Iranian Journal of Electrical and Electronic Engineering
Volume:20 Issue: 1, Mar 2024

This paper proposed a control system for the battery charger of a solar vehicle. The battery charger has two parts, boost converter and isolated DC/AC/DC converter. The boost converter is controlled by a proposed control system based on sliding mode. In this controller, the MPPT is implemented by an extreme point of the solar cell P-V curve. Also, the control system of the DC/AC/DC converter is based on sliding mode with consideration of uncertainties of the output filter. A fast charging algorithm based on variable frequencies was carried out by the presented control system and charging of a Lithium-ion battery was done during 20 min from SOC 20% to SOC 80%. The simulation results show control system effectiveness.

The impact of cognitive tasks on human movement is of practical significance; we hereby aim to demonstrate that a significant relationship exists between the dual task’s cognitive demand and the disruption caused in hand movement, with the hope to extend this experiment to subjects with disorders (MS, CP, stroke patients) in future studies. By doing so, we hope to be able to develop a metric for evaluating their disease levels using our method and minimize clinical interventions. While previous research has predominantly focused on lower body activities, this study explores the effect of dual tasks on hand movements in healthy individuals.A simulated finger-to-nose test combined with a standard reverse counting task, featuring four difficulty levels, was conducted. Utilizing SVM and decision tree classifiers, we analyzed various features to discern the impact of cognitive tasks on hand movements, including completed cycles and idle time at markers. Our findings reveal that features such as entropy and kurtosis effectively distinguish between task difficulty levels and hand movement disruption. The classifiers achieved accuracies of 70% and 74% for decision tree and SVM, respectively. We hope extending this research to diseased subjects could potentially provide a more accurate assessment of disease severity through the measurement of hand movements during cognitive tasks, offering a non-clinical alternative for disease evaluation.

Dynamometers are equipment that has been widely used in the field of electric machines test benches. A dynamometer system has the ability to create intricate and unpredictable behaviours of mechanical loads according to a programmed manner. Extensive research into the characteristics of loads found in industrial settings has shown that non-linear and complex phenomena, including misalignment, mechanical friction, and others, are unavoidable in industrial drive systems. To assess the performance of motor and drive systems in industrial drives when subjected to these non-linear and complex loads, a fast and precise dynamic drive system must track high-frequency torque signals with precision. The suggested dynamometer, serving as an instrumental device, has the ability to emulate a wide torque response across various frequencies during both transient and steady-state conditions for the machine under test. Simulations and experimental results confirm the dynamometer's wide-ranging dynamic response, enabling the emulation of different linear and non-linear loads.

Losses in electric machines produce heat and cause an efficiency drop. As a consequence of heat production, temperature rise will occur which imposes severe problems. Due to the dependence of electrical and mechanical performance on temperature, conducting thermal analysis for a special electric machine that has a compact configuration with poor heat dissipation capability is crucial. This paper aims to carry out the thermal analysis of an axial-field flux-switching permanent magnet (AFFSPM) machine for electric vehicle application. To fulfill this purpose, three-dimensional (3D) finite element analysis is performed to accurately derive electromagnetic losses in active components. Meanwhile, copper losses are calculated by analytic correlation in maximum allowable temperature. To improve thermal performance, cooling blades are inserted on the frame of AFFSPM, and 3D computational fluid dynamics (CFD) is developed to investigate thermal analysis. The effect of different housing materials, the external heat transfer coefficient, and various operating points on the components' temperature has been reported. Finally, 3-D FEA is used to conduct heat flow path and heat generation density.

In recent years, due to the widespread applications of DC power-based appliances, the researchers attention to the adoption of DC microgrids are continuously increasing. Nevertheless, protection of the DC microgrid is still a major challenge due to a number of protection issues, such as pole-to-ground and pole-to-pole faults, absence of a zero crossing signal, magnitude of the fault current during grid-connected and islanded mode, bidirectional behaviour of converters, and failure of the converters due to enormous electrical stress in the converter switches which are integrated in the microgrid.  Failure of the converter switches can interrupt the charging of the electrical vehicles in the charging stations which can affect transportation facilities. In addition to the above mentioned issues protection of the DC microgrid is more challenging when fault parameters are varying due to dissimilar grounding conditions and varying operational dynamics of the renewable sources of energy. Motivated by the above challenges a support vector machine and ensemble of k-nearest neighbor based protection scheme has been proposed in this paper to accurately detect and classify faults under both of the modes of operation. Results in the section 5 indicate that performance of the protection scheme is greater as compared to other algorithms.

Cognitive radio (CR) is an effective technique for dealing with scarcity in spectrum resources and enhancing overall spectrum utilization. CR attempts to enhance spectrum sensing by detecting the primary user (PU) and allowing the secondary user (SU) to utilize the spectrum holes. The rapid growth of CR technology increases the required standards for Spectrum Sensing (SS) performance, especially in regions with low Signal-to-Noise Ratios (SNRs). In Cognitive Radio Networks (CRN), SS is an essential process for detecting the available spectrum. SS is divided into sensing time and transmission time; the more the sensing time, the higher the detection probability) and the lower the probability of a false alarm). So, this paper proposes a novel two-stage SS optimization model for CR systems. The proposed model consists of two techniques: Interval Dependent De-noising (IDD) and Energy Detection (ED), which achieve optimum sensing time, maximum throughput, lower and higher. The Simulation results demonstrated that the proposed model decreases the, achieves a higher especially at low SNRs ranging, and obtains the optimum sensing time, achieving maximum throughput at different numbers of sensing samples (N) and different SNRs from -10 to -20 dB in the case of N = 1000 to 10000 samples. The proposed model achieves a throughput of 5.418 and 1.98 Bits/Sec/HZ at an optimum sensing time of 0.5ms and 1.5ms respectively, when N increases from 10000 to 100000 samples. The proposed model yields an achievable throughput of 5.37 and 4.58 Bits/Sec/HZ at an optimum sensing time of 1.66ms and 13ms respectively. So, it enhances the SS process than previous related techniques.

In this paper, the performance of the EGLA (Externally Gaped Line Arresters) and its impact on the back flashover rate of a 400 kV transmission line have been investigated. The frequency behavior of the grounding system and soil resistivity has been modeled. To analyze the EGLA performance in relation to the grounding system's frequency behavior, a rod-shaped grounding system model has been implemented. By placing the EGLA at different phases of the transmission line, the best scenario has been identified to minimize back-flashover occurrences. Furthermore, the performance of the frequency grounding system to that of the nonlinear grounding system has been compared. The results clearly indicate that using a nonlinear grounding system leads to higher back flashover rates compared to the frequency grounding system. Additionally, the EGLA absorbs less energy when connected to a nonlinear resistor compared to the frequency grounding system. It can be concluded that modeling the grounding system's frequency behavior using the frequency grounding model provides more accurate results, especially in investigations related to power grid insulation coordination.

The scaling limitations of Complementary Metal-Oxide-Semiconductor (CMOS) transistors to achieve better performance have led to the attention of other structures to improve circuit performance. One of these structures is multi-valued circuits. In this paper, we will first study Carbon Nanotube Transistors (CNT). CNT transistors offer a viable means to implement multi-valued logic due to their variable and controllable threshold voltage. Subsequently, we delve into the realm of three-valued flip-flop circuits, which find extensive utility in digital electronics. Leveraging the insights gained from our analysis, we propose a novel D-type flip-flop structure. The presented structure boasts a remarkably low power consumption, showcasing a reduction exceeding 61% compared to other existing structures. Furthermore, the proposed circuit incorporates a reduced number of transistors, resulting in a reduced footprint. Importantly, this circuit exhibits negligible static power consumption in generating intermediate values, rendering it robust against process variations.  Overall, the proposed circuits demonstrate a 29.7% increase in delay compared to the compared structures. However, they showcase a 96.1% reduction in power-delay product (PDP) compared to the other structures. The number of transistors is also 8.3% less than other structures. Additionally, their figure of merits (FOM) are 19.7% better than the best-compared circuit, underscoring its advantages in power efficiency, chip area, and performance.

The potential adverse effects of maize leaf diseases on agricultural productivity highlight the significance of precise disease diagnosis using effective leaf segmentation techniques. In order to improve maize leaf segmentation, especially for maize leaf disease detection, a hybrid optimization method is proposed in this paper. The proposed method provides better segmentation accuracy and outperforms traditional approaches by combining enhanced Particle Swarm Optimisation (PSO) with Firefly algorithm (FFA). Extensive tests on images of maize leaves taken from the Plant Village dataset are used to show the algorithm's superiority. Experimental results show a considerable decrease in Hausdorff distances, indicating better segmentation accuracy than conventional methods. The proposed method also performs better than expected in terms of Jaccard and Dice coefficients, which measure the overlap and similarity between segmented sections. The proposed hybrid optimization method significantly contributes to agricultural research and indicates that the method may be helpful in real scenarios.  The performance of proposed method is compared with existing techniques like K-Mean, OTSU, Canny, FuzzyOTSU, PSO and Firefly. The overall performance of the proposed method is satisfactory.

Fifth Generation-New Radio (5G-NR) is an advanced air interface defined to fulfil diverse services with ubiquitous coverage in next generation Wireless networks. The waveform is the crucial part of air interface that must have good spectral confinement and low peak-to-average power ratio (PAPR). Orthogonal Frequency Division Multiplexing (OFDM) is a widely used air interface in Fourth Generation Long Term Evolution (4G-LTE) system. But OFDM suffers from high PAPR, Carrier Frequency offset (CFO), and loss of spectral efficiency due to insertion of cyclic prefix. So, the high dense networks with heterogeneous traffic in the 5G requires new multicarrier waveform. In the proposed work, waveforms based on sub-band filtering are considered due to more flexibility and shorter filter length as compared to the sub-carrier-based filtering waveforms. Two major 5G waveform candidates Filtered-Orthogonal Frequency Division Multiplexing (F-OFDM) and Universal Frequency Division Multiplexing (UFMC) are proposed in the system design. Channel coding is the inherent part of air interface for enhancing the error performance. New error correcting channel codes introduced in NR to support variable information block length and flexible codeword size. The capacity achieving Polar codes is the highlight of this paper adopted for control channels. 5G NR air interface using new modulation waveform along with the polar coding can be an effective way to enhance error performance. This paper presents comparative analysis of comprehensive systems Polar coded F-OFDM (PC-F-OFDM) and Polar coded UFMC (PC-UFMC) in massive MIMO scenario. Simulation results indicate that the proposed PC-F-OFDM systems significantly outperform the PC-UFMC systems in AWGN channel. But in massive MIMO setup BER performance of PC-UFMC is better than PC-F-OFDM system.

In recent decades, because of the rapid population growth of the world, considerable changes in climate, the reduction of fossil fuel sources to consume the traditional power plants and their high depreciation, and the increase in fuel prices.  Due to the increased penetration of DG units which have a random nature into the power system, the ordinary equations of power flow must be changed. For the power system to operate in a stable condition estimating future demand and calculating the important and operational indexes such as losses of the power system is an important duty that must be done precisely and rapidly. In this paper, the Improved Taguchi method and phasor measurement unit are used to model the uncertainties of DGs and estimate the error of voltage, respectively. The results show that the magnitude error and the angle error of voltage are decreased using PMU. The applied optimal power flow and state estimations are analyzed and verified using standard IEEE 30-bus and 14-bus test power systems by MATLAB, and MINITAB softwares. The Made Strides Taguchi strategy appears to have modeled the DG units precisely and successfully, and using the PMU, the mistake of the point and greatness estimation is exceptionally moot. The values that were evaluated are very close to the values that were done by the Newton-Raphson stack stream.

The progress of 5G networks is propelled by wireless technology, specifically mobile internet and smart devices. This article provides an in-depth analysis of the fundamental elements of 5G technology, encompassing the advancement of cellular networks, simultaneous transmission capabilities, energy efficiency enhancements, and the implementation of cooperative communication. This study examines the application of simultaneous wireless information and power transfer (SWIPT) in cooperative device-to-devices (D2D) communication. Specifically, it investigates relay selection using decode-forward (DF) protocols and considers the issue of self-interference. Radio frequency based energy harvesting (RF-EH) is proposed to address power limitations in device-to-device (D2D) communication. This article describes the development of this technology and suggests a system architecture that employs time-switching relaying (TSR) techniques to enhance the power efficiency of base stations. This research aims to assess data transfer efficiency in two-way cooperative communication systems by incorporating many technologies.

This paper proposes a stochastic optimization problem for local integrated hydrogen-power energy systems. In the proposed model, the integrated system tries to reduce the day-ahead operation costs using dispatchable resources, renewable energy resources, battery energy storage systems, demand response programs, and energy trading with the upstream network. Also, the integrated system is able to transact electricity with the upstream network to get more benefits. When the generation of renewable resources is high, the integrated system can convert the surplus electricity to hydrogen by power-to-gas units. The generated hydrogen can be sold to different industries or stored in the hydrogen tank storage. During peak hours, the stored hydrogen can be imported into the gas-to-power unit to generate the required electricity. The sector coupling between electricity and hydrogen provides more flexibility for integrated systems and is an effective solution to control the uncertainty of renewable energy resources in order to increase the power and energy flexibilities. The simulation results show that the proposed sector coupling provides the opportunity for electricity and hydrogen trading for integrated system. The benefit of the integrated system by electricity and hydrogen trading with the upstream network and different industries are $ 88.39, and $ 6846, respectively.