of bits, the accuracy increases. For a complete survey, discussions addressing the CORDIC algorithm are also presented.

Background: Oil-immersed distribution transformer is an important power transmission and distribution equipment in the power system. If it fails, it will cause huge economic losses and safety hazards. It is of great significance to identify and diagnose its faults, find potential faults in time, and restore normal operation. Objective: To detect transformer fault, a transformer fault diagnosis method based on Graph Markov Neural Networks for Particle Swarm Optimization algorithm (PSO-GMNN) is proposed. Methods: Five common dissolved gases in transformer oil are used to construct a 22-dimensional feature set to be selected, and then the similarity between each feature vector is calculated by using Mahalanobis Distance. The graph structure is constructed with feature vectors as vertices and similarities as edges. Finally, the Particle Swarm Optimization algorithm is used to optimize the initial weights of Graph Markov Neural Networks, and then transformer fault diagnosis is realized. Results: The experiments are performed in the environment of Python 3.7, PyTorch 1.6.0, and the validity of the proposed method is verified by a comparative analysis of the detection accuracy between the proposed method and existing mainstream methods. Conclusion: A transformer fault diagnosis method based on Graph Markov Neural Networks for Particle Swarm Optimization algorithm is proposed to detect transformer fault, and the experimental results demonstrate the effectiveness and advantage of the proposed method.

Background: The era of flexible antennas started long ago because they are cost-effective while offering several advantages, such as good flexibility, stretchability, and compactness. Although several synthetic and natural polymers with good flexibility are available, the first flexible antenna is designed with polyimide materials (polymers), often known as engineering plastics. Objective: To fabricate a compact antenna with a higher gain than other existing ones and the bending loss of the proposed antenna is lower than other existing ones, this study proposes an ideal antenna. Methods: A polyimide (PI)-based flexible antenna with a defected ground structure is proposed for telemedicine and wireless applications, and we implement this antenna using microstrip feeding. The proposed antenna consists of a polyimide substrate with a thickness of 0.1 mm, a relative permittivity of 3.15, a loss factor of 0.0013, and a compact overall size of 25 x 32 x 0.1 mm³. Results: The proposed antenna operates on three frequencies, including 2.4 GHz (ISM or telemedicine application), 5.5 GHz (WiMAX band), and 7.5 GHz (wireless radio band). The proposed antenna produces impedance bandwidths of 10.16%, 14.54%, and 5.33% at frequencies of 2.4 GHz, 5.5 GHz, and 7.5 GHz, with gains of 4.9 dB, 5.1 dB, and 5 dB. Conclusion: The proposed antenna is simulated using Ansys High-Frequency Structure Simulator (HFSS) software. A good agreement is found between the measured and simulated results.

Background: The on-board test system is the key technology of in-wheel motor electric vehicles, which plays a vital role in the safety of the driver and the efficient operation of the vehicle. Methods: Based on the requirements of the current in-wheel motor electric vehicle experiment teaching content, this research develops an in-wheel motor electric vehicle experimental teaching platform based on Matlab/Simulink and LabVIEW to meet the current needs of the in-wheel motor electric vehicle experiment teaching content. Results: The vehicle speed, sideslip angle, and road adhesion coefficient can be accurately estimated using the vehicle test platform developed in the article. Conclusion: With accurate experimental results, the functionality, value, and teaching value of the in-wheel motor electric vehicle experimental teaching platform were fully verified.

Background: Recently, the construction of a smart city has accelerated due to developing technologies such as 5G and the Internet of things (IoT). The IoT is gaining access day by day in the area of the remote monitoring system. Along with smart city concepts, intelligent patient monitoring systems and intelligent health are being developed. Combining the two, here, patients have a nurse navigation system and a doctor emergency call system. IoT improves the effectiveness of medical equipment by providing real-time monitoring of patient health, in which sensors collect data from patients with less human errors. In IoT, the patient's parameters get transmitted through medical devices via a gateway to the centralized system, where it is stored and analyzed. Objective: In this paper, we have proposed an intelligent patient monitoring system for monitoring the patients' health condition automatically through sensors-based connected links. The system is more intelligent that it can be able to detect the critical condition of a patient by processing sensor data and instantly provides a notification to doctors/nurses as well as hospital in-charge personnel. The doctors and nurses get benefited from this system by observing their corresponding patients remotely without visiting to the particular seat of the patient. Methods: An idea has been proposed to use the centralized processing of IoT devices along with the rigid security and privacy of the classical blockchain to overcome the computation expense challenge with blockchain and the security and privacy threat of the IoT systems. We are developing a system in the field of medical care to enhance the functioning of Medicare systems and provide patients with more ease and hassle-free procedures of the Medicare system, i.e., hospitals, laboratories, dispensaries, chemists, druggists, etc. Results: This model helps in getting rid of this issue faced by all of us. There is a separate blockchain of different verified medical stores linked within the networks, which will be managed by the central hub based on their ratings, reviews, and stock availability. Conclusion: The exponential expansion of blockchain technology in healthcare is also astonishing and has a tremendous impact on the industry. By assessing prior activities, the idea is proposed to use a centralized database system with more privacy and security to gap between the healthcare industry and blockchain technologies has been addressed in this paper.

Background: Devices with field plates have gained much popularity in high power and high voltage applications. The work done in this paper is related to designing and studying the different DC and RF characteristics of a field plated GaN HEMT. The results obtained were compared with that of non-field plated GaN HEMT. This comparison and study reported the effect of field plate on device performance. Methods: A GaN HEMT device with and without a field plate was designed and simulated in the SILVACO ATLAS TCAD tool. The performance of both the devices was compared in terms of the exhibited DC and RF characteristics in order to study the effect of the field plate on the device. We have also studied the variation in the cut-off frequency and maximum frequency of both the field plate and without field plate GaN HEMT with respect to gate-source voltage. We have further investigated the device performance by varying the length of the field plate from 0 to 2.5 μm. Results: The study reflects the advantageous feature of GaN HEMT with field plate by exhibiting high breakdown voltage of 292 V in comparison to GaN HEMT without field plate which exhibits a breakdown voltage of 98 V. As a result of using field plate in the GaN HEMT structure, a rise in the Cgs and Cgd capacitances are witnessed. This in turn affects the other RF characteristics of the GaN HEMT with field plate even though the GaN HEMT with and without field plate exhibits nearly same DC characteristics. The field plated GaN HEMT exhibits a reduced cut-off frequency and maximum frequency of 7 GHz and 20 GHz, respectively, in comparison to the GaN HEMT without field plate’s cut-off frequency and maximum frequency of 10 GHz and 25 GHz, respectively. Conclusion: The study reports that using a field plate helps in enhancing the breakdown voltage but at the cost of reduced frequency performance. We have compared our proposed field plated device with different non-field plated devices and concluded that our device exhibits much higher breakdown voltage in spite of reduced device dimension. With the attainment of higher breakdown voltage our proposed GaN HEMT device can be used for high power applications. From the study, it is reported that while increasing the length of the field plate the breakdown voltage also increases. For a particular set of device dimensions, an optimum field plate length provides the highest breakdown voltage but increasing the length of the field plate beyond the optimum value results in reduction in breakdown voltage.