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In order to address the issue of keeping the converter operating at a high efficiency level under different conditions, this paper suggests an adaptive step frequency adjustment online optimization search algorithm, which achieves the goal of fast adjustment and real‐time response to parameter changes. The converter is quickly adjusted to operate at a high efficiency by sampling the input and output current values and modulating the switching frequency utilizing the algorithm. Additionally, the algorithm shifts between two working models to finish the search for the best switching frequency while the converter's characteristics do not change. Moreover, it accomplishes the objective of instantly resynchronizing the algorithm after a change in the converter's parameters and starting a search for the best switching frequency in the new converter state. For various input voltages and output loads, the operating principle, optimal frequency, and efficiency are given. In addition, the principle analysis when the converter parameters are changed is provided, and the choice of two algorithm models is compared. Finally, a prototype buck converter with adjustable input voltage and load is constructed to test the algorithm's efficiency. [ABSTRACT FROM AUTHOR]

In the application of bipolar DC bus configuration in the DC nanogrid, the unbalanced voltage of two outputs in bipolar DC bus, due to the unbalanced conditions of loads and/or energy sources, will cause deterioration of the power quality of the bus and may damage the switch, affecting the stability and safety of the system. In order to solve the problem of unbalanced voltage of two outputs, interleaved series capacitor based dual‐output converter with a high conversion ratio is presented in this paper. By applying negative current mode (NCM) to the main inductor, the character of two‐output self‐balancing and zero voltage switching (ZVS) of all switches for such this topology configuration is achieved. In the NCM mode, the parallel diodes of main switches are not conducted during dead time and guarantee the flowing path to load side. Thus, based on this condition, volt‐second balance of main inductor is obtained to get the character of two‐output self‐balancing. Furthermore, by adopting series capacitor in the proposed topology and based on the charge‐balance of the intermediate block capacitor, inductor current existed in the two phase could be auto‐sharing. Comprehensive operational principle analysis, loss analysis, and efficiency of the proposed converter under different load conditions have been given, and the comparison analysis of three operation modes and selection of negative current mode is clarified. Small signal model of the proposed converter is described to convenient for the controller design. Finally, simulation results and a 20–220 V prototype are built to verify the character analysis of the proposed converter. [ABSTRACT FROM AUTHOR]

Aim to improve the power efficiency of the dual-active-bridge (DAB) dc–dc converter, an efficiency optimization scheme with triple-phase-shift (TPS) modulation using reinforcement learning (RL) is proposed in this article. More specifically, the Q-learning algorithm, as a typical algorithm of the RL, is applied to train an agent offline to obtain an optimized modulation strategy, and then the trained agent provides control decisions online in a real-time manner for the DAB dc–dc converter according to the current operating environment. The main objective is to obtain the optimal phase-shift angles for the DAB dc–dc converter, which can achieve the maximum power efficiency by reducing the power losses. Moreover, all possible operation modes of the TPS modulation are considered during the offline training process of the Q-learning algorithm. Thus, the cumbersome process for selecting the optimal operation mode in the conventional schemes can be circumvented successfully. Based on these merits, the proposed efficiency optimization scheme using the RL can realize the excellent performances for the whole load conditions and voltage conversion ratios. Finally, a 1.2-KW prototyped is built, and the simulation and the experimental results demonstrate that the power efficiency can be improved by using the optimization scheme based on the RL. [ABSTRACT FROM AUTHOR]