DC-DC Buck Converter Research Articles

A design of constant on-time control DC-DC buck converter with slope compensation

Abstract In this paper, a DC-to-DC buck converter with slope compensation based on COT architecture is proposed for applications in walkie-talkies, portable power supplies, and cellular phones. Compared to the common COT-controlled DC-DC BUCK converter, which does not notice the feedback voltage jitter problem when the external input power fluctuates, or the load changes rapidly, the slope compensation function is proposed to be incorporated in the design. The feedback path of the voltage is changed by the superimposed ramp signal, which improves the system’s anti-jitter function. The principle is similar to the ramp compensation mode in the conventional current mode, but the implementation is different. The proposed design uses the eastern DP 180nmBCD process with an input voltage range of 6 V to 24 V, an output voltage range of 3 V to 5 V, and a transient response time of only 12.327us for a load from 6 A to 8 A.

Development of Digital Twin for DC-DC Converters Under Varying Parameter Conditions

The constantly changing characteristics of sources, loads, and operating environments in microgrids aboard marine vessels warrant the need for the real-time and accurate transient state estimation of the various converters used for power flow management. This paper presents the digital twin development for a parameter-varying non-isolated DC-DC buck (step down) converter to demonstrate the potential of circuit identification and state estimation within a single digital twin model. The digital twin will utilize individual and parameter-specific NARX-RNNs in a centralized model to identify and adapt system state predictions relative to the most current configuration of the buck converter. Additionally, the model’s ability to maintain state estimation accuracy in the presence of circuit component variation will be demonstrated through simulated deviations from nominal values, and model versatility will be shown through testing a simulation-based model on physical hardware. This modular model, which is demonstrated through simulation and experimentation, can be adapted and scaled for additional circuit configurations. It has the potential to be integrated into real-time system monitoring and fault detection systems within multi-converter microgrid environments.

Evaluation of a fuzzy-based sliding mode control strategy for a DC-DC buck converter

DC-DC converters operate as semiconductor power devices in which transformers such as buck converters often cause nonlinear characteristics to the converter, while the output voltage of the converter affected by dynamic input voltage and load change. This paper presents a sliding mode control strategy using a fuzzy observer to provide a sustainable response and high performance for buck converters affected by uncertainties such as input voltage and resistance load. The control strategy includes two feedback loops in which an external control loop forces the output voltage to track the set voltage, and the output of the external control loop is adapted as a sliding surface to control the current through the inductor to track the set current, called the internal control loop. Design analysis, control law and Lyapunov stability of the control strategy are illustrated. The simulation is developed on the MATLAB-Simulink platform, the results are re-evaluated experimentally based on the self-built prototype of DC-DC buck converter. The simulated and experimental results have showed that the output voltage and current of the buck converter have tracked the set points from low to high values despite sudden changes in load as well as in input voltage in the presence of noise. The compatibility index normalized root mean square error of the measured voltage and current using the proposed algorithm is [96.34%±1.02%, 95.09%±3.04%] higher than that using the proportional integral (PI) algorithm which is [95.94% ± 3.01%, 85.72% ± 3.95%] in the presence of varying parameters.

Fractional-Order Linear Active Disturbance Rejection Control Strategy for DC-DC BUCK Converters

This paper explores the problems of slow response speed, poor anti-interference performance, and low control accuracy that exist in traditional Active Disturbance Rejection Control methods in Buck-type DC/DC converters. To address these issues, a fractional-order Active Disturbance Rejection Control (FO-LADRC) controller is proposed to enhance the dynamic characteristics and anti-interference ability of Buck-type DC/DC converters, while expanding the control range and flexibility of traditional linear Active Disturbance Rejection Control (LADRC). Firstly, the mathematical model of the Buck-type DC/DC converter is established. Secondly, based on Active Disturbance Rejection Control, a fractional-order linear Extended State Observer (FO-LESO) is constructed to estimate the model error and external disturbance of the system. Then, the stability of the system is studied through transfer function and error analysis. Finally, the effectiveness of the FO-LADRC controller method is verified through simulation. The simulation and experiment results show that the proposed FO-LADRC method outperforms traditional PI and LADRC methods in terms of dynamic performance. It can effectively improve the dynamic characteristics of the system and enhance the anti-interference ability of the system.

On-line switched robust fault detection framework for switched systems with unknown inputs

This paper concerns an on-line robust fault detection (RFD) for continuous-time switched linear systems with unknown disturbances and noises. Owing to a novel event-triggered mechanism, the current mode-dependent event detector receives the sampled information of the unknown synchronous switching signal at each sampling instant; the active mode is updated. Thus, the on-line switched unknown input observer immediately estimates the system states. Using the average dwell-time (ADT) approach, new linear matrix inequalities (LMIs) are determined through an online switched quadratic Lyapunov function ensuring the globally uniformly asymptotically system stability (GUAS). So, we establish less conservative stability criteria, while the ADT switching mechanism is formulated to ensure that the estimation error converges by determining a minimum average dwell time for the switching signal. The designed robust fault detection framework is proper to find out all kinds of unknown faults (affected by each current mode), in real-time, via online residual indicators with adaptive thresholds that are robust to the deterministic input disturbances, as well as the impact of the stochastic disturbances is reduced regarding an H ∞ performance with on-line switched index. Simulation results on a DC-DC buck converter are given to underline the online applicability of the suggested approach. A comparative study of the RFD scheme concerning existing works is provided, where our results are shown to be less conservative and more valid.

Smart AcuGlove: A Mobile-Controlled Wearable for Targeted Pain Relief and Wellness

The Smart AcuGlove is an embedded therapeutic device designed to automate acupressure treatment by merging electromechanical actuation with principles of Traditional Chinese Medicine (TCM). It features eight micro servo motors embedded in a flexible textile glove, each aligned with specific palmar meridian acupoints. An ESP32-based control unit orchestrates these actuators using real-time task scheduling to execute predefined stimulation protocols with precise timing and force parameters. The system is powered by a compact 12V lithium polymer battery, with voltage regulation provided by a high-efficiency DC-DC buck converter to ensure the safe operation of the actuators. The glove's ergonomic and compliant design maintains natural hand mobility while delivering consistent therapeutic output. By eliminating the need for sensors, the Smart AcuGlove reduces system complexity enhances reliability, and minimizes operational overhead. This integration of traditional therapeutic practices with modern embedded technology offers a portable, autonomous, and repeatable solution for pain management and neuromuscular rehabilitation.

A New Type of DC-DC Buck Converter with Soft Start Function and Reduced Voltage Stress

This paper introduces a novel topology called the dual-path step-down converter with auxiliary switches to minimize voltage stress and enable wide voltage conversion ranges. The proposed dual-path step-down converter with auxiliary switches, which uses an inductor and flying capacitor as power conversion components, helps to reduce the voltage stress on the power switches. By adding auxiliary switches, the proposed topology achieves the same voltage conversion ratio range as that of a conventional buck converter. Additionally, soft-start technology is incorporated to reduce the initial inrush current. Furthermore, this paper introduces a system-level design procedure for DC-DC converters. Designed for low-power applications with lithium-ion (Li-ion) batteries, the proposed converter steps down the battery voltage to 1.2 V. With a 380 nH inductor and a 5 µF output capacitor, the converter attains a peak efficiency of 90% under the conditions of 2.7 V to 1.2 V conversion.

Design and control of a DC-DC buck converter using discrete Takagi-Sugeno fuzzy models

Introduction. A DC-DC buck converter plays a crucial role in industrial applications by efficiently stepping down voltage levels to power various electronic components and systems. However, controlling a buck converter is challenging due to its inherently nonlinear behavior. This paper presents a novel fuzzy tracking control approach for the buck converter, based on the combination of time-discrete Takagi-Sugeno (T-S) fuzzy models and the concept of virtual desired variables (VDVs). Originality. This paper introduces an innovative fuzzy tracking control that integrates time-discrete T-S models and VDVs concept to develop an efficient digital controller. Goal. The proposed fuzzy control strategy aims to regulate the output voltage regardless of sudden change in setpoint, load variation and change in input voltage. Methodology. The proposed control strategy aims to regulate the output voltage of a DC-DC buck converter. The design starts with a discrete T-S fuzzy controller based on the nonlinear model of the buck converter. A nonlinear tracking controller is developed using a virtual reference model that incorporates the VDVs concept. System stability is analyzed via Lyapunov’s method and expressed through linear matrix inequalities. Results. Simulation tests under varying conditions validate the accuracy and effectiveness of the controller in achieving superior voltage tracking performance. Comparative analysis with a conventional PID controller highlights faster dynamic response and better tracking, showcasing the advantages of the proposed approach. Practical value. The practical value of this research lies in the development of a robust voltage control strategy for DC-DC buck converters and the establishment of reliable and efficient electrical systems using discrete-time fuzzy T-S control. This work also opens up the prospect for future implementation in experimental prototypes. References 30, table 2, figures 7.

Solar charging controller using DC-DC buck converter with cascaded PI controller for a sustainable renewable energy system

The renewable energy system (RES) has recently become hot topic due to its unlimited, green energy potential, and the maturity of its technology. A solar charging controller (SCC) is required to regulate parameters for the battery and is an essential component for sustainable and renewable energy usage. An SCC based on a DC-DC Buck converter with cascaded proportional-integral (PI) controller is used in the system for managing the current and voltage loops, thereby preventing battery overcharging. The control parameters are determined using the Ziegler-Nichols method based on the reaction curve. A first -order system is employed due to the open-loop responses show no overshoot and oscillations. MATLAB software is used for both simulation and controller design. Simulations are conducted to validate the proposed SCC with the cascaded controller. Variations in the state of charge (SoC) are presented in two cases: without and with the controller. The SoC is set 20%, 50%, and 95%. A high SoC percentage indicates that the battery is near the full capacity, whereas a low percentage indicates that battery is near empty. Using the cascaded controller, both current and voltage responses at different SoC levels demonstrate satisfactory performance, including rapid transient responses, minimal overshoot, small ripples, and robustness.

Hybrid AHP-VIKOR methodology for multi-criteria decision-making in marine renewable energy systems: Optimizing DC-DC buck converters for sustainable offshore applications.

Hybrid AHP-VIKOR methodology for multi-criteria decision-making in marine renewable energy systems: Optimizing DC-DC buck converters for sustainable offshore applications.

Evaluating DC-DC Buck Converter Efficiency with MOSFET and GaN-FET Technology

This paper assesses the efficiency of DC-DC buck converters utilizing both MOSFET and GaN-FET technology. An analysis is conducted on single-phase switched capacitor buck converter equipped with GaN FETs, highlighting its capability to operate at higher frequencies due to the rapid switching speeds of GaN FETs. This feature results in a decreased size of passive components in comparison to traditional buck converters. Additionally, the specifications for the inductor are also examined. To demonstrate the advantages of GaN FETs over MOSFETs in DC-DC converters, the performance of the GaN-FET based converter is compared with that of a traditional MOSFET-based converter. Key performance metrics evaluated includes output voltage, inductor current ripple, voltage stresses across semiconductor devices, power losses, and overall efficiency. The results indicate that the GaN-FET based converter achieves a lower output voltage at higher duty cycles, reducing losses associated with small duty cycles. Additionally, the proposed converter demonstrates superior performance across all evaluated parameters, reinforcing the efficiency benefits of GaN-FET technology in DC-DC buck converters.

IOT-Based Automatic Vehicle Accident Detection System

Road accidents remain a pressing global issue, causing significant injuries, loss of life, and economic setbacks. The delayed detection of accidents and communication to emergency responders often worsens these outcomes, highlighting the need for efficient and automated solutions. . An IoT-based Automatic Vehicle Accident Detection and Alert System has been developed to solve the identified problems by integrating superior sensors and real-time communications. The system employs an accelerometer module to continuously monitor vehicle dynamics, identifying sudden deceleration or impact patterns that signify a potential accident. Once an accident is detected, a NEO-6M GPS module accurately determines the exact location, and a GSM module instantly transmits SMS alerts to predefined contacts or emergency services, reducing response times and increasing the chances of saving lives. An Arduino Nano microcontroller acts as the system's core, seamlessly processing data from all sensors and managing the communication protocols. A DC-DC buck converter ensures stable and efficient power delivery, enhancing the system’s reliability, even in adverse conditions. Compact and cost effective, this design can be easily adapted for various vehicle types, ranging from personal cars to commercial fleets. Moreover, the system lays the foundation for future enhancements, such as mobile app integration, cloud-based accident data analysis, real-time updates to stakeholders, and predictive vehicle maintenance. By bridging the gap between accident occurrence and emergency response, this innovation not only promises to save lives but also empowers stakeholders with data-driven insights to improve road safety and vehicle reliability.

Design of Controllers for DC-DC Buck Converters

The design of controllers for DC-DC buck converters using PID controller and fuzzy logic controller has been the subject of numerous research studies in recent years. The objective of these studies is to improve the performance of the buck converter in terms of output voltage regulation, transient response, and efficiency. PID controller is a commonly used feedback control mechanism that uses proportional, integral and derivative terms to adjust the output of the system. The PID controller is widely used in DC-DC buck converters due to its simplicity and effectiveness. The proportional term of the PID controller adjusts the output based on the difference between the actual and desired output, the integra term is used to eliminate steady-state error, and the derivative term improves the transient response of the system. On the other hand, the Fuzzy Logic Controller (FLC) is a more complex control mechanism that uses linguistic rules and fuzzy sets to adjust the output of the system. FLCs have been shown to be effective in DC-DC buck converters due to their ability to handle non-linearities and uncertainties in the system. In this paper, we are simulating PID control and fuzzy logic control for both single stage and cascaded converter. The hardware implementation of the former is done as well, and the results are compared based on rise time, settling time, peak overshoot and offset at steady state.

Optimizing State Space Integral Controllers for DC-DC Buck Converters Using FPGA-Based Genetic Algorithms

Optimizing State Space Integral Controllers for DC-DC Buck Converters Using FPGA-Based Genetic Algorithms

Firefly Algorithm-based Optimization of Control Parameters in DC Conversion Systems

Sustainable energy and electric vehicles require DC-DC converters in renewable energy systems, EV charging, and smart grids. In this context, buck converters are crucial, providing efficient voltage regulation and reliable performance in these advanced energy systems. While Proportional-Integral (PI) controllers are widely adopted for their simplicity and dependability, they often rely on manual parameter tuning, limiting their adaptability and responsiveness. To address this limitation, this research introduces a digital control strategy that optimizes the PI parameters using the Firefly Algorithm (FA). This optimization significantly enhances the stability and reduces the oscillations in the DC-DC buck converter. A MATLAB/Simulink simulation model is utilized to validate the proposed approach, and the results demonstrate that the FA-optimized control parameters substantially improve the converter's performance, making it highly suitable for high-demand applications in advanced energy systems.

Through-Hole Buck Converters for Fast Prototyping: A Comparative Study

The increasing demand for emerging applications like IoT or drones has boosted the interest of industry and academia in DC-DC converters. Due to their high performance, non-isolated buck DC-DC converters have become one of the most common configurations for covering the power demand of portable devices. The current trend focuses on manufacturing these integrated circuits (IC) using surface-mount technology packaging. However, this technology presents disadvantages compared to through-hole devices in pursuing a quick functional circuit. This work aims to guide designers in choosing the most suitable integrated THT buck converter to develop a fast prototype. A comparative market analysis was conducted considering five integrated chip manufacturers to identify the most adequate ICs for this purpose. Then, a comparative experimental study focused on the buck converter LM2576-ADJ by Texas Instruments was carried out. The analysis aims to determine the performance of this IC mounted in a breadboard and stripboard compared to a demonstration board based on SMT technology provided by the manufacturer. Despite their shortcomings, these quick implementations performed remarkably well regarding, among others, line regulation and load regulation (0.37% and –0.33%, respectively), as well as efficiency (up to 79.9%), which indicates that their electrical response was not compromised.

Active Disturbance Rejection Control Method With Its Application to DC/DC Converter

This paper investigates the control of DC-DC converter with the help of Active Disturbance Rejection Control (ADRC). The DC-DC converter is an important power electronic equipment used for voltage regulation, but its performance is often influenced by external disturbances. Traditional control approaches, such as PID, are inadequate in handling such disturbances in real-time. To address this challenge, an ADRC-based control approach is applied. The ADRC control approach, particularly through the use of Extended State Observer (ESO), is configured to address and reject disturbances, ensuring accurate output voltage control. In this paper, DC-DC buck converter and boost converter are both applied with ADRC control approach, to analyze the more general situation.

Artificial Neural Network Based On a Predictive Current Control in A DC to DC Buck Converter

Artificial Neural Networks (ANNs) have emerged as a powerful tool for enhancing predictive control strategies in power electronics applications. This paper presents an ANN-based predictive current control approach for a DC-DC buck converter, aimed at improving dynamic performance and efficiency. The proposed method utilizes a trained neural network model to predict the optimal duty cycle for the converter, based on real-time input voltage, load conditions, and current feedback. By leveraging machine learning techniques, the system can achieve faster transient response, reduced steady-state error, and enhanced robustness against parameter variations compared to conventional control methods like PI controllers.

Battery management system using Jaya maximum power point tracking technique

This paper introduces the development of a battery management system (BMS) utilizing the Jaya-based maximum power point tracking (MPPT) technique. Previous studies have combined various MPPT techniques with switching methods, each having its pros and cons. Traditional MPPT methods are common but have limited performance. Therefore, artificial intelligence (AI)-based approaches are introduced to enhance and reduce the limitations faced. The Jaya technique is straightforward and easy to implement, making it an attractive choice for MPPT in photovoltaic systems. It is recognized for its effectiveness in eliminating the worst solutions and identifying the best solution with only a few control parameters required for operation. The proposed work aims to develop a BMS using a DC-DC buck converter and the Jaya MPPT technique. The objective is to find the MPP to achieve the desired performance level and ensure the effectiveness of maintaining battery quality, preventing overcharging or undercharging. The system is modeled in MATLAB/Simulink. The findings indicate that the Jaya MPPT demonstrates a tracking speed of less than 1 second to locate the maximum power point (MPP). Furthermore, the BMS is capable of monitoring changes in state of charge (SoC) to determine whether the system is in charging or discharging mode.

Power Extraction in Photovoltaic Systems using P&O-Based MPPT with DC-DC Buck Converter Integration

Solar energy is an abundant, renewable resource that offers a sustainable alternative to fossil fuels. Photovoltaic (PV) systems, which convert sunlight into electricity, have gained global prominence due to technological advancements and decreasing costs. A typical PV system consists of solar panels, inverters, and energy storage. However, the efficiency of these systems is affected by variable sunlight and temperature conditions. Maximum Power Point Tracking technology works as an optimization tool for solar panel operations by finding their maximum operational efficiency. The research examines solar panel modeling together with MPPT algorithms and buck converter implementation for energy management between solar panels and storage systems. Simulations based on MATLAB/Simulink evaluated the performance output of a two-stage PV system which integrated an MPPT-controlled buck converter for performance assessment. The system evaluation results demonstrate its analysis of maximum power point while monitoring various conditions that optimize energy efficiency through irradiance and temperature variations. Off-grid and hybrid systems require energy storage according to research findings which demonstrates both lead-acid and lithium-ion batteries as options. The paper explores solar energy integration challenges alongside methods to use advanced energy conversion systems and smart grid systems for enhancing future performance. The study highlights solar energy promising potential to be a key player in the global shift toward renewable energy. The simulation results further validate the system's strong performance, confirming its effectiveness in supporting this transition.