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Developing an effective and efficient electroencephalography (EEG)-based drowsiness monitoring system is crucial for enhancing road safety and reducing the risk of accidents. For general usage, cross-subject evaluation is indispensable. Despite progress in unsupervised domain adaptation (UDA) and source-free domain adaptation (SFDA) methods, these often rely on the availability of labeled source data or white-box source models, posing potential privacy risks. This study explores a more challenging setting of UDA for EEG-based drowsiness detection, termed black-box domain adaptation (BBDA). In BBDA, adaptation in the target domain relies solely on a black-box source model, without access to the source data or parameters of the source model. Specifically, we propose a framework called Self-distillation and Pseudo-labelling for Ensemble Deep Random Vector Functional Link (edRVFL)-based Black-box Knowledge Adaptation (SPARK). SPARK employs entropy-based selection of high-confidence samples, which are then pseudo-labeled to train a student edRVFL network. Subsequently, ensemble self-distillation is performed to extract knowledge by training the edRVFL using refined labels introduced by ensemble learning. This process further improves the robustness of the student edRVFL network. The features of the edRVFL are beneficial for improving the computational efficiency of the framework, making it more suitable for tasks involving small datasets. The proposed SPARK framework is evaluated on two publicly available driver drowsiness datasets. Experimental results demonstrate its superior performance over strong baselines, while significantly reducing training time. These findings underscore the potential for practical integration of the proposed framework into drowsiness monitoring systems, thereby contributing substantially to the privacy preservation of source subjects.

In this article, a time-division multiplexing (TDM) modulation technology is proposed to enhance the efficiency of modular multiactive bridge (MMAB) converters in multiport power electronic transformers over a wide operating range. The TDM modulation retains the simplicity of single phase-shift (SPS) modulation while achieving efficiency improvement by adopting different structures (i.e., half-bridge and full-bridge) under different operating conditions with dc bias capacitors. However, determining the optimal structure under the same operating condition poses a significant challenge due to the strong coupling among MMAB ports. To address this issue, this article analyzes a dual-active bridge converter to investigate the steady-state characteristics of different structures, including the root-mean-square current and zero-voltage switching. By decomposing the MMAB converter into different transmission branches, the optimal combination structure of half-bridge and full-bridge are selected based on the branch powers, forming a simple and efficient TDM modulation technology. Finally, an experimental prototype of a four-port MMAB converter is established and tested. The results demonstrate that the proposed TDM can increase efficiency up to 19.09% compared to SPS, validating the correctness and effectiveness of the theoretical analysis.

With the rapid development of renewable energy, high-frequency bus electric energy router that provides multiple ports for different sources and loads is gaining attention, and the application of redundant modules for electric energy router is necessary to improve the reliability of the system. However, the strong coupling characteristics of the common high-frequency bus structure can cause transient current dc bias and current fluctuation for redundant modules during the entry stage, which may result in overcurrent, device damage, and failed entry of redundant modules. This article proposes a partial module high-frequency current model to analyze the causes of transient current dc bias of redundant modules when entering into normal operation and designs a seamless entry control strategy for redundant modules to eliminate the current dc bias and achieve rapid entry into steady-state operation, which can remove the high-frequency current sampling process to simplify the control system. The feasibility of the proposed control strategy is verified by offline simulation and hardware-in-loop real-time simulation platform.

With the increasing popularity of renewable energy and electric terminal equipment, the large-scale application of isolated bidirectional dc–dc converters (IBDCs) is growing. Among these converters, the dual active bridge (DAB) converter, as the core topology of IBDCs, has garnered significant attention due to its bidirectional power transmission capability, simple modularity, and wide soft-switching range. To enhance the efficiency of DAB, various multi-degree-of-freedom (M-DOF) modulation techniques and related solutions have been proposed. However, there is currently a lack of in-depth understanding and thorough comparison of different M-DOF modulation techniques, making it difficult to obtain the optimal solution for different application scenarios. Therefore, based on the latest research and contributions, this article provides an overview of M-DOF, including models, objectives, and algorithms. Furthermore, the existing typical M-DOF modulation techniques are compared through experiments, exploring the differences and advantages among these technologies. Through these analyses, this article offers robust support for the advancement and application of M-DOF modulation techniques in DAB converters.

In modular multiactive bridge (MMAB) converters, which are inherently coupled among dc ports, single phase shift (SPS) control has been widely adopted due to its simplicity in implementation and neglect of coupling characteristics in control algorithms. However, under SPS control, the converter may have unfavorable system efficiency performance, especially when voltage conversion ratios of ports mismatch. To improve the efficiency, this article proposes a common phase shift (CPS) control method for a generalized MMAB or multiactive bridge (MAB) converter. A comprehensive operation analysis of MMAB converters under CPS control with switching characterization of power semiconductors has been carried out. Besides, an overall power loss model is derived, with main electrical components and their power-loss behaviors taken into consideration. Moreover, an optimal strategy aimed at power loss optimization is proposed to improve the efficiency of the converter. Finally, a four-port experimental MMAB converter prototype has been constructed. The experimental results and tested efficiency curves have verified the feasibility and effectiveness of the proposed CPS control.