Search Results (481)

The stability and transient performance of DC-DC buck converter output voltage is critical. In order to address the voltage control problem under mismatched disturbances and time-varying output constraints, this paper proposes a voltage control framework of the DC-DC buck converter with the guaranteed prescribed performance and fixed stabilization time based on a higher-order fully actuated approach. Firstly, to estimate the mismatched disturbance, a fixed-time extended state observer (ESO) is designed. The original model of buck converter is transformed into a high-order fully actuated system. The uncertainties are approximated by a radial basis function neural network (RBFNN). Then, an adaptive fixed-time sliding mode control law is proposed. The proposed control law could guarantee the prescribed transient performance for the buck converter in the presence of load changing and bounded model uncertainties. The fixed-time stability of the closed-loop system is guaranteed by the Lyapunov approach. The proposed control law is evaluated by comparative experimental tests. Experimental results illustrate the effectiveness and superiority of the proposed control strategy. Full article

This paper presents a fractal–multiscale supervisory control strategy for a digitally controlled DC–DC buck converter. A conventional PI controller is augmented with a supervisory layer that adaptively modulates the effective control gains based on multiscale error dynamics and oscillation indicators derived from the error and its time derivative. In addition, automatic PI shaping using notch and lead compensators is performed through FFT-based identification of dominant oscillatory modes. The proposed approach is evaluated under load, input voltage, and combined disturbances, as well as robustness and stress-test scenarios. The simulation results indicate comparable nominal regulation, reduced oscillatory behavior, and improved robustness-oriented transient response compared to baseline PI control, particularly under non-ideal and stress-test conditions. Full article

This paper presents the design, digital implementation, and experimental validation of a new 50 W scaled prototype of a quadratic buck converter (48 V to 5 V, 10 A) controlled by a finite control set model predictive control (FCS-MPC) strategy. The converter utilizes its quadratic step-down topology to achieve high voltage conversion gain without extreme duty cycles, making it suitable for low-power applications requiring precise voltage regulation. The proposed methodology encompasses the theoretical design of the power stage, the development of the experimental prototype based on a C2000 Digital Signal Processor DSP, and a comparative performance assessment between the proposed FCS-MPC and a conventionally tuned PD controller. An iterative tuning and real-time validation process is employed to optimize both the converter parameters and the control law, ensuring closed-loop stability and enhanced dynamic response under line and load disturbances. The experimental results demonstrate that the FCS-MPC strategy significantly outperforms the PD controller in terms of output voltage regulation, settling time (4.2 s vs. 5 ms), and disturbance rejection (<2 ms recovery). The main contribution of this work is the construction of a new scaled prototype and the experimental validation of a predictive control strategy for a high-gain DC–DC converter, positioning the FCS-MPC-controlled quadratic buck converter as a viable solution for modern applications demanding high energy efficiency and robustness. Full article

This paper proposes a new hybrid switched inductor and switched capacitor (HSISC) buck–boost DC–DC converter. For the duty ratio above 28%, the proposed converter operates as a boost converter; otherwise, it acts as a buck converter. Compared with conventional buck–boost converters, incorporating the hybrid switched inductor and switched capacitor (HSISC), the network yields a substantial voltage gain at lower duty ratios. Being a non-isolated topology, high-frequency transformers and the associated issues are absent. Additionally, the proposed topology has the merits of continuous input current, making it suitable for renewable energy integration and vehicle-to-grid (V2G) applications, a wide range of duty ratio for boost operation, and ease of control as there are only two modes of operation with switches operating in a complementary manner. Operational analysis for the two modes, necessary mathematical derivations for component design, and a steady-state analysis of the converter are reported. The experimental findings for the converter, which were conducted at a duty ratio of 0.05 to 0.5 at a switching frequency of 10 kHz, are reported. The presented results provide proof-of-concept validation based on analytical and simulation studies, demonstrating the feasibility and operational characteristics of the proposed converter. Full article

In recent years, the rapid evolution of large artificial intelligence (AI) models has placed unprecedented demands on the computing power of data center servers, driving an explosive growth in data center computing requirements. The power consumption of core computing components, represented by GPUs, has surged dramatically. When facing extremely high power densities, the traditional 12 V single-voltage power delivery architecture exposes severe limitations, including increased transmission link losses, thermal management difficulties, and low system efficiency. To address these challenges, this paper proposes and designs a hierarchical 54 V/12 V dual-plane multi-phase DC power delivery architecture for high-computing-power AI servers. By conducting refined hierarchical identification of system loads, this architecture introduces a 54 V high-voltage DC power plane for high-power loads while retaining the 12 V power plane for conventional loads. Within each power plane, multi-phase interleaved parallel Buck converters integrated with Turbo-COT control strategies and high-density DrMOS are deployed. Experimental results demonstrate that this power architecture exhibits excellent electrical characteristics: under steady-state conditions, the peak-to-peak (PK-PK) ripple voltage fluctuation amplitude of the 54 V power plane under different loads is compressed to between ±0.22% and ±0.26%, while the PK-PK ripple voltage fluctuation amplitude of the 12V power plane under different loads reaches ±0.66% to ±0.68%; in dynamic load step (0–50% and 50–100%) tests, the PK-PK voltage fluctuations of the 54 V plane are ±1.42% and ±1.33%, whereas the PK-PK voltage fluctuations of the 12 V power plane are ±2.36% and ±1.83%. Furthermore, the peak conversion efficiency of the 54 V power plane approaches 97%, and the maximum efficiency of the 12 V power plane reaches 94%, showing a measurable efficiency improvement under the tested conditions. The hierarchical multi-phase power delivery technology comprehensively reduces power supply link losses and enhances power stability, providing an important theoretical basis and engineering reference for the design of next-generation high-density AI servers and the optimization of green, energy-saving networks in data centers. Full article

This study addresses the power dispatching of a DC-coupled three-phase grid-connected photovoltaic (PV) and energy storage-integrated system by proposing a peak shaving and valley-filling control architecture based on time-of-use (TOU) pricing. This research involves achieving maximum power-point tracking (MPPT) for PVMAs using a boost converter combined with the perturb and observe (P&O) method. A lithium-iron phosphate battery pack is integrated into the DC link via a bidirectional buck-boost converter, where charging and discharging control is executed according to peak and off-peak periods to regulate and stabilize the DC link voltage. Furthermore, bidirectional power flow control for peak and off-peak electricity consumption is realized using hysteresis current control and sinusoidal pulse-width modulation (SPWM) technologies within a smart inverter. By integrating the aforementioned power control architecture, the grid system can store energy from the utility during off-peak hours and release the stored energy during peak hours to reduce the load demand on the utility side. Initially, a simulation environment was established using Matlab/Simulink (2024b version) software, followed by control verification of the proposed system on a physical platform. The simulation and experimental results confirm that the integrated control architecture can precisely control the system’s DC link voltage at 800 V and stabilize the grid-connected AC voltage at an effective value (RMS) of 380 V. Moreover, under conditions of peak/off-peak switching and load variations, the system effectively demonstrates its stability and efficacy in performing valley filling and peak shaving. The proposed strategy achieves a power factor above 0.99 and a total harmonic distortion (THD) below 5%, regulates the DC-link voltage at 800 V with a steady-state error within 1.75%, and prevents up to 66.4 kWh of over-contract energy consumption per day under a 35 kW contract capacity, thereby contributing to sustainable energy management and economic savings. Full article

The main contribution of this work is a co-design process for buck DC/DC converters, aimed at facilitating the development of a system that meets performance specifications from the earliest stages. This process incorporates a cascade control strategy—featuring a PI regulator for the output voltage and a sliding-mode controller for the inductor current—and is implemented as a software tool that guides the designer in selecting off-the-shelf components, determining feasible ranges that balance cost, size, efficiency, and electrical performance. From an engineering perspective, the tool is modeled using component and sequence diagrams, ensuring modularity, traceability, and step-by-step validation between the electrical design and control modules. The validity of this design process is demonstrated through an application that uses two USB Type-C ports. The experimental and simulation results, obtained using commercially available components, confirm that even in the worst-case scenario, the closed-loop system meets all USB-PD specifications, exhibiting precise voltage regulation, fast dynamic response, and well-damped inductor current. Consequently, this work not only proposes a systematic and practical design method but also supports it with concrete evidence of its ability to generate robust, implementation-ready solutions. Full article

This paper presents a five-phase, two-switch buck-boost (5P-TSBB) converter rated at 75 kW, intended for photovoltaic and energy storage applications that require a wide operating voltage range. The proposed system operates with photovoltaic input voltages ranging from 250 V to 1000 V and regulates the DC-link voltage between 600 V and 950 V. The converter supports two distinct operating modes: an independent multi-input mode for multiple independent input sources and an interleaved mode for a single high-power input. The feasible operating area of the converter is determined in the V_in–V_out plane, taking into account voltage, current, and power limitations. Simulation results and experimental investigations on a laboratory prototype, including measurements of efficiency and power losses, support the theoretical considerations. Full article

Transformerless inverters are increasingly becoming essential in renewable energy generation, particularly for grid-connected photovoltaic (PV) and other sustainable and alternative energy resources. The transformerless designs offer higher efficiency, compact size, and reduced cost compared to traditional inverters with bulky transformers. These inverters minimize energy losses and enable direct connection to the grid by removing the low-frequency transformer. This paper investigates a highly reliable single-phase common-ground inverter for solar panels and other alternative energy generation. The proposed PV inverter has the benefits of existing non-isolated common-ground PV inverters, including direct connection of an input source’s negative terminal to the AC neutral terminal, eliminating leakage ground currents. The inverter is an enhancement of the dual-buck inverter, incorporating one additional diode and a flying capacitor. The dual-buck structure with the inductor inserted between the inverter phase leg prevents short-circuiting. This increases the reliability of the entire power electronics system. Moreover, using external diodes to freewheel the current, the configuration has no reverse recovery issues, allowing power MOSFETs to be employed with safe commutation at higher DC-link voltage and achieve higher efficiency. Summarily, this design prevents short-circuit issues, enhancing reliability and efficiency, and relaxing pulse-width-modulation dead times. The derivation of the PV inverter is carefully analyzed. A 700 W prototype of power converter hardware has been built. The comparative study validates the operational performance, and the grid-connected experiment confirms its theoretical analysis. Experimental results of the hardware prototype are discussed to prove the feasibility and effectiveness of the proposed PV inverter. Full article

To address the voltage regulation problem of the DC-DC buck converter under multi-source disturbances, this paper proposes a composite anti-disturbance control strategy integrating a Chebyshev-based self-evolving fuzzy neural network (SECFNN) and an arctangent super-twisting sliding mode control (ASTSMC). First, to construct the composite anti-disturbance framework, a load algebraic reconstruction compensator (LARC) is utilized to analytically estimate real-time load dynamics, providing active feedforward compensation for extreme load steps. Second, targeting the unmodeled nonlinearities and parameter uncertainties, the SECFNN is deeply integrated into the control loop. It employs a bidirectional structural learning mechanism—dynamically growing and pruning fuzzy rules—to achieve high-precision adaptive approximation and intelligent compensation. Furthermore, serving as the robust inner-loop core of this composite strategy, the ASTSMC is introduced. By replacing the traditional discontinuous sign function with a continuous arctangent operator, it effectively mitigates sliding mode chattering while ensuring the rapid finite-time convergence of the current tracking error. Ultimately, by synergistically fusing feedforward disturbance rejection (LARC), intelligent nonlinear approximation (SECFNN), and robust tracking (ASTSMC), the proposed strategy significantly reduces transient voltage drops and achieves smoother steady-state performance. Comparative simulation experiments demonstrate the superiority of the proposed method, achieving a rapid startup settling time of 6.5 ms, limiting the maximum transient voltage drop to 15 mV, and completing dynamic reference tracking in 1.2 ms. Furthermore, hardware experimental results confirm its practical engineering feasibility, demonstrating a fast startup of 8.3 ms with zero overshoot, effectively mitigating transient voltage drops during load step changes, and completing dynamic tracking in just 2.2 ms, which verifies its reliable dynamic agility and strong robustness under various test conditions. Full article

This paper presents an adaptive nonlinear control and state observation framework for energy management in standalone photovoltaic (PV) systems integrated with battery energy storage. A unified nonlinear dynamic model is developed to describe the interactions between the PV generator, the DC/DC buck converter, and the lithium-ion battery. Based on this model, a multi-mode control strategy is designed to ensure efficient and safe operation under varying environmental and loading conditions. The proposed scheme incorporates maximum power point tracking (MPPT) to maximize photovoltaic energy extraction, along with constant current (CC) and constant voltage (CV) charging modes to guarantee battery safety and longevity. To address uncertainties and unmeasured states, an adaptive nonlinear observer is developed for real-time estimation of the battery open-circuit voltage and state of charge. The observer design is supported by Lyapunov-based stability analysis, ensuring boundedness and convergence of the estimation error in the presence of modeling uncertainties and external disturbances. An energy management algorithm is further introduced to coordinate the transition between operating modes according to the estimated system states and battery constraints. The effectiveness and robustness of the proposed control and observation strategy are validated through detailed simulations in MATLAB/Simulink under varying solar irradiance conditions. The results demonstrate accurate maximum power tracking, reliable state estimation, and safe battery charging performance, highlighting the potential of the proposed approach for advanced autonomous PV–battery systems. Full article

This study details the modelling and simulation analyses performed on a mathematically modelled permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) driven by a field-oriented controlled (FOC) voltage source inverter (VSI) coupled with a half-bridge bidirectional buck-boost DC/DC converter for two-wheeler electric vehicle (EV) applications. The 5 kW, 1500 rpm PMa-SynRM employed here has a shorter response time and is also naturally lighter and cost-effective, making it suitable for two-wheeler EVs. Field-oriented control simplifies the control strategy for PMa-SynRM by decoupling torque and flux, effectively matching the behaviour of a DC motor. A half-bridge buck-boost converter is a DC-DC converter capable of bidirectional power flow, stepping up and down voltages. This makes it ideal for both motoring and regenerative braking in electric vehicles. The buck-boost converter with its controller effectively adjusts the inverter and battery voltage for efficient power flow during motoring and maximum power recovery during regenerating braking. The developed model aims at demonstrating forward and reverse motoring, as well as forward and reverse braking to validate the four-quadrant torque-speed characteristics of two-wheeler EVs. The proposed model attains less than 2% torque ripple and less than 1% speed ripple, respectively. Further, the current ripples are minimised to reduce losses and to improve efficiency. The work presented in this paper implements a PMa-SynRM-based drive system for EVs, a technology which is in the exploratory stage and not commercially widespread. This adds novelty to the proposed work. A MATLAB Simulink environment was used for modelling and simulation. Full article

Aiming to improve the robustness of two-phase buck converters powering DC bus of permanent magnet synchronous motor drives, this article presents a novel voltage regulation scheme. The proposed scheme comprises a three-switching-surface nonsingular fast terminal sliding mode controller (TSS-NFTSMC) for output voltage regulation and a current balancing controller to equalize the inductor currents. Due to the fast terminal sliding mode surface, the output voltage error converges more rapidly both when far from zero and when approaching zero. The phase plane is split into four regions by three independent switching surfaces. Based on the region where the sliding variable resides, the TSS-NFTSMC can directly decide the number of enabled high-side switches, which helps suppress internal disturbances effectively. The stability and convergence of the presented control system are verified via Lyapunov stability analysis. The convergence property of TSS-NFTSMC is independent of the current controller. Both simulation and experimental results demonstrate that the proposed control strategy achieves satisfactory dynamic response and strong disturbance rejection capability. Full article

Photovoltaic (PV) power generation is inherently intermittent due to unpredictable irradiance variations, posing significant challenges for grid integration. While conventional power smoothing strategies mitigate short-term fluctuations, they do not explicitly enforce the tracking of a scheduled power trajectory. This paper proposes a dispatchable PV framework that integrates a hybrid convolutional neural network-long short-term memory (CNN-LSTM) model for precise day-ahead power forecasting with a real-time supercapacitor (SC) compensation strategy. The CNN-LSTM network captures complex spatiotemporal meteorological dependencies to generate a robust day-ahead reference trajectory. Concurrently, a supercapacitor energy storage system (SC-ESS) integrated at the DC-link level via a bidirectional buck–boost converter actively balances the instantaneous mismatch between this forecast trajectory and the actual PV generation. Unlike filter-based hybrid methods, the SC-ESS is employed as a direct forecast error actuator in a closed-loop control scheme. This strategy strictly enforces real-time forecast tracking while preserving maximum power point tracking (MPPT) and DC-link voltage stability. Simulations and laboratory experiments under rapidly varying irradiance confirm that the proposed method significantly reduces power deviations from the forecast reference and improves short-term power predictability without imposing excessive stress on the SC. This forecast-aware strategy effectively enhances the dispatchability of PV systems, providing a practical solution for grid-supportive operation. Full article

Power converters are fundamental components in vehicle electrification systems. However, their inherently nonlinear and time-varying condition requires complex design procedures when conventional control strategies based on linear small-signal models are employed. This work proposes a simplified and hardware-oriented DC-DC converter control methodology that combines fuzzy logic and Neural Networks in a sequential manner. A fuzzy logic fuzzy controller is first used to generate a dataset of control actions under closed-loop operation. A lightweight neural network is then trained using the obtained data to approximate this mapping and subsequently replace the fuzzy controller in real-time operation. To validate the approach, a bidirectional buck–boost DC-DC converter is designed for applications in the powertrain of electric vehicles with 500 kHz switching frequency and 13 kW power rating. The control algorithm is embedded in an FPGA to demonstrate its suitability for hardware deployment. The experimental results show a reduction in RMSE of 33.7% and a decrease in the settling time of at least 51.7% when compared with a benchmark PID control. Full article