Analysis and verification of leakage inductance calculation in DAB converters based on high-frequency toroidal transformers under different design scenarios

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

Analysis of the dual active bridge-based DC-DC converter topologies, high-frequency transformer, and control techniques

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.Web of Science1523art. no. 894

High gain coupled inductor SEPIC based boost inverter using extended SPWM

This research work designs a high gain coupled inductor SEPIC (CI-SEPIC) based boost inverter. This topology presents low switching voltage stress, high output DC and AC voltage and highly efficient system, which makes it suitable for renewable energy applications. A seventh order system is obtained through dynamic modelling of the CI-SEPIC converter for which PID controller is designed to track the reference value. The extended sine-wave pulse width modulation (ESPWM) has maintained the high gain without compromising the efficiency and ensured low voltage stress on the switching devices. Simulation and experimental results validated that CI-SEPIC based boost inverter with ESPWM achieved high dc gain of 15.98, boost factor of 25, exceptional dc-ac coupling with minimum possible capacitance of 3.3uF, decreased device stress by 33% and smaller size of the complete system

Analysis of the Dual Active Bridge-Based DC-DC Converter Topologies, High-Frequency Transformer, and Control Techniques

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

Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line

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

Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line

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