Analysis of Modulation and Optimal Design Methodology for Half-Bridge Matrix-Based Dual-Active-Bridge (MB-DAB) AC–DC Converter

Saha, Jaydeep; Gorla, Naga Brahmendra Yadav; Subramaniam, Aravinth; Panda, Sanjib Kumar

doi:10.1109/jestpe.2021.3107500

Cited by 26 publications

(3 citation statements)

References 44 publications

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“…This means that three individually controlled converters must be used in the three-phase PFC stage. Even though three-phase systems based on matrix converters were proposed in [30] and [147], this is not a common solution for i-AFE because of the high number of active components. For example, a phase-controlled i-AFE based on three 2×2 matrix converters results in the use of 36 active semiconductors [147], [148].…”

Section: Phase-controlled Single-stage I-afementioning

confidence: 99%

Grid Integration of DC Buildings: Standards, Requirements and Power Converter Topologies

Carvalho

Blinov

Chub

et al. 2022

IEEE Open J. Power Electron.

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Residential dc microgrids and nanogrids are the emerging technology that is aimed to promote the transition to energy-efficient buildings and provide simple, highly flexible integration of renewables, storages, and loads. At the same time, the mass acceptance of dc buildings is slowed down by the relative immaturity of the dc technology, lack of standardization and general awareness about its potential. Additional efforts from multiple directions are necessary to promote this technology and increase its market attractiveness. In the near-term, it is highly likely that the dc buildings will be connected to the conventional ac distribution grid by a front-end ac-dc converter that provides all the necessary protection and desired functionality. At the same time, the corresponding requirements for this converter have not been yet consolidated. To address this, present paper focuses on various aspects of the integration of dc buildings and includes analysis of related standards, directives, operational and compatibility requirements as well as classification of voltage levels. In addition, power converter configurations and modulation methods are analyzed and compared. A classification of topologies that can provide the required functionality for the This article has been accepted for publication in IEEE Open Journal of Power Electronics.

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Section: Phase-controlled Single-stage I-afementioning

confidence: 99%

Grid Integration of DC Buildings: Standards, Requirements and Power Converter Topologies

Carvalho

Blinov

Chub

et al. 2022

IEEE Open J. Power Electron.

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“…Power converters consist of interconnected individual circuit components (e.g., resistors, capacitors, inductors, diodes, and switching devices), making their design quite complex and prone to inefficiencies. To increase the energy conversion efficiency and stability in modern power systems, power converters are often optimally designed to achieve different operation goals [3]- [6]. For instance, the authors in [4] have proposed a novel soft-switching integrated boost DC-DC converter for PV power systems to reduce loss and improve power conversion efficiency.…”

Section: Introductionmentioning

confidence: 99%

Deep Neural Network-Based Surrogate Model for Optimal Component Sizing of Power Converters Using Deep Reinforcement Learning

Bui

Chang

et al. 2022

IEEE Access

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The optimal design of power converters often requires a huge number of simulations and numeric analyses to determine the optimal parameters. This process is time-consuming and results in a high computational cost. Therefore, this paper proposes a deep reinforcement learning (DRL)-based optimization algorithm to optimize the design parameters for power converters using a deep neural network (DNN)-based surrogate model. The surrogate model of power converters can quickly estimate the power efficiency from input parameters without requiring any simulation. The proposed optimization model includes two major steps. In the first step, the surrogate model is trained offline using a large dataset. In the second step, a soft actor-critic-based optimization model interacts with the surrogate model from step 1 to determine the optimal values of design parameters in power converters. Unlike deep Q learning-based methods, the proposed method is able to handle large state and action spaces. In addition, using entropy-regularized reinforcement learning, our proposed method can accelerate and stabilize the learning process and also prevent trapping in local optima. Finally, to show the effectiveness of the proposed method, the performance of different optimization algorithms is compared, considering over ten power converter topologies. INDEX TERMSComponent sizing, deep reinforcement learning, deep neural networks, optimal design parameters, optimization, power converters, surrogate model. NOMENCLATURE ABBREVIATIONS DNN Deep neural network DRL Deep reinforcement learning DDPG Deep deterministic policy gradient SAC Soft actor-critic The associate editor coordinating the review of this manuscript and approving it for publication was Seifedine Kadry . RUBEN GLATT (Member, IEEE) received the Dipl.-Ing. degree in mechatronics from the

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“…The aforementioned literature has not included any insight into to the reduction of the transformer losses during operation. [27] provides design procedure of an AC-DC DAB converter for optimizing efficiency and power density. A comparison of transformer efficiency has been provided in [28] for multilevel Si and SiC DAB converters and it is shown that 3 level modulation is an optimized modulation scheme for high power density, high efficiency and low cost.…”

Section: Introductionmentioning

confidence: 99%

FEA Based Transformer Loss Analysis for Dual Active Bridge DC–DC Converter Using Triple Phase Shift Modulation

Akbar

Hasan

Watson

et al. 2022

IEEE J. Emerg. Sel. Topics Power Electron.

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High frequency transformers are a key component of dual active bridge (DAB) dc-dc converters, providing isolation and voltage scaling. The losses in the transformer should be minimized to improve efficiency and extend lifetime. The existing research focuses on the optimization of design parameters, such as core material, cross sectional area and winding configuration to minimize losses. However, the transformer losses also depend on the harmonic content of the current as well as the design parameters and thus the efficiency can be further improved by selecting a modulation scheme which results in minimum current harmonics. This paper evaluates the effect of modulation schemes on the transformer losses of a DAB converter operating under triple phase shift (TPS) modulation by using finite element analysis. A comparison of losses under different modes of TPS modulation has been provided and it is proved that losses can be significantly reduced by selecting optimal modulation schemes. The experimental results performed on a 1kW DAB converter laboratory prototype are provided to validate the proposed work. Moreover, a generalized framework has been proposed to analyze and optimize transformer losses for isolated converters.Index Terms-Dual active bridge (DAB) dc-dc converter, finite element analysis (FEA), triple phase shift (TPS), winding loss.

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Analysis of Modulation and Optimal Design Methodology for Half-Bridge Matrix-Based Dual-Active-Bridge (MB-DAB) AC–DC Converter

Cited by 26 publications

References 44 publications

Grid Integration of DC Buildings: Standards, Requirements and Power Converter Topologies

Grid Integration of DC Buildings: Standards, Requirements and Power Converter Topologies

Deep Neural Network-Based Surrogate Model for Optimal Component Sizing of Power Converters Using Deep Reinforcement Learning

FEA Based Transformer Loss Analysis for Dual Active Bridge DC–DC Converter Using Triple Phase Shift Modulation

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