Search Results (391)

This paper presents a novel open-loop modulation and control strategy for bidirectional, multi-source/load parallel AC-link power converters. While these converters offer advantages such as high-frequency operation and flexible power conversion capabilities, their application to complex systems such as nanogrids presents significant control challenges. Traditional control methods often struggle to efficiently manage power flow and charging/discharging processes, especially when dealing with multiple sources and loads of varying characteristics. To address these issues, this paper proposes a new control strategy that enables intelligent source and load selection while maintaining fast charging and discharging times. Simulation results demonstrate the effectiveness of the proposed approach. This research contributes to advancing the state-of-the-art in power electronics by providing a foundation for improved control of complex power conversion systems for renewable energy applications. Full article

In the event of power outages caused by natural disasters, accidents, or other emergencies, outdoor emergency lighting systems play a critical role in providing illumination to maintain spatial orientation, facilitate evacuation procedures, and help individuals avoid hazardous areas or locate safe shelters. Compared to traditional lighting technologies, LED-based outdoor emergency lighting offers several advantages, including compact size, long operational lifespan, low energy consumption, high safety, resistance to breakage, and the absence of chemical residue or pollution. These characteristics align with contemporary trends in environmental sustainability and energy efficiency. This study proposes a novel LED driver circuit architecture for outdoor emergency lighting applications. The primary circuit topology is based on an improved buck-boost converter integrated with a flyback converter, forming a hybrid buck-boost-flyback configuration. The proposed circuit is capable of recycling the energy stored in the transformer’s leakage inductance, thereby enhancing overall power conversion efficiency. A 12 W (20 V/0.6 A) prototype LED driver circuit was designed and implemented to validate the performance of the proposed system. Experimental measurements, including waveform analysis and efficiency evaluation, demonstrate that the driver circuit achieves a high efficiency exceeding 91%. These results confirm the practical feasibility and effectiveness of the proposed electronic driver for LED-based outdoor emergency lighting applications. Full article

This paper presents an enhanced operation strategy for a recently proposed converter called Modified Non-Inverting Step-Down/Up (MNI-SDU) DC-DC converter intended for battery voltage regulation. Unlike the conventional approach, where both switching stages share a single duty cycle, the proposed method controls asynchronously the two duty cycles through a fixed time offset to optimize performance. A methodology is developed to define suitable duty cycle ranges that ensure proper converter operation according to input/output voltage specifications, while simultaneously reducing the current and voltage ripples and electrical stress in the capacitor and semiconductors. Furthermore, a model-based control strategy is proposed, taking into account the enhanced operational characteristics. Consequently, a PI-PI current-mode controller is designed using loop shaping techniques to maintain the output voltage regulated at the desired level. The proposed approach is analyzed mathematically and validated through experimental results. The findings demonstrate that optimizing through asynchronous duty-cycle control with a fixed time offset improves ripple, stress values, and overall efficiency, while maintaining robust output voltage regulation, making this method well-suited for applications requiring compact and reliable power conversion. Full article

Power converters play an important role in incorporating renewable energy sources into power systems. Among different converter designs, Buck and Boost converters are popular, as they use fewer components and deliver cost savings and high efficiency. However, Boost converters are known as non–minimum phase systems, imposing harder constraints for designing a robust converter. Developing an efficient controller for these topologies can be difficult since they exhibit nonlinearity and distortion in high frequency modes. The Lyapunov-based Adaptive Backstepping Control (ABSC) technology is used to regulate suitable outputs for these structures. This approach is an updated version of the technique that uses the stability Lyapunov function to produce increased stability and resistance to fluctuations in real-world circumstances. However, in real-time situations, disturbances with larger ranges such as supply voltage changes, parameter variations, and noise may have a negative impact on the operation of this strategy. To increase the controller’s flexibility under more difficult working settings, the most appropriate first gains must be established. To solve these concerns, the ABSC’s performance is optimized using the Reinforcement Learning (RL) adaptive technique. RL has several advantages, including lower susceptibility to error, more trustworthy findings obtained from data gathering from the environment, perfect model behavior within a certain context, and better frequency matching in real-time applications. Random exploration, on the other hand, can have disastrous effects and produce unexpected results in real-world situations. As a result, we choose the Deep Deterministic Policy Gradient (DDPG) approach, which uses a deterministic action function rather than a stochastic one. Its key advantages include effective handling of continuous action spaces, improved sample efficiency through off-policy learning, and faster convergence via its actor–critic architecture that balances value estimation and policy optimization. Furthermore, this technique uses the Grey Wolf Optimization (GWO) algorithm to improve the initial set of gains, resulting in more reliable outcomes and quicker dynamics. The GWO technique is notable for its disciplined and nature-inspired approach, which leads to faster decision-making and greater accuracy than other optimization methods. This method considers the system as a black box without its exact mathematical modeling, leading to lower complexity and computational burden. The effectiveness of this strategy is tested in both modeling and experimental scenarios utilizing the Hardware-In-Loop (HIL) framework, with considerable results and decreased error sensitivity. Full article

The integration of Internet of Things (IoT) technologies into islanded microgrids has increased their vulnerability to cyberattacks, particularly those targeting critical components such as power converters within an islanded AC microgrid. This study investigates the impact of False Data Injection (FDI) and Denial of Service (DoS) attacks on various power converters, including DC–DC boost converters, DC–AC converters, battery inverters, and DC–DC buck–boost converters, modeled in MATLAB/Simulink. A dataset of healthy and compromised operational parameters, including voltage and current, was generated under simulated attack conditions. To enhance system resilience, a deep learning-based detection and classification framework was proposed. After evaluating various deep learning models, including Deep Neural Networks (DNNs), Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Long Short-Term Memory (LSTM), and Feedforward Neural Networks (FNNs), the final system integrates an FNN for rapid attack detection and an LSTM model for accurate classification. Real-time simulation validation demonstrated a detection accuracy of 95% and a classification accuracy of 92%, with minimal computational overhead and fast response times. These findings emphasize the importance of implementing intelligent and efficient cybersecurity measures to ensure the secure and reliable operation of islanded microgrids against evolving cyberattacks. Full article

Three-level non-inverting buck–boost converters are promising for electric vehicle charging stations due to their wide voltage regulation capability and bidirectional power flow. However, the number of three-level operating states is four times that of two-level operating states, and the lack of a unified switching state selection mechanism leads to serious challenges in its application. To address these issues, a finite control set model predictive control (FCS-MPC) strategy is proposed, which can determine the optimal set and select the best switching state from the excessive number of states. Not only does the proposed method achieve fast regulation over a wide voltage range, but it also maintains the input- and output-side capacitor voltage balance simultaneously. A further key advantage is that the number of switching actions in adjacent cycles is minimized. Finally, a hardware-in-the-loop experimental platform is built, and the proposed control method can realize smooth transitions between multiple operation modes without the need for detecting modes. In addition, the state polling range and the number of switching actions are superior to conventional predictive control, which provides an effective solution for high-performance multilevel converter control in energy systems. Full article

To address the issues of DC-side voltage fluctuation and three-phase current distortion in rectifier systems under pulsed load conditions, this paper proposes a control strategy that integrates Model Predictive Control (MPC) with a Luenberger observer for the Power Pulsation Buffer (PPB). The observer parameters are adaptively tuned using a gradient descent method. First, the pulsed current generated by the load is decomposed into dynamic and average components, and a mathematical model of the PPB is established. Considering the negative impact of DC voltage ripple and lumped disturbances such as parasitic parameters on model accuracy, a Luenberger observer is designed to estimate these disturbances. To overcome the dependence of traditional Luenberger observers on empirically tuned gains, an adaptive gradient descent algorithm based on gradient direction consistency is introduced for online gain adjustment. Simulation and experimental results demonstrate that the proposed control strategy—combining the Luenberger observer with gradient descent and MPC—effectively reduces current tracking overshoot and improves tracking accuracy. Furthermore, it enables sustained decoupling of the PPB from the system, significantly mitigating DC-side voltage ripple and three-phase current distortion under pulsed load conditions, thereby validating the effectiveness of the proposed approach. Full article

This paper presents an advanced energy management system (EMS) for optimizing power distribution in a battery/ultracapacitor (UC) hybrid energy storage system (HESS) for electric vehicles (EVs). The proposed EMS accounts for all energy flow scenarios within a practical driving cycle. A regenerative braking control strategy is developed to maximize kinetic energy recovery using an induction motor, efficiently distributing the recovered energy between the UC and battery. Additionally, a power flow management approach is introduced for both motoring (discharge) and braking (charge) operations via bidirectional buck–boost DC-DC converters. In discharge mode, an optimal distribution factor is dynamically adjusted to balance power delivery between the battery and UC, maximizing efficiency. During charging, a DC link voltage control mechanism prioritizes UC charging over the battery, reducing stress and enhancing energy recovery efficiency. The proposed EMS is validated through simulations and experiments, demonstrating significant improvements in vehicle acceleration, energy efficiency, and battery lifespan. Full article

Dual-active bridge (DAB) converters have emerged as a preferred topology in electric vehicle charging and energy storage applications, owing to their structurally symmetric configuration and intrinsic galvanic isolation capabilities. However, conventional triple-phase shift (TPS) control strategies face significant challenges in maintaining high efficiency across ultra-wide output voltage and load ranges. To exploit the inherent structural symmetry of the DAB topology, a symmetric optimization strategy based on triple-phase shift (SOS-TPS) is proposed. The method specifically targets the forward buck operating mode, where an optimization framework is established to minimize the root mean square (RMS) current of the inductor, thereby addressing both switching and conduction losses. The formulation explicitly incorporates zero-voltage switching (ZVS) constraints and operating mode conditions. By employing the Karush–Kuhn–Tucker (KKT) conditions in conjunction with the Lagrange multiplier method (LMM), the refined control trajectories corresponding to various power levels are analytically derived, enabling efficient modulation across the entire operating range. In the medium-power region, full-switch ZVS is inherently satisfied. In the low-power operation, full-switch ZVS is achieved by introducing a modulation factor λ, and a selection principle for λ is established. For high-power operation, the strategy transitions to a conventional single-phase shift (SPS) modulation. Furthermore, by exploiting the inherent symmetry of the DAB topology, the proposed method reveals the symmetric property of modulation control. The modulation strategy for the forward boost mode can be efficiently derived through a duty cycle and voltage gain mapping, eliminating the need for re-derivation. To validate the effectiveness of the proposed SOS-TPS strategy, a 2.3 kW experimental prototype was developed. The measured results demonstrate that the method ensures ZVS for all switches under the full load range, supports ultra-wide voltage conversion capability, substantially suppresses RMS current, and achieves a maximum efficiency of 97.3%. Full article

The research demonstrates, through simulation and laboratory validation, the development of a low-voltage DC-link (LVDC) back-to-back converter system that enables multi-frequency power transfer. The system operates in two distinct modes, which include a three-phase grid-connected converter transferring fundamental and 5th and 7th harmonic power to a three-phase residential inverter supplying a clean 50 Hz load and another mode that uses a DC–DC buck–boost converter to integrate a battery storage unit for single-phase load supply. The system allows independent control of each harmonic component and maintains a clean sinusoidal voltage at the load side through DC-link isolation. The LVDC link functions as a frequency-selective barrier to suppress non-standard harmonic signals on the load side, effectively isolating the multi-frequency power grid from standard-frequency household loads. The proposed solution fills the gap between the multi-frequency power systems and the single-frequency loads because it allows the transfer of total multi-frequency grid power to the traditional household loads with pure fundamental frequency. Experimental results and simulation outcomes demonstrate that the system achieves high efficiency, robust harmonic isolation, and dynamic adaptability when load conditions change. Full article

The dual-active-bridge (DAB) converter has emerged as a promising topology for renewable energy applications and microgrid systems due to its high power density and bidirectional energy-transfer capability. Enhancing the overall efficiency and reliability of DAB converters requires the simultaneous realization of zero-voltage switching (ZVS) across all switches and the minimization of current stress over wide load and voltage ranges—two objectives that are often in conflict. Conventional modulation strategies with limited degrees of freedom fail to meet these dual goals effectively. To address this challenge, this paper introduces an enhanced integrated optimization strategy based on triple phase shift (EIOS-TPS). This approach formulates the power transmission requirement as an equality constraint and incorporates ZVS and mode boundary conditions as inequalities, resulting in a comprehensive optimization framework. Optimal phase-shift parameters are obtained using the Karush–Kuhn–Tucker (KKT) conditions. To mitigate zero-current switching (ZCS) under a light load and achieve full-range ZVS with reduced current stress, a modulation factor λ is introduced, enabling a globally optimized control trajectory. An experimental 1176 W prototype is developed to validate the proposed method, which achieves full-range ZVS while maintaining low current stress. In the low-power region, it improves efficiency by up to 2.2% in buck mode and 2.0% in boost mode compared with traditional control strategies, reaching a peak efficiency of 96.5%. Full article

The four-switch buck–boost (FSBB) converter, which possesses both step-up and step-down capabilities, is highly suitable for applications where input and output voltages have overlapping ranges. Correspondingly, the current shaping control (CSC) strategy is investigated for the FSBB converter, which shapes a quadrilateral inductor current waveform featuring the minimum RMS value to improve efficiency and power density. However, the small-signal model for the CSC algorithm has not yet been established, and the traditional and common modeling method requires considering multiple duty cycles and phase shifts of the FSBB converter, whose calculation is complex and inconvenient to use. For the special case of the CSC strategy using cycle-by-cycle current detection, an additional constraint of the averaged volt-second on the inductor can be regarded as zero, making the inductor current no longer a variable of the state-space, which eliminates the pole generated by the inductor and reduces the order of the small-signal model. Thus, this paper greatly simplifies the computation and design of the compensator by using the constraint condition mentioned above. This one-pole first-order model is simplified, maintains enough accuracy in the low-frequency domain, and can be corrected using only a simple PI controller. Finally, a prototype of the 300 W FSBB converter under the digital CSC algorithm was built to validate the precision and dynamic performance of the proposed first-order small-signal model. Full article

This paper introduces a non-isolated ultra-high voltage gain topology using the combination of the coupled-inductor-based inverting buck-boost converter (IBB) and voltage multiplier (VM) structure. In the proposed converter, an ultra-high step-up voltage gain can be achieved with a small duty cycle thanks to a coupled inductor and VMs. The voltage stress and the losses of the switches in the proposed converter are even less than other conventional topologies. Unlike other coupled-inductor topologies, a large voltage spike caused by the leakage inductance of the coupled inductor is smoothed by the capacitor in the voltage multiplier. In addition, zero-voltage switching (ZVS) turn-on for the switches and zero-current switching (ZCS) turn-off for the diodes can be achieved with the energy stored in the leakage inductance. A 360 W (40 V/380 V) prototype converter is implemented to prove the advantages of the proposed converter, with a maximum efficiency of 98.4%. Full article

This paper proposes a high-reliability power conversion system optimized for Urban Air Mobility (UAM) applications, which utilizes silicon carbide (SiC) chopper modules within a hybrid fuel cell and battery structure. The system features a redundant power configuration that employs both a main and an auxiliary battery to ensure continuous and stable power supply, even under emergency or fault conditions. By integrating SiC-based power converters, the proposed system achieves high efficiency, low switching losses, and enhanced thermal performance, which are crucial for the space- and weight-constrained environment of UAM platforms. Furthermore, a robust control strategy is implemented to enable smooth transitions between multiple power sources, maintaining operational stability and safety. System-level simulations were conducted using PowerSIM to validate the performance and reliability of the proposed architecture. The results demonstrate its effectiveness, making it a strong candidate for future UAM power systems requiring lightweight, efficient, and fault-tolerant power solutions. Full article

Low-Voltage DC-DC converters (LDCs) in electric vehicles require high power density and high efficiency operation over the wide range of load and input voltage variations. This paper introduces a novel topology which combines three 1 MHz half-bridge (HB) LLC resonant converters and an inverting buck–boost (IBB) converter to adjust the output voltage without frequency modulation. The switching frequency of the proposed converter is fixed at 1 MHz to achieve a constant frequency operation for the resonant converter. In the proposed topology, Gallium Nitride (GaN) devices and planar transformers are employed to optimize the converter operation at high frequency. A 1-MHz/1.8 kW-400/14 V prototype converter is built to verify the feasibility and the validity of the proposed LDC topology. Full article