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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.

Intelligent and safe overtaking maneuvering is always a challenging task for autonomous vehicles. This paper proposes and experimentally implements a novel approach of overtaking maneuvering using modified form of Rendezvous Guidance (RG) algorithm for trajectory planning and obstacle avoidance, considering driver safety and comfort during autonomous overtaking. The simulations for all possible scenarios are conducted to ensure the effectiveness of proposed modified RG algorithm. These scenarios involved presence and absence of obstacle vehicle in overtaking lane alongside leading vehicle in driving lane. In addition, the enhanced performance of modified RG algorithm is established over conventional RG algorithm by comparative analysis. The results indicate that overtaking maneuvering period could be decreased by 10% using a modified RG algorithm and vehicle will cover less distance to complete overtaking. The efficacy of proposed method is justified by performing experiments using mobile robots. The experimental results and simulation results of modified RG algorithm are compared, and their plots are almost identical.

Solar photovoltaic PV plants worldwide are continuously monitored and carefully protected to ensure safe and reliable operation through detecting and isolating faults. Faults are very common in modern solar PV systems which interrupt normal system operation adversely affecting the performance of the PV systems. When undetected, faults not only cause significant reduction in the efficiency and life span of the PV system, but also result in damage and fire hazards compromising their reliability. Therefore, early fault detection and diagnosis of photovoltaic plants is a necessity for safe and reliable operation required for growing solar PV systems. Unfortunately, several recent fire incidents have been reported recently caused by undetected faults in solar PV systems. Motivated by this challenge, this paper, utilizing a proposed fuzzy logic algorithm, presents a novel technique for detecting and classifying faults in solar PV systems. Furthermore, the proposed method introduces fault indexing as a performance indicator that measures the degree of deviation from the normal operating conditions of the photovoltaic system. Various signatures of each fault scenario are identified in the shape of corresponding current-voltage trajectories and their extracted parameters. The effectiveness of the proposed technique is evaluated both in simulation and experimentally using a 5 kW grid connected solar array. It is demonstrated that the proposed technique is capable of diagnosing the occurrence of different faults with more than 98% accuracy.

Fault analysis in photovoltaic (PV) arrays is considered important for improving the safety and efficiency of a PV system. Faults do not only reduce efficiency but are also detrimental to the life span of a system. Output can be greatly affected by PV technology, configuration, and other operating conditions. Thus, it is important to consider the impact of different PV configurations and materials for thorough analysis of faults. This paper presents a detailed investigation of faults including non-uniform shading, open circuit and short circuit in different PV interconnections including Series-Parallel (SP), Honey-Comb (HC) and Total-cross-Tied (TCT). A special case of multiple faults in PV array under non-uniform irradiance is also investigated to analyze their combined impact on considered different PV interconnections. In order to be more comprehensive, we have considered monocrystalline and thin-film PV to analyze faults and their impact on power grids. Simulations are conducted in MATLAB/Simulink, and the obtained results in terms of power(P)–voltage(V) curve are compared and discussed. It is found that utilization of thin-film PV technology with appropriated PV interconnections can minimize the impact of faults on a power grid with improved performance of the system.

High-frequency transformers are becoming an essential component in the integration of power resources that rely on power electronic converters; their efficiency and performance are influenced by parasitic characteristics in the interface. In this article, the design of a high-frequency toroidal transformer has been explained in detail using the ANSYS Maxwell platform. Various parameters, such as leakage inductance, magnetic flux density, magnetic field strength and uniform magnetic flux line are analyzed using Finite element analysis. High-frequency transformers using a toroidal core with different winding configurations are examined and all parameters obtained through simulation are validated by an analytical approach. Analysis of each design is based on its leakage inductances, which will aid in the appropriate selection of transformers as a function of their operating frequency. This analysis is expected to guide designers to optimize the high-frequency transformer parameters based on practical applications. The optimized parameters are then applied for a dual active bridge (DAB) converter within MATLAB/Simulink to verify the design process. A prototype has been built to validate the simulation and design procedure. The results obtained from both simulation and experiments are compared and show great correlation.

Energy demand forecasted for the next several years has been bench marked due to the massive need for electrical energy. Solar power plants have earned a great marketplace position in recent years, but also face challenges in terms of power dissipation due to the frequent occurrence of shade. As a result, the per unit solar electricity price increases drastically. There is an immense need to ensure the maximum dependable power conversion efficiency of Photovoltaic (PV) systems by mitigating power output losses during partial shading conditions. The reconfiguration of PV arrays is a useful, effective, and promising approach in this context. Though several reconfiguration techniques have been developed in recent years, their applicability to real-time power plants is debatable due to the requirement of many physical relocations, long interconnecting ties, and complexity. This research work proposes a novel row index mathematical procedure followed by a technique in which the reconfiguration matrix indexes are filled with a unique number so that no row number repeats in the same row and column. Additionally, the proposed approach uses small number of switches that reduce the cost as well as the computational complexity. To strengthen the analysis, very recent techniques such as Sudoku, Total Cross Tied (TCT), Chess-Knight, and Particle Swarm Optimization (PSO) based reconfiguration are compared against five different shading patterns. It has been observed that approximately 68% power loss is mitigated in TCT configuration. It is worth noting that it results in higher PV output power than the existing latest reconfiguration techniques such as PSO, Chess-Knight, Sudoku, and others.

Lithium-ion batteries are the most used technology in portable electronic devices. High energy density and high power per mass battery unit make it preferable over other batteries. The existing constant-temperature and constant-voltage charging technique (CT–CV), with a closed loop, lacks a detailed design of control circuits, which can increase charging speed. This article addresses this research gap in a novel way by implementing a simpler feedback proportional integral and differential (PID) control to a closed-loop CT–CV charging circuit. Voltage-mode control (VMC) and average current-mode control (ACM) methods were implemented to maintain the battery voltage, current, and temperature at safe limits. As per simulation results, 23% faster charging is achieved by implementing VMC and almost 50% faster charging is attained by employing the ACM technique in the PID controller. Our proposed control strategy is validated experimentally, which yields up to 25% faster charging of a battery than the reference battery.

Intelligent and safe overtaking maneuvering is always a challenging task for autonomous vehicles. This paper proposes and experimentally implements a novel approach of overtaking maneuvering using modified form of Rendezvous Guidance (RG) algorithm for trajectory planning and obstacle avoidance, considering driver safety and comfort during autonomous overtaking. The simulations for all possible scenarios are conducted to ensure the effectiveness of proposed modified RG algorithm. These scenarios involved presence and absence of obstacle vehicle in overtaking lane alongside leading vehicle in driving lane. In addition, the enhanced performance of modified RG algorithm is established over conventional RG algorithm by comparative analysis. The results indicate that overtaking maneuvering period could be decreased by 10% using a modified RG algorithm and vehicle will cover less distance to complete overtaking. The efficacy of proposed method is justified by performing experiments using mobile robots. The experimental results and simulation results of modified RG algorithm are compared, and their plots are almost identical.

The growth and productivity of wheat crops depend on the availability of essential nutrients such as zinc (Zn) and potassium (K2O), which play critical roles in the plant’s physiological and biochemical processes. This study aimed to investigate the synergizing effect of zinc and potassium fertilizers on uptake of both the nutrients, growth, yield, and quality of the Hashim-08 cultivar and local landrace, during the 2019–2020 growing season in Dera Ismail Khan, Pakistan. The experiment was designed using a split plot pattern in a randomized complete pattern, with main plots for the wheat cultivars and subplots for the fertilizer treatments. Results indicated that both cultivars responded positively to the fertilizer treatments, with the local landrace exhibiting maximum plant height and biological yield, and improved Hashim-08, showing increased agronomic parameters, including the number of tillers and grains and spike length. Application of Zn and K2O fertilizers significantly enhanced agronomic parameters, such as the number of grains per plant, spike length, thousand-grain weight, grain yield, harvest index, Zn uptake of grain, dry gluten content, and grain moisture content, while crude protein and grain potassium remained relatively unchanged. The soil’s Zn and K content dynamics were found to vary among treatments. In conclusion, the combined application of Zn and K2O fertilizers proved beneficial in improving the growth, yield, and quality of wheat crops, with the local landrace exhibiting lower grain yield but greater Zn uptake through fertilizer application. The study’s findings highlight that the local landrace showed good response to the growth and qualitative parameter when compared with the Hashim-08 cultivar. Additionally, the combined application of Zn and K showed a positive relation in terms of nutrient uptake and soil Zn and K content.

Due to the high spectral efficiency (SE) and fast synchronization, the time-domain synchronization orthogonal frequency division multiplexing (TDS-OFDM) system has gotten much more attraction of researchers as compared to cyclic-prefix (CP) and zero padding (ZP) OFDM in terrestrial as well as underwater acoustic communication. Inter-block interference (IBI) degrades the TDS-OFDM performance due to its long-delay multiple channels. In TDS-OFDM, dual pseudo-random noise (DPN) sequences utilize two PN sequences as a guard interval (GI) after every data block to cope with interference from the OFDM data block to the next PN sequence resulting in compromising the energy efficiency (EE) and spectral efficiency. We have proposed compressed sensing-based technique compressive sensing matching pursuit (CoSaMP), orthogonal matching pursuit (OMP), and look-ahead and backtracking OMP (LABOMP) for TDS-OFDM over the real-time underwater channel in this paper. Moreover, prior to estimating the channel, the received PN sequence is considered in the time domain to compensate for the Doppler shift of the UWA channel. The real-time data experiment has been initially conducted for testing in a water tank in our laboratory. Furthermore, it has been tested on the sea for long communications under the water at the Wuyuan sea area in Xiamen, China. Simulations and experimental results evident that the compressed sensing techniques have better performance over the conventional TDS-OFDM and DPN-TDS-OFDM, even LABOMP outperform OMP and CoSaMP in terms of bit-error-rate (BER), SE, and EE.