Model Of Buck Converter Research Articles

Data‐driven Buck converter model identification method with missing outputs

AbstractA data‐driven Buck converter model identification method is proposed to deal with missing (incomplete) outputs, which is robust to the data length and percentage of missing data. A nuclear norm based convex optimization problem instead of linear interpolation, to guarantee the recovered missing data satisfying the potential model structured low‐rank character, is constructed to estimate missing outputs. The alternating direction method of multiplier strategy is used to solve the nuclear norm based convex optimization problem. In this way, the high‐quality missing data can be estimated, even for short data length and high percentage of missing data. Based on the recovered data, the subspace identification method provides accurate estimates of the structure and parameter of the Buck converter synchronously. By applying the proposed method to a Buck converter, experimental results demonstrate its effectiveness.

Robust digital voltage mode control of buck converter with enhanced tracking performance

The digital voltage controller of power converters is used because it has many advantages over its analog counterparts. Thus, in this paper, a controller of digital voltage mode is designed and analyzed for a non-isolated DC-DC buck converter in continuous conduction mode (CCM). First, an analog controller is designed using a Bode plot to achieve the desired stability margins in the frequency domain. Next, the analog controller is discretized using bilinear transformation with the pre-warping method. The characteristics of the discretized compensator can be maintained close to the corresponding analog compensator as long as a proper sampling time is selected. The digital control scheme is simulated with a nonlinear DC-DC buck converter model in MATLAB/Simulink to investigate the controller performance. The simulation results demonstrated the validation of the proposed digital voltage-mode control design approach. The developed digital controller eliminates DC error by tracking the reference voltage, achieving a fast transient response, maintaining specified stability margins, and effectively rejecting large disturbances.

Investigation on the Effect of Parasitic Elements on PID Control of DC-DC Buck Converter

DC-DC converter circuits are used in many electronic devices to adjust the voltage to a certain level such as Electric Vehicle. DC-DC Buck converters, which are the most used type of DC-DC converters, reduce the input voltage and keep the output voltage constant at a desired reference voltage value. In this study, the effect of parasitic elements in Buck DC-DC converters is examined on the PID controllers. Parasitic elements cause a non-linear effect on the Buck converter system model. Studies in the literature generally control the output voltage by designing controllers on the Buck converter model without parasitic elements. Alternatively, linear controllers such as PID are designed according to the linearizing model, taking into account the effect of parasitic elements. In addition, nonlinear controllers are designed on the full model with the effect of parasitic elements. In this study, the effect of parasitic elements on linear controllers, especially PID, is examined.

Automatic Word Length Selection with Boundary Conditions for HIL of Power Converters

Hardware-in-the-loop (HIL) is a common technique used for testing in power electronics. It draws upon FPGAs (field-programmable gate arrays) because they allow for reaching real-time simulation for mid-high switching frequencies. FPGA area and delay are keys to reaching a compromise between performance and accuracy. To minimize area and delay, signal word length (WL) is critical. Furthermore, the input and output’s WL should be carefully chosen because these signals come from ADCs (analog-to-digital converters) or go to DACs (digital-to-analog converters). In other words, the role of ADCs and DACs is the boundary condition when assigning all the signal WLs in an HIL model. This research presents an automatic method for computing the signal WLs in the corresponding model by considering input/output boundary conditions. This automatic method needs a single simulation to decide both the integer and fractional width of every signal. Our method accelerates the process, showing an advantage over manual methods and those requiring multiple simulations. The proposed method is applied to create all the WL assignments to the signals involved in a fixed-point coded buck converter model, which shows its feasibility.

Stability analysis of a hybrid DC-DC buck converter model using dissipation inequality and convex optimization

The stability analysis of a DC-DC buck converter is a challenging problem due to the hybrid systems characteristic of its dynamics. Such a challenge arises from the buck converter operation which depends upon the ON/OFF logical transitions of its electronic switch component to correspondingly activate different continuous vector fields of the converter’s temporal dynamics. This paper presents a sum of squares (SOS) polynomial optimization approach for stability analysis of a hybrid model of buck converter which explicitly takes into account the converter’s electronic switching behavior. The proposed method first transforms the converter’s hybrid dynamics model into an equivalent polynomial differential algebraic equation (DAE) model. An SOS programming algorithm is then proposed to computationally prove the stability of the obtained DAE model using Lyapunov’s stability concept. Based on simulation results, it was found that the proposed method requires only 8.5 seconds for proving the stability of a buck converter model. In contrast, exhaustive simulations based on numerical integration scheme require 15.6 seconds to evaluate the stability of the same model. These results thus show the effectiveness of the proposed method as it can prove the converter stability in shorter computational times without requiring exhaustive simulations using numerical integration.

Filtering of Noisy Nonlinear Buck Converter with CPL Using Carleman Linerization

The paper includes a novel approach for filtering of nonlinear Buck converter with Constant Power Load in noisy environment based on the Carleman linearization approach. The procedure starts with the modeling of Buck converter with Constant Power Load using Hamiltonian framework resulting in the deterministic model of network i.e., a finite dimensional system of ordinary differential equations. To evaluate the effect of noise on it, a Gaussian noise is embedded in the network through switch, which results in the development of stochastic state model and noise present at measurement terminals is considered for measurement equations. Using Carleman linearization approach, the finite-dimensional nonlinear model is transmuted into a bilinear model of infinite-dimension which can be approximated for any chosen order. As a result, we arrive at the finite-dimensional bilinear model of Buck converter with augmented state vector of higher dimension than the original system. State estimation of stochastic dynamical systems in the presence of noisy measurements is an interesting problem and hence, filtering technique is adopted here. The filtering equations in Itô setting are derived for bilinear systems using probabilistic approach for state estimation. The superiority of the proposed bilinear filtering technique over the benchmark EKF is demonstrated by the numerical simulations.

Adaptive Backstepping Terminal Sliding Mode Control of Nonlinear System Using Fuzzy Neural Structure

An adaptive backstepping terminal sliding mode control (ABTSMC) method based on a multiple−layer fuzzy neural network is proposed for a class of nonlinear systems with parameter variations and external disturbances in this study. The proposed neural network is utilized to estimate the nonlinear function to handle the unknown uncertainties of the system and reduce the switching term gain. It has a strong learning ability and high approximation accuracy due to the combination of a fuzzy neural network and recurrent neural network. The neural network parameters can be adaptively adjusted to optimal values through the adaptive laws derived from the Lyapunov theorem. To stabilize the control signal, the additional parameter adaptive law derived by the adaptive projection algorithm is used to estimate the control coefficient. The terminal sliding mode control (TSMC) is introduced on the basis of backstepping control, which can ensure that the tracking error converges in finite time. The simulation example is carried out on the DC–DC buck converter model to verify the effectiveness and superiority of the proposed control method. The contrasting results show that the ABTSMC−DHLRNN possesses higher steady−state accuracy and faster transient response.

Simulation research on sliding mode PID control of Buck converters with improved approaching law

To solve the problem that Buck converters under traditional control strategies will be affected by various disturbances, resulting in poor stability, a new sliding mode PID control strategy based on improved power exponential reaching law is proposed. The sliding mode PID control model of Buck converter is constructed by using the state space average method. On this basis, the traditional reaching law is improved, and the system equivalent control expression of the improved reaching law is obtained by calculation. Finally, according to the equivalent control expression, the control models are built in Matlab/Simulink simulation software, and compared with the PWM-based sliding mode PID control strategy. The simulation results show that the controller with improved reaching law can effectively reduce chattering, steady-state error and overshoot of the system. Besides, the improved controller can make the robustness of the system better.

Design of DC–DC Buck Converter Based on Improved Voltage-Mode COT Control

In this paper, an improved voltage-mode constant on-time (COT) control DC–DC buck converter is designed, which makes the DC–DC buck converter have good stability. Firstly, an improved compensation scheme is introduced through the analysis and derivation of the traditional voltage-mode COT controlled buck converter model. Then, according to the application requirements of the design, Simplis software modeling is used to verify the correctness of the theoretical analysis. The 0.13[Formula: see text][Formula: see text]m BCD technology is used to tape out the DC–DC converter of the improved voltage mode COT. The input voltage is 3.7–5.5[Formula: see text]V and the output voltage is 3.3[Formula: see text]V. The chip test mainly includes heavy-load condition in CCM operation, light-load condition in DCM operation, and load transient response. The test results show that the chip can remain stable under heavy-load and light-load conditions. The overshoot and undershoot in transient response can be quickly restored to steady state during the recovery process. Finally, compared with chips of the same type, it shows that the DC–DC chip for portable electronic equipment designed in this paper adopts an internal compensation structure, which has good stability, simple design, small main chip area, simple peripheral equipment, and good application value.

Dynamic Analysis and Fractional-Order Terminal Sliding Mode Control of a Fractional-Order Buck Converter Operating in Discontinuous Conduction Mode

Fractional calculus provides a new tool for designing the control scheme of a PWM converter. However, in most studies of fractional-order converters, one has used the fractional orders of the converters to construct the controllers. Essentially, this controller does not add any additional fractional-order parameters, which will affect its flexibility. Taking the fractional-order Buck converter operating under discontinuous conduction mode (DCM) as well as the chaotic state as an example, this study proposes a novel fractional-order terminal sliding mode control strategy utilizing additional fractional orders. In order to analyze the nonlinear behaviors attributed to load changes, the discrete iterated mapping model of the voltage-controlled fractional-order Buck converter is proposed and built. According to the discrete iterated map, the bifurcation diagrams and Lyapunov exponent spectrums following different fractional orders are generated, indicating a process attributable to chaos. To suppress the undesirable nonlinear behaviors, a novel fractional-order terminal sliding surface is formed, and the corresponding controller is established. Moreover, the hyperbolic tangent function is introduced to solve the chattering problem. The proposed controller provides greater flexibilities to further improve the control capability. Furthermore, to verify the robustness of the proposed control method, the Mittag–Leffler stability condition of fractional-order systems is adopted. The effects of fractional orders on control performance are also discussed. Finally, circuit simulations with the approximate fractal structures of fractional-order components are implemented and compared so as to further verify the feasibility of the proposed controller.

System Optimization: High-Frequency Buck Converter With 3-D In-Package Air-Core Inductor

In this work, we present the analytical model of buck converter with 3D in-package air-core inductor (150 μm thick). To optimize the power efficiency at a targeted power density, models including 3D inductor and power switches are developed. Compared to 3D EM simulation, the proposed inductor model has a modeling error within 12% for the inductance calculation. With the proposed design methodology, an inductor with Q-factor up to 35 @ 300 MHz is achieved. From the system aspect, the loss breakdown in the integrated power converter is investigated. A 0.5-ratio buck converter can reach 88.5% efficiency @ 1–5W/mm2 based on the optimized inductor designs, with output voltage ranging from 0.7 V to 0.9 V and based on 28 nm CMOS.

Chaos analysis of Buck converter with non-singular fractional derivative

This paper presents a time-domain mathematical model of the Buck converter using the non-singular fractional derivative that was proposed by Caputo and Fabrizio. The time-domain waveforms of the output voltage and current of the converter in different orders are obtained, and the correctness of the time-domain model has been verified. On this basis, the discrete iterative mapping model of the fractional-order Buck converter in peak current mode is established. The chaotic behaviors of the system are studied by numerical simulations, and the bifurcation diagrams at different fractional orders are investigated. The analog circuit implementation of the fractional-order Buck converter is established, and the results obtained via circuit simulations are consistent with the results of numerical simulations, which effectively validate the accuracy of the previous theoretical analysis.

Design of Buck Converter and PV Module for Solar Powered Sailing Boat

The main intention of this work is to minimize the operating cost and increase the power generation of solar photovoltaic (PV) power-driven sailing boat with buck converter. The design of dc-dc converter for solar powered sailing boat is presented here. The entire PV source output power is taken and given to the solar boat through buck converter. The entire output power from the PV source which is given to the dc load is enough to drive a boat. The Buck converter model and solar PV module has been designed and simulated with the use of Matlab Simulink and compared with theoretical predictions.

Design of PID Controller Based on ELM and Its Implementation for Buck Converters

Buck converter is a kind of converter device with high efficiency, wide adjustable output voltage, small loss, small size and light weight. Its circuit has nonlinearity and will exhibit abundant nonlinear phenomena with the change of circuit parameters, resulting in unstable output voltage and being susceptible to load and external disturbances. Therefore, a control method based on Extreme Learning Machine (ELM) combined with a proportionalintegral-derivative (PID) controller is proposed in this paper and used for output voltage control of buck converter. Firstly, the mathematical model of buck converter in Continuous Conduction Mode (CCM) is established by the state space averaging method. Then the PID tuning algorithm is designed in combination with ELM, and the stability analysis of the model is carried out. Finally, the simulation experiment is carried out under different disturbances. By comparing with the open-loop control strategy, the effectiveness of the proposed ELM-PID control strategy is verified, indicating that the proposed method can achieve the stability of output voltage and good dynamic response.

SMC CONTROL APPLIED TO A BUCK CONVERTER: COMPARISON TO A PID CONTROLLER

This paper aims to control the output voltage of a buck converter using a Sliding Mode Controller (SMC) on an AVR experimental setup. The controller has been implemented with SIMULINK followed by simulations in order to check its convergence and to compare SMC’s robustness to PID’s. We have shown that the designed SMC reaches convergence and is more robust than the classic PID controller. We also pointed out that the robustness of the SMC is widely variable from one noised parameter in the Buck converter model to another. Complementary work can be done to explain this variation of the robustness offered by the SMC.

Implementing Discrete Model of Photovoltaic System on the Embedded Platform for Real-Time Simulation

This paper presents the development of a discrete model of a photovoltaic (PV) system consisting of a PV panel, Maximum Power Point Tracking (MPPT), a dual-axis solar tracker, and a buck converter. The discrete model is implemented on a 32-bit embedded system. The goal of the developed discrete PV model is to provide an efficient way for evaluating several algorithms and models used by the PV system in real-time fashion. The proposed discrete model perfectly matches the continuous and discrete model simulated with MATLAB-SIMULINK. The real-time performance is tested by running the model to simulate the PV system, where the fastest time sampling of 1 ms is achieved by the buck converter model, while the longest time sampling of 100 ms is achieved by the solar tracker model. Moreover, a novel method is proposed to optimize the net energy, which is calculated by subtracting the energy consumed by the tracker from the PV energy generated. The proposed net energy optimization method varies the operation time interval of the solar tracker under high and low solar irradiation conditions. Based on the real-time simulation of the discrete model, our approach increases the net energy by 29.05% compared to the system without the solar tracking and achieves an increase of 1.08% compared to the existing method.

Parameter identification based on linear model for buck converters

Parameter identification is an effective method to monitor the health condition of multiple components in power electronic converters. The hybrid model-based method has been proved to be a universal approach. However, the existing hybrid model of buck converter ignores the winding resistance of filter inductor and non-ideal factors, which will cause errors in the identification results. To solve these problems, leg midpoint voltage is used to replace the input voltage and switching signals, and a linear model is proposed, which can be implemented by fewer sensors. In order to verify the superiority of the linear model, this paper proposes a simple and practical parameter identification method for passive components. Compared with the hybrid model-based method, the proposed method does not need a sensor to measure driving signals and can obtain higher accuracy under non-ideal situations. Simulation and experimental results prove the proposed method to be effective and accurate.

Bat Algorithm Based an Adaptive PID Controller Design for Buck Converter Model

The aim of this paper is to design a PID controller based on an on-line tuning bat optimization algorithm for the step-down DC/DC buck converter system which is used in the battery operation of the mobile applications. In this paper, the bat optimization algorithm has been utilized to obtain the optimal parameters of the PID controller as a simple and fast on-line tuning technique to get the best control action for the system. The simulation results using (Matlab Package) show the robustness and the effectiveness of the proposed control system in terms of obtaining a suitable voltage control action as a smooth and unsaturated state of the buck converter input voltage of ( ) volt that will stabilize the buck converter system performance. The simulation results show also that the proposed control system when compared with the other controllers results has the capability of minimizing the rising time to ( sec) and the settling time to ( sec) in the transient response and minimizing the voltage tracking error of the system output to ( ) volt at the steady state response. Furthermore, the number of fitness evaluations is decreased.

Discrete Iterative Map Model-Based Stability Analysis of Capacitor Current Ripple-Controlled SIDO CCM Buck Converter

Capacitor current ripple (CCR) control is applied to single-inductor dual-output (SIDO) buck converter due to its advantages in reducing cross regulation and fast transient response. However, it shows that the stability of CCR-controlled SIDO CCM buck converter can be affected by circuit parameters. In this article, a 5-D discrete iterative map model of CCR-controlled SIDO CCM buck converter is established based on Poincaré maps. The bifurcation analysis and eigenvalues loci clearly shows that the effect of control parameters and load parameters on the stability of CCR-controlled SIDO CCM buck converter. Besides, the effect of studied circuit parameters on the stability range of the converter is investigated. Furthermore, the stability boundaries and stable regions of load parameters and control parameters are obtained by using eigenvalues analysis. The study results show that the increasing of proportional parameters would cause instability and it will reduce the stable region of load parameters. The converter has a stable region for load parameters and these two load parameters have influence on each other. Finally, experimental results are presented to verify the theoretical analysis in this article.

A Generalized Multifrequency Small-Signal Model for High-Bandwidth Buck Converters Under Constant-Frequency Voltage-Mode Control

This article studies the modeling of high-bandwidth buck converters under constant-frequency voltage-mode control, where the traditional small-signal averaged model fails due to two major factors in the pulsewidth modulation (PWM), i.e., the large harmonics of modulation waveform and the considerable sideband components. Several modified small-signal models have been proposed to improve the predictions of the frequency domain characteristics. However, these models are less generalized or with high complexity, and may hardly be used in the closed-loop design of real applications. To handle this issue, this article proposes a generalized multifrequency small-signal model (G-MFSSM) for high-bandwidth buck converters, which makes further progress in accuracy while maintaining simplicity in deriving the analytical transfer functions for a closed-loop design. The generalized average model is adopted to precisely describe the first-order harmonic of the modulation waveform, from which a correction factor is extracted to evaluate the influence of the ripple. Furthermore, two dominant sideband components are selected optimally for extremely accurate loop gain predictions. Finally, a closed-loop design procedure is presented for wide-input, high-bandwidth buck converters based on the proposed G-MFSSM. The validity of the proposed G-MFSSM is verified by simulations and experiments.