Search Results (669)

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

This work investigates the application of artificial intelligence techniques for optimizing photovoltaic systems using maximum power point tracking (MPPT) algorithms. Simulation models were developed in MATLAB/Simulink (Version 2024), incorporating conventional and intelligent control strategies such as fuzzy logic, genetic algorithms, neural networks, and Deep Reinforcement Learning. A DC/DC buck converter was designed and tested under various irradiance and temperature profiles, including scenarios with partial shading conditions. The performance of the implemented MPPT algorithms was evaluated using such metrics as Mean Absolute Error (MAE), Integral Absolute Error (IAE), mean squared error (MSE), Integral Squared Error (ISE), efficiency, and convergence time. The results highlight that AI-based methods, particularly neural networks and Deep Q-Network agents, outperform traditional approaches, especially in non-uniform operating conditions. These findings demonstrate the potential of intelligent controllers to enhance the energy harvesting capability of photovoltaic 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

Considering the challenges posed by traditional continuous control set model predictive control (CCS-MPC) calculations, this paper proposes an event-triggered-based model predictive control (ET-MPC). First, a novel tracking error state-space model is proposed to improve tracking performance. Second, a reduced-order extended state observer (RESO) is designed to estimate and compensate for the total disturbances, thereby effectively improving robustness against the variations of the load resistance and reference voltage. At the same time, RESO significantly reduces computational complexity and accelerates the convergence speed of state estimation. Subsequently, an event trigger mechanism is introduced to enhance the MPC with a threshold function for the converter status. Finally, the reduced-order extended state observer-based model predictive control (RESO-MPC) is compared with the proposed ET-MPC through experiments. The ripple voltage of ET-MPC is within 2%, and the computational burden is reduced by more than 57%, verifying the effectiveness of the proposed ET-MPC. 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 optimal design of electromagnetic interference (EMI) filters relies on accurate characterization of noise source impedance. The conventional insertion loss method involves integrating two distinct passive two-port networks between the linear impedance stabilization network (LISN) and the equipment under test (EUT). The utilization of the insertion loss to formulate a system of binary quadratic equations concerning the real and imaginary components of the impedance of the noise source enables the precise extraction of the magnitude and phase of the noise source impedance in theory. However, inherent inaccuracies in the insertion loss method during extraction can compromise impedance accuracy or even cause extraction failure. This work employs a series inductance method to overcome these limitations. Exact analytical expressions are derived for the magnitude and phase of the noise source impedance. Subsequently, the application scope of the series insertion loss method is analyzed, and the impact of insertion loss measurement error on noise source impedance extraction accuracy is quantified. Requirements for improving extraction accuracy are discussed, and method optimization strategies are proposed. The permissible range of insertion loss error ensuring a solution exists is deduced. Finally, simulation and experimental results validate the proposed approach in a buck converter. 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

In this research, a step-down converter with a lossless snubber is proposed, and its output is floating; therefore, it can be applied to LED driving applications. Such a structure is a modification of the conventional buck converter by adding a resonant capacitor, a resonant inductor, and two diodes to form this lossless snubber to reduce the switching loss during the switching period. Although the efficiency improvement in this circuit is not as good as the existing soft switching circuits, this circuit has the advantages of simple structure, easy control, and zero voltage switching (ZVS) cutoff. Full article

Power converters in the smart grid systems are essential to link renewable energy sources with all grid appliances and equipment. However, this raises the possibility of electromagnetic interference (EMI) between the smart grid elements. Hence, spread spectrum (SS) modulation techniques have been used to mitigate the EMI peaks generated from the power converters. Consequently, the performance of the nearby communication systems is affected under the presence of EMI, which is not covered in many situations. In this paper, the behavior of the G3 Power Line Communication (PLC) channel is evaluated in terms of the Shannon–Hartley equation in the presence of SS-modulated EMI from a buck converter. The SS-modulation technique used is the Random Carrier Frequency Modulation with Constant Duty cycle (RCFMFD). Moreover, The analysis is validated by experimental results obtained with a test setup reproducing the parasitic coupling between the PLC system and the power converter. Full article

Electromagnetic interference (EMI) has become a significant issue as electronic devices become more integrated and achieve high performance. In order to operate at high performance in an integrated system, a high-frequency clock signal is essential to enhance processing speed. However, the harmonic component of the clock signal or gate signal is one of the major EMI sources that can cause peripheral devices to malfunction and affect their stability and reliability. In this paper, harmonic component analysis of the MOSFET gate signal which depends on gate resistance is conducted. Based on theoretical analysis using Fourier series expansion, gate resistance contributes to harmonic components that are determined by the rising and falling times of a gate signal. Simulation and measurement are conducted using a buck converter as a practical application. The theoretical analysis is validated by simulation and experimental results demonstrate that the magnitude of the harmonics is reduced because increasing the gate resistance extends the rising and falling times. Full article

This paper analyzes the possibility of using averaged models to analyze the distribution of power losses in the components of a DC-DC converter including a power module. An electrothermal averaged model of a buck converter including the IGBT module was formulated. This model takes into consideration conduction and switching losses in the mentioned components, the self-heating phenomenon in each component, and mutual thermal coupling between their sub-components. It is designed for SPICE software (version PSPICE A/D 17.4). Its correctness was verified experimentally, and the results obtained were compared with the results of analyses performed with the use of PLECS software and the IGBT module model proposed by the manufacturer. The proposed model’s results show very good accuracy. Through the use of the proposed model, the dependences of the components of power losses and the case temperature of the IGBT module and the inductor on parameters describing the control signal and load of this converter were determined. The distribution of power losses in the converter components was analyzed for selected operating conditions of the buck converter. On the basis of the results obtained, some recommendations were formulated for designers of such DC-DC converters. 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