Search Results (3,704)

Maritime power systems must reduce fuel use and emissions while improving resilience. We study a shipboard PV–battery subsystem interfaced with a DC–DC converter running maximum power point tracking (MPPT) and curve-scanning GMPPT to manage partial shading. Dynamic average-value models capture irradiance steps and show GMPPT sustains operation near the global MPP without local peak trapping. We compare converter options—conventional single-port stages, high-gain bidirectional dual-PWM converters, and three-level three-port topologies—provide sizing rules for passives, and note soft-switching in order to limit loss. A Fourier framework links the switching ripple to power quality metrics: as irradiance falls, the current THD rises while the PCC voltage distortion remains constant on a stiff bus. We make the loss relation explicit via \({{I}_{rms}^{2}R}\) scaling with THDi and propose a simple reactive power policy, assigning VAR ranges to active power bins. For AC-coupled cases, a hybrid EMT plus transient stability workflow estimates ride-through margins and critical clearing times, providing a practical path from modeling to monitoring. Full article

This article presents the development and implementation of an IoT-enabled, off-grid solar power supply prototype designed to power a range of electrical devices. The developed system comprises a Photovoltaic panel, a Maximum Power Point Tracking (MPPT) charger, a 2.5 kWh/24 V high-performance LiFePO4 battery bank with a Battery Management System, an embedded controller with IoT connectivity, and DC/DC and DC/AC converters. The PV panel serves as the primary energy source, with the MPPT controller optimizing battery charging, while the DC/DC and DC/AC converters supply power to the connected electrical devices. The article includes a case study of a developed platform for powering an information and advertising system. The system features a predictive energy management algorithm, which optimizes the appliance operation based on daily solar irradiance forecasts and real-time battery State-of-Charge monitoring. The IoT-enabled controller obtains solar irradiance forecasts from an online meteorological service via API calls and uses these data to estimate energy availability for the next day. Using this prediction, the system schedules and prioritizes the operations of connected electrical devices dynamically to optimize the performance and prevent critical battery discharge. The IoT-based controller is equipped with both Wi-Fi and an LTE modem, enabling communication with online services via wireless or cellular networks. Full article

This paper presents a three-phase powerline energy harvesting circuit with doubly regulated output voltages to power wireless sensors for the monitoring of railroad powerline status. Three ring-shaped silicon steel cores coupled to the three phases of a powerline convert the line current into three-phase voltages, which are applied to an energy harvesting circuit. The key parts of the circuit are a series three-phase voltage rectifier, a buck–boost converter operating in discontinuous conduction mode (DCM), and a microcontroller unit (MCU) for maximum power point tracking (MPPT). The MCU performs two-step MPPT, coarse and fine, for impedance matching based on the perturb and observe method. Two parallel voltage regulators deliver 5 V and 5.7 V regulated DC voltages to power a radio and a set of sensors, respectively. The energy harvesting circuit is prototyped using commercial-off-the-shelf (COTS) components on an FR4 PCB. The measured maximum efficiency is 84% for the three-phase voltage rectifier and 89% for the buck–boost converter under the powerline current ranging from 5 A to 20 A. Full article

This study presents the development of a buck–boost converter for application in unmanned guided vehicles (UGVs). The converter was designed with its input connected to a lithium iron phosphate battery pack and its output connected to an inverter. This configuration enabled the inverter, which powered the drive motor, to receive a stable DC voltage, thereby mitigating the effects of battery voltage fluctuations and enhancing the overall system stability. A pulse-width modulation (PWM) controller was employed to regulate the developed buck–boost converter. During the transition from buck mode to buck–boost mode, both power MOSFETs were simultaneously turned on; however, the datasheet of the PWM controller did not provide operational details or characteristic curve analysis for this mode. Therefore, this study derived the relationship between voltage gain and duty cycle ratio for the transition mode. To analyze the input voltage versus duty cycle characteristics, the linear equation was employed. This analytical model was adjusted to meet different converter specifications developed for experimental validation. Furthermore, the external-connect test capacitor method was used to extract the equivalent parasitic inductance and capacitance present in the practical circuit of the buck–boost converter. Based on these parameters, a snubber circuit was designed and connected across the drain–source terminals of the power MOSFETs to suppress voltage spikes occurring at the junctions. Finally, the developed buck–boost converter prototype was installed on an unmanned guided vehicle to convert the power from the lithium battery pack into the input power required by two inverters. A computer host was used to control the motor speed. By measuring the output voltage and current of the buck–boost converter, its electrical functionality and performance specifications were verified. The dimensions of the developed UGV chassis prototype were 40 cm in length, 45 cm in width, and 18.3 cm in height. Full article

The widespread adoption of electric vehicles (EVs) is contingent on high-power fast-charging infrastructure that can also provide grid stabilization services through bidirectional power flow. While the constituent power stages of such off-board chargers are well-known, a critical research gap exists in their system-level integration, where sub-optimal dynamic interaction between independently controlled stages often leads to DC-link instability and poor transient performance. This paper presents a rigorous, system-level study to address this gap by developing and optimizing a unified control framework for a high-power bidirectional EV fast-charging system. The system integrates a three-phase active front-end rectifier with an LCL filter and a four-phase interleaved bidirectional DC/DC converter. The methodology involves a holistic dynamic modeling of the coupled system, the design of a hierarchical control strategy augmented with a battery current feedforward scheme, and the system-wide optimization of all Proportional–Integral (PI) controller gains using the Artificial Bee Colony (ABC) algorithm. Comprehensive simulation results demonstrate that the proposed optimized control framework achieves a critically damped response, significantly outperforming a conventionally tuned baseline. Specifically, it reduces the DC-link voltage settling time during charging-to-discharging transitions by 74% (from 920 ms to 238 ms) and eliminates voltage undershoot, while maintaining excellent steady-state performance with grid current total harmonic distortion below 1.2%. The study concludes that system-wide metaheuristic optimization, rather than isolated component-level design, is key to unlocking the robust, high-performance operation required for next-generation EV fast-charging infrastructure, providing a validated blueprint for future industrial development. Full article

In this article, an approach to balance the State of Charge (SoC) of two batteries connected to the DC bus of a fuel cell (FC) electric aircraft by Droop-controlled converters is described. The proposed algorithm is based on shifting the Droop reference voltages and prevents the simultaneous charging and discharging of the batteries. This approach is not only practical but also highly versatile, as it is compatible with all converters as long as the Droop voltage can be changed remotely, and a current measurement is provided to a central controller. No further programming access to the DC/DCs is necessary. There is no need for nonlinear or different-valued Droop resistances for charging and discharging. The balancing approach is validated via simulation in MATLAB/Simulink 2024a.The results show that the proposed approach achieves SoC balancing without degrading the dynamic performance of the grid. The delays added by the slower communication with the central controller have a minimal impact on performance. Full article

This paper investigates the feasibility of vehicle-integrated photovoltaic (VIPV) systems for light vehicles by developing and simulating an intelligent solar integration design based on the Tesla Model 3. The proposed system incorporates roof and bonnet-mounted photovoltaic modules, each managed by independent buck converters employing maximum power point tracking (MPPT) for optimal energy extraction. A novel fuzzy logic controller was designed to dynamically allocate auxiliary battery charging between the traction battery and the solar subsystem, using real-time irradiance and state-of-charge (SOC) inputs. The system was implemented in MATLAB/Simulink with location-specific data for Melbourne, Australia. Simulation results demonstrate high converter efficiencies of 94–95%, stable MPPT convergence within 0.5 s and an estimated annual solar contribution of 930 kWh, confirming effective control and energy management under varying conditions. This work highlights the innovative application of adaptive fuzzy control and dual MPPT coordination within VIPV systems and provides a validated basis for future optimisation and real-world integration. Full article

This paper presents a robust and reliable voltage regulation method in DC–DC converters, for which a multiloop control strategy is developed and analyzed for a boost converter. The proposed control scheme consists of an inner current loop and an outer voltage loop, both systematically designed using the control Lyapunov function (CLF) methodology. The main contributions of this work are (1) the formulation of a control structure capable of maintaining performance under variations in load, reference voltage, and input voltage; (2) the theoretical demonstration of global asymptotic stability of the closed-loop system in the Lyapunov sense; and (3) the experimental validation of the proposed controller on a physical DC–DC boost converter, confirming its effectiveness. The results support the advancement of high-efficiency nonlinear control methods for power electronics applications. Furthermore, the experimental findings reinforce the practical relevance and real-world applicability of the proposed approach. Full article

This paper presents an innovative approach to the modeling and dynamic analysis of DC–DC converters in photovoltaic applications. Departing from traditional studies that focus on the transfer function from duty cycle to output voltage, this work investigates the duty cycle to input voltage transfer function, which is critical for accurate dynamic representation of photovoltaic systems. A notable contribution of this study is the integration of the PV panel behavior in the small-signal representation, considering a model-derived differential resistance for various operating points. This technique enhances the model’s accuracy across different operating regions. The paper also validates the effectiveness of this linearization method through small-signal analysis. A comprehensive comparison is conducted among several non-isolated converter topologies such as Boost, Buck–Boost, Ćuk, and SEPIC under both open-loop and closed-loop conditions. To ensure fairness, all converters are designed using a consistent set of constraints, and controllers are tuned to maintain similar phase margins and crossover frequencies across topologies. In addition, a gain-scheduling control strategy is implemented for the Boost converter, where the PI gains are dynamically adapted as a function of the PV operating point. This approach demonstrates superior closed-loop performance compared to a fixed controller tuned only at the maximum power point, further highlighting the benefits of the proposed modeling and control framework. This systematic study therefore provides an objective evaluation of dynamic performance and offers valuable insights into optimal converter architectures and advanced control strategies for photovoltaic systems. Full article

The objective of this work was to study the possibility of upgrading the control system of the drum shear mechanism by using neural network PI controllers to improve the efficiency of the sheet-metal cutting process. The developed detailed model of the mechanism, including a dual DC electric drive with three subordinate control loops for the voltage of the thyristor converter, current and speed of the motors, a 6-mass kinematic system with viscoelastic connections as well as a model of the metal cutting process, made it possible to uncover that the interaction of electric drives with the mechanical part leads to significant speed fluctuations during the cutting process, which worsens the quality of the sheet-metal edge. A modified system of current and speed controllers with built-in three-layer fitting neural networks as nonlinear components of proportional-integral channels is proposed. An algorithm for the fast learning of neural controllers using the gradient descent method in each cycle of calculating the controller signal is also proposed. The developed neuro-regulators make it possible to reduce the amplitude of speed fluctuations during the cutting process by four times, ensuring the effective damping of oscillations and reducing the duration of transient processes to 0.1 s. Full article

In order to reduce magnetic components for a current-fed dual active bridge converter, this paper proposes a dual coupled-inductor (DCI) structure, which integrates two DC inductors, one high-frequency transformer, and one leakage inductor into two EE cores. By analyzing the principle of the magnetic components, a derivation process is presented to modify the current-fed dual active bridge converter. To simplify the design and enhance efficiency, an equal air gap length optimization method is proposed. And the geometric parameters with the highest efficiency are optimized based on losses. Finally, the feasibility and effectiveness of the above design were verified through a 1 kW test prototype. Full article

This work presents the development and experimental validation of a low-cost, piezoelectret-based energy harvesting system integrated into a custom insole, as a promising alternative for future self-powered wearable electronics. The design utilizes eight thermoformed Teflon piezoelectrets, strategically positioned in high-impact regions (heel and forefoot), to convert footstep-induced mechanical motion into electrical energy. The sensors, fabricated using Fluorinated Ethylene Propylene (FEP) and Polytetrafluoroethylene (PTFE) layers via thermal pressing and aluminum sputtering, were connected in parallel to enhance signal consistency and robustness. A solenoid-actuated mechanical test rig was developed to simulate human gait under controlled conditions. The system consistently produced voltage pulses with peaks up to 13 V and durations exceeding ms, even under limited-force loading (10 kgf). Signal analysis confirmed repeatable waveform characteristics, and a Delon voltage multiplier enabled partial conversion into usable DC output. While not yet optimized for maximum efficiency, the proposed setup demonstrates the feasibility of using piezoelectrets for energy harvesting. Its simplicity, scalability, and low cost support its potential for future integration in applications such as fitness tracking, health monitoring, and GPS ultimately contributing to the development of autonomous, self-powered smart footwear systems. It is important to emphasize that the present study is a proof-of-concept validated exclusively under controlled laboratory conditions using a mechanical gait simulator. Future work will address real-time insole application tests with human participants. Full article

Voltage stability in DC microgrids (DC MG) is crucial for ensuring reliable operation and component safety. This paper surveys voltage control techniques for DC MG, classifying them into model-based, model-free, and hybrid approaches. It analyzes their fundamental principles and evaluates their strengths and limitations. In addition to the survey, the study investigates the voltage control problem in a critical scenario involving a DC/DC buck converter with an input LC filter. Two model-free deep reinforcement learning (DRL) control strategies are proposed: twin-delayed deep deterministic policy gradient (TD3) and proximal policy optimization (PPO) agents. Bayesian optimization (BO) is employed to enhance the performance of the agents by tuning their critical hyperparameters. Simulation results demonstrate the effectiveness of the DRL-based approaches: compared to benchmark methods, BO-TD3 achieves the lowest error metrics, reducing root mean square error (RMSE) by up to 5.6%, and mean absolute percentage error (MAPE) by 7.8%. Lastly, the study outlines future research directions for DRL-based voltage control aimed at improving voltage stability in DC MG. Full article

Lift–cruise-type unmanned aerial vehicles (UAVs) powered by hydrogen fuel cells often integrate secondary energy storage devices to improve responsiveness to load fluctuations during different flight phases, which necessitates an efficient energy management strategy that optimizes power allocation among multiple power sources. This paper presents an innovative fuel cell DC–DC converter (FDC) design for the hybrid power system of a lift–cruise-type UAV comprising a multi-stack fuel cell system and a battery. The novelty of this work lies in the development of an FDC suitable for a multi-stack fuel cell system through a dual-input single-output converter structure and a control algorithm. To integrate inputs supplied from two hydrogen fuel cell stacks into a single output, a controller with a single voltage controller–dual current controller structure was applied, and its performance was verified through simulations and experiments. Load balancing was maintained even under input asymmetry, and fault-tolerant performance was evaluated by analyzing the FDC output waveform under a simulated single-stack input failure. Furthermore, under the assumed flight scenarios, the results demonstrate that stable and efficient power supply is achieved through power-supply mode switching and application of a power distribution algorithm. Full article

This paper presents a new robust control strategy for buck DC–DC converters that achieve fast and robust voltage regulation in the presence of load disturbances and model uncertainties. First, an adaptive state observer is designed to estimate the inductor current and capacitor voltage by utilizing the output measurement. The observer gains are tuned online via a Lyapunov-based adaptation law, ensuring that the estimation error remains uniformly bounded, even when the disturbances act on the system. Based on the state estimates, an integral sliding-mode controller is designed in order to eliminate the steady state error and ensure the finite time sliding. The detailed stability proofs for both the observer and the sliding-mode controller are derived showing the finite-time reaching of the sliding surface and exponential convergence of the voltage error. Simulation results under varying load profiles confirm that the proposed scheme outperforms traditional sliding-mode designs in terms of disturbance rejection and settling time, while avoiding excessive chattering. Full article