This paper proposes a highly reliable multi-input DC/DC converter designed for long-endurance unmanned aerial vehicles (UAVs) in industrial and commercial applications. The proposed converter consists of a SEPIC converter and n expandable units. With n+1 input ports, the proposed converter can efficiently interface with multiple photovoltaic (PV) arrays. Moreover, each input port of the converter features redundancy and can operate independently, thereby ensuring stable operational performance and high reliability. Furthermore, the proposed multi-input converter (MIC) can realize low input current ripple with the coupled inductor, which can both minimize the input filter capacitor of the converter and reduce the volume of the UAV power system, ultimately achieving a power density of 35.523 W/in3. Based on the theoretical analysis and simulation, a prototype with 1 kW output power is fabricated. Experimental results verify the effectiveness of the operational principles and the validity of its characteristics.

Battery voltage balancing of series-connected battery packs is the crucial guarantee for the safe and efficient operation of the battery. This paper reviews the recent advancements in balancing topologies for series battery packs. The necessity of battery balancing is first introduced. Subsequently, the characteristics of passive balancing are analyzed. Then the active balancing techniques are categorized into four types: switched-capacitor, switched-inductor, bidirectional converter, and multi-winding transformer topologies. The focus of the review lies on analyzing the different features and vital distinctions among these active balancing topologies, analyzing their balancing mechanisms and design principles. The merits and limitations of each balancing topologies are delineated, along with their suitable application scenarios. Finally, based on the developmental requirements of battery balancing topologies, potential future research directions are proposed.

This paper presents a dual-switch high-voltage-gain DC-DC converter designed for renewable energy-based DC microgrids, utilizing a coupled inductor and voltage multiplier cells to achieve high voltage step-up. The proposed topology achieves high voltage gain at low duty cycles, which enhances efficiency by minimizing conduction losses. Operating at reduced duty cycles not only improves power conversion efficiency but also contributes to lower thermal stress on semiconductor devices, further enhancing reliability. Additionally, the converter features low input current ripple, which is crucial for the stable integration of renewable energy sources such as photovoltaic panels and ensuring smooth power delivery to the load. The common ground connection between the input and output ports simplifies system integration and enhances safety and makes the converter suitable for connecting low-voltage renewable sources to a high-voltage DC bus in microgrid applications. The combination of high voltage gain, high efficiency, and reduced input current ripple positions this converter as a suitable solution for renewable energy systems, where maximizing power extraction and minimizing losses are critical. To verify the converter’s performance, detailed operational modes, steady-state analysis, comparative evaluations, and experimental results are provided.

An accurate and reliable thermal property model is important for evaluating the thermal stress of insulated gate bipolar transistor (IGBT) modules and analyzing their reliability. For the first time, fractional-order thermal capacitance (FOTC) is introduced in this article as a new modeling element for IGBT modules thermal analysis. Meanwhile, this article presents a fractional-order thermal network model (FOTNM) for IGBT modules based on the potential relationship between the time-dissipative characteristics of power device heat transfer and the time-domain behavior of FOTC. In addition, the parameters of the proposed FOTNM are extracted by the Levenberg-Marquardt algorithm. To verify the scheme, this article presents both experimental and comparative studies. The analysis demonstrates that, compared to the traditional Foster thermal network model, the presented FOTNM can accurately characterize the thermal impedance properties of the IGBT module with fewer model parameters and a relatively simple form, thereby improving the efficiency of model parameter extraction and thermal analysis.

The development of 5th-generation mobile networks, 5G communication, is currently underway. However, the high energy consumption and associated carbon emissions of 5G base stations have emerged as significant challenges. Based on the DC load characteristics of 5G base stations, this paper designs and constructs an innovative photovoltaic-storage DC power supply system. And an Adaptive t-distribution Educational Competition Optimization (ATD-ECO) maximum power point tracking (MPPT) algorithm is proposed. This proposed system not only reduces energy losses caused by the AC-DC conversion process compared to traditional AC power supply systems, but also has lower construction costs, enhancing both economic viability and robustness. Furthermore, the proposed ATD-ECO MPPT algorithm demonstrates excellent tracking performance in partially shaded environments, further improving the photovoltaic generation efficiency of the proposed power supply solution for 5G base stations. Through simulations and experiments conducted in MATLAB/Simulink, the photovoltaic generation efficiency of the proposed system can be enhanced by more than 67% under partially shaded conditions. To further validate the system's performance, we have established a DC experimental platform to conduct power supply experiments for the base station, and the results confirm the applicability and superiority of the proposed system.

Accurate electric vehicle (EV) charging load forecasting is essential for grid planning and resource allocation, yet existing approaches struggle with the inherent sparsity of charging data—a phenomenon characterized by excessive zeros representing periods of no charging activity. This paper addresses this challenge through a novel framework combining a Zero-Inflated Neural Network (ZINN) architecture with an Evolutionary Neural Architecture Search (ENAS) algorithm. ZINN explicitly decomposes the forecasting problem into binary classification (predicting charging occurrence) and regression (estimating energy magnitude conditioned on occurrence), enabling the model to learn distinct patterns for the absence and presence of charging events. Rather than relying on manually designed architectures, ENAS automatically discovers optimal encoder and decoder configurations from a comprehensive search space encompassing modern architectures (LSTM, GRU, Transformer, and iTransformer), layer configurations, activation functions, and hyperparameters. The evolutionary algorithm balances prediction accuracy with computational efficiency through multi-objective optimization. Extensive experiments on real-world EV charging data from 30 stations in Wuhan demonstrate that the ZINN+ENAS framework achieves the lowest prediction error compared to conventional baselines, with the discovered optimal configuration substantially outperforming hand-crafted designs. Comprehensive ablation studies reveal that the asymmetric dual-head architecture and adaptive regularization strategies are critical for handling data sparsity. These findings highlight the importance of explicit zero-inflation modeling and automated architecture discovery for specialized forecasting tasks, providing practitioners with an open-source framework for practical EV charging load prediction.

Accurate state-of-charge (SOC) estimation is crucial for the effective management of lithium-ion batteries, particularly in the face of temperature fluctuations and complex dynamic behaviors. Conventional moving horizon estimation (MHE) methods, however, often overlook the effects of temperature variations and nonlinear behaviors, such as hysteresis, limiting their accuracy and robustness under varying thermal conditions. To address these limitations, this study proposes an advanced MHE framework that integrates a battery model with temperature-dependent parameters and hysteresis effects, effectively capturing these nonlinearities within the estimation process. Furthermore, nonlinear factors are incorporated into both event-triggered recursive (ETR) optimization and Gauss-Newton (GN) iteration, supplemented by a forward-backward recursive strategy to improve the algorithm's adaptability and robustness across varying temperature conditions. Simulation results conducted at 0 degrees C, 25 degrees C, and 45 degrees C, using both the Beijing Dynamic Stress Test (BJDST) and the standard Dynamic Stress Test (DST), demonstrate that the proposed method consistently outperforms conventional MHE and other improved approaches in terms of SOC estimation accuracy and stability. Specifically, the proposed method achieves an average improvement rate of 50.7 % in RMSE and 47.56 % in MAE across all tested scenarios, highlighting its superior performance, especially under extreme temperature conditions.

This article proposes a new nonisolated high step-up dc-dc converter topology based on voltage multiplier networks, designed for renewable energy-based dc microgrids. The proposed converter features dual input ports, enabling power delivery to the output from two distinct power sources with different voltage levels, such as photovoltaic panels and fuel cells. Key advantages include a simple structure, reduced voltage stress across power switches, high voltage gain, high power efficiency, and common ground between input and output ports. Additionally, the topology exhibits low input current ripple, which is critical for maximizing the lifespan and performance of renewable energy sources. This article presents a detailed analysis of the operational modes, steady-state performance, and design procedure, along with a comprehensive design procedure and comparative study. Finally, a 200 W/ 200 V prototype is built, and experimental results are presented to confirm the effectiveness of the proposed topology.

Aiming at the problem of interpolar voltage unbalance in bipolar low voltage dc (BLVDC) microgrid, a family of bipolar dc-dc converters with interpolar voltage self-balancing is proposed in this article. The proposed converters are composed of a full bridge inverter and four types of bipolar voltage multiplier (BVM) circuits. Benefiting from the characteristics of the proposed topology, its output power can automatically flow to the output side with lower voltage and has the ability to maintain the voltage balance between BLVDC buses. In addition, the proposed converters have ZVZCS soft-switching characteristics, and the control and driving circuits are consistent with the traditional full bridge inverter. The topology derivation, working principle, soft-switching and voltage self-balancing performances of the proposed converter are analyzed, and a 1 kW experimental prototype with its control system is designed. The experimental results verify the accuracy of the theory and analysis.

The large-scale integration of wind, solar, and battery energy storage is a key feature of the new power system based on renewable energy sources. The optimization results of wind turbine (WT)–photovoltaic (PV)–battery energy storage (BES) hybrid energy systems (HESs) can influence the economic performance and stability of the electric power system (EPS). However, most existing studies have overlooked the effect of power electronic converter (PEC) efficiency on capacity configuration optimization, leading to a significant difference between theoretical optimal and actual results. This paper introduces an accurate efficiency model applicable to different types of PECs, and establishes an enhanced mathematical model along with constraint conditions for WT–PV–BES–grid–load systems, based on precise converter efficiency models. In two typical application scenarios, the capacity configurations of WT–PV–BES are optimized with optimal cost as the objective function. The different configuration results among ignoring PEC loss, using fixed PEC efficiency models, and using accurate PEC efficiency models are compared. The results show that in the DC system, the total efficiency of the system with the precise converter efficiency model is approximately 96.63%, and the cost increases by CNY 49,420, about 8.56%, compared to the system with 100% efficiency. In the AC system, the total efficiency with the precise converter efficiency model is approximately 97.64%, and the cost increases by CNY 4517, about 2.02%, compared to the system with 100% efficiency. The analysis clearly reveals that the lack of an accurate efficiency model for PECs will greatly affect the precision and effectiveness of configuration optimization.

This paper introduces a novel dual-input multi-output (DIMO) DC-DC converter for high step-up applications in renewable energy-based DC micro grids. The topology utilizes two magnetically coupled inductors whose primary windings are connected to separate input sources. Their secondary windings are integrated with voltage multiplier cells (VMCs) to achieve high voltage gain while reducing stress on semiconductor devices. The converter delivers power to three outputs: two non-isolated ports that share a common ground with the inputs, and one isolated port achieved via a high-frequency transformer (HFT). The operational principles, steady-state analysis, and efficiency are examined. A hardware prototype is developed, and both simulation and experimental results including maximum power point tracking (MPPT) performance to validate the design. The efficiency is obtained 93.21 % at rated power of 554 W.

The bipolar dc power architecture provides a new high-efficiency and high-reliability solution. Maintaining interpolar voltage balance is crucial in bipolar structures to ensure the reliable and stable operation of the system. This article proposes a family of bipolar dc-dc converters based on bipolar voltage multipliers (BVMs). Notably, the proposed BVM structure has the capacity to autonomously achieve interpolar voltage balance without external balance control strategy. This inherent feature significantly alleviates control circuit complexity. Meanwhile, the BVM structure possesses rectification functionality, facilitating its connection to various front-stage structures with ac output. This article provides a detailed exposition of the operational principles and performance analysis of the proposed voltage balancers (VBs) and discusses a 1-kW prototype experiment. The experimental results validate the accuracy of the theoretical analysis.

The eGaN HEMT power devices face serious crosstalk problems when applied to high-frequency bridge circuits, thereby limiting the switching performance of these devices. To address this issue, a gate driver is proposed in this paper that can suppress both positive and negative crosstalk of eGaN HEMT power devices, offering the advantages of simple control and easy integration. The basic idea is to suppress positive crosstalk by constructing a negative voltage capacitor, and to suppress negative crosstalk by reducing the impedance of the gate loop. To verify the capability of the proposed gate driver, double-pulse and synchronous Buck test platforms are constructed. The experimental results clearly demonstrate that the proposed gate driver reduces the positive and negative crosstalk spikes by 2.03 V and 1.54 V, respectively, ensuring that the positive and negative crosstalk spikes fall within a safe operating range. Additionally, the turn-off speed of the device is enhanced, leading to a reduction in switching loss.

This paper proposes a kilowatt-level high power flyback converter consists of basic flyback and multiple input-terminal voltage multiplier (MIVM) circuits for photovoltaic power generation systems. The proposed converter improves the transformer utilization ratio and enhances the output power level of the converter. Additionally, the proposed converter features high voltage conversion gain, which can effectively reduce the number of turns in the transformer's secondary winding in high step-up applications. An active clamp circuit is implemented to recover leakage energy, effectively suppressing the switch voltage spike during turn off and enabling zero voltage switching (ZVS), thereby further improving the efficiency of the converter. This paper provides a detailed analysis of the working principles and performance characteristics of the proposed converter. A 1 kW prototype of the proposed converter has been constructed and achieving a maximum efficiency of 97.5 %. Theoretical analysis is validated through experimental results.

High-precision photovoltaic (PV) power generation prediction models are essential for ensuring secure and stable grid operation and optimized dispatch. Existing models often ignore the significant variations in PV grid-connected inverter loss distributions and exhibit inadequate data decomposition processing, which influences the accuracy of the prediction models. This paper proposes a PSO-VMD-LSTM prediction model that includes PV converter loss characteristics. Firstly, the Particle Swarm Optimization (PSO) algorithm is employed to optimize the parameters of Variational Mode Decomposition (VMD), enabling effective decomposition of data under different weather conditions. Secondly, the decomposed sub-modes are individually fed into Long Short-Term Memory (LSTM) networks for prediction, and the results are subsequently reconstructed to obtain preliminary predictions. Finally, a neural network-based equivalent model for inverter losses is constructed; the preliminary predictions are fed into this model to obtain the final prediction results. Simulation case studies demonstrate that the proposed PSO-VMD-LSTM-based model can comprehensively consider the impact of uneven converter loss distribution and effectively improve the accuracy of PV power prediction models.

Bipolar DC microgrids gain significant attention for their flexible structure, high power supply reliability, and strong compatibility with distributed power sources. However, inter-pole voltage imbalance undermines system operational stability. An isolated bipolar bidirectional three-port converter with voltage self-balancing capability is proposed in this paper, which can serve as the interface between the energy storage system and bipolar bus while achieving automatic voltage balance between poles. Unlike traditional bidirectional grid-connected voltage balancers (VBs), the proposed converter requires no additional voltage monitoring or complex control systems. The operating modes, soft-switching boundary conditions, and inter-pole voltage self-balancing mechanism are elaborated. A 1 kW experimental prototype has been built to validate the theoretical analysis of the proposed converter.

This paper focus on the modeling and time-domain analyzing method of piecewise-smooth fractional-order circuit systems. Firstly, an analytical framework is constructed based on a generalized piecewise-smooth two-port impedance network model, which takes the topological characteristics of Dickson type switched-capacitor converters (SCCs) as examples, and considers the fractional-order characteristics of class-2 X7R ceramic capacitors, which are widely used in SCCs. Secondly, the time-domain analyzing method for such a piecewise-smooth fractional-order circuit system is developed, numerical solutions are obtained, and the influence of the fractional-order capacitor on the power conversion efficiency of the system are revealed. Finally, in order to validate the analysis, both numerical simulation and experiments are provided in the work, the results of which confirm that, the proposed fractional-order analytical framework can capture the power loss mechanism of piecewise-smooth fractional-order circuit systems more effectively than the traditional integer-order based approach, thus benefiting the design of circuit systems.

GaN high electron mobility transistors (HEMTs) have been widely used due to their high withstand voltage characteristic and low parasitic parameters. However, these devices always face power losses caused by electron trapping effects, which perform in the form of the on-resistance of the devices. In this work, a fractional-order equivalent model is proposed for characterizing the dynamic on-resistance of GaN HEMTs, in which a fractional-order capacitor is introduced to describe the long-tailed distribution of time constants of electron detrapping effects. A cuckoo search algorithm-based parameter identification scheme is developed for extracting the parameters of the proposed model. The comparison between the prediction of the proposed model and experiments shows that, the dynamic on-resistance of GaN HEMTs can be characterized concisely and effectively.

In order to address the energy imbalance issue of a series-connected lithium-iron battery pack, this paper proposes an active equalization method based on a reduced-order solving strategy for the Hanoi Tower problem. The proposed scheme utilizes a combined structure of a switching-network circuit and a bidirectional Cuk converter and leverages an ultracapacitor cell as the energy-transfer carrier. Simulation and comparison demonstrate that the exchange of unbalanced energy within the battery pack can be achieved. The proposed approach can effectively achieve various balancing modes such as cell-to-cell, cell-to-string, string-to-cell, and string-to-string with a relatively fast balancing speed.

Deploying energy storage systems (ESSs) is an effective way to maintain the reliability and robustness of power systems with renewable energy sources (RESs). This paper proposes a battery-ultracapacitor (UC) hybrid energy storage system (HESS) based on a bidirectional hybrid Z-source converter, which can be applied to mitigate the impact of dynamic power fluctuations and prolong the service life of battery cells. Compared with the conventional non-isolated bi-directional converters that have been used as the power interfacing circuit of energy storage systems, such as bi-directional dc-dc boost converter, Z-source converter, quasi-Z-source converter, and hybrid switched capacitor/quasi-Z-source converter, the outstanding advantage of this scheme lies in its relatively high voltage conversion ratio in bidirectional energy flows. This characteristic is beneficial to reducing the cost and size of ESSs, because the energy-storage components with a smaller rated voltage can be employed in the design. The detailed operation mode derivation of the proposed hybrid Z-source based HESS (HZS-HESS) is presented in the work along with characteristic analysis and energy-management strategy design. Two test scenarios of short-term power fluctuations are conducted for the proposed HZS-HESS. The simulation and comparison results show the effectiveness and superiority of the proposed scheme. In addition, an experiment prototype is developed to validate the characteristics and the analysis of the proposed scheme.