Bidirectional Buck-boost Converter Research Articles

Switched-Capacitor-Based Hybrid Resonant Bidirectional Buck–Boost Converter for Improving Energy Harvesting in Photovoltaic Systems

Photovoltaic (PV) modules are often connected in series to achieve the desired voltage level in practical applications. A common issue with this setup is module mismatch, which can be either permanent or temporary and is caused by various factors. The differential power processing (DPP) concept has emerged as a prominent solution to address this problem. However, a significant drawback of current DPP topologies is their reduced performance under certain conditions, particularly in cases of permanent mismatch. As a result, applications involving the DPP concept for permanent mismatches remain underexplored. In this context, the goal of this work is to develop and implement a novel DPP topology capable of increasing energy harvesting in PV systems under permanent mismatch. The proposed hybrid architecture combines features from both bidirectional buck–boost (BBB) and resonant switched capacitor (ReSC) converters. The ReSC converter operates under soft-switching conditions, minimizing undesirable losses. Key advantages of the proposed converter include fewer switches, lower voltage stress, and soft-switching operation, making it suitable for PV systems with mismatched modules. Experimental tests showed an energy harvesting improvement under the assessed conditions.

Solar PV powered DC charger for electric vehicles with reconfigurable power electronic interface

ABSTRACT Global expansion of the EV market has led to widespread DC charging infrastructure. Consumers prefer DC charging over AC to reduce charging time per kilometer. However, grid-connected DC chargers can cause issues such as grid instability, power quality problems, demand imbalance, and conversion losses. This paper proposes an off-grid photovoltaic (PV) fed DC charger for EVs along with a battery energy storage system (BESS) to mitigate these challenges. The work aims to increase the use of clean energy for EV charging, to ensure uninterrupted EV charging with minimum power conversion stages, and to improve PV utilization. BESS serves as a backup power source that charges or discharges based on PV availability. Additionally, the system powers the non-critical adjustable loads of domestic/industrial sites with the available PV power when both EV and BESS are fully charged. The system can be reconfigured to operate in six distinct modes using two DC-DC converters and five relays. Among six modes, four modes operate in single-stage power conversion. A buck converter is used to extract power from PV. A bidirectional buck-boost converter is used to charge and discharge the BESS. The proposed system is validated through hardware prototype for both steady-state and transient conditions.

A robust sliding mode control strategy for DC voltage stabilization in solar powered electric vehicle charging station

ABSTRACT Integrating DC power sources and AC grid in an electric vehicle charging station through converters can introduce oscillations, potentially leading to system instability. This paper explored the utilization of a sliding mode controller in a bidirectional DC-DC buck-boost converter for DC bus voltage control within the charging station. This controller aims to promptly respond to power fluctuations, offering robustness against variations in system parameters, external disturbances, and uncertainties. Control strategies play a critical role in mitigating DC link voltage fluctuations and ensuring power stability. The system entails a photovoltaic array employing maximum power point tracking for optimal energy harnessing. In addition, a bidirectional buck-boost converter is employed to effectively manage battery charging in buck mode and discharging in boost mode. A comparative analysis between Proportional-Integral control and sliding mode control incorporating a washout filter was conducted. This assessment is simulated and validated using MATLAB/Simulink, and the Sim Power System toolbox. The proposed model offers a comprehensive solution for integrating solar power, battery storage, and grid-based charging by enhancing overall system efficiency and reliability.

Heuristic power management of hybrid source electric vehicle based on PV-battery-PEMFC

Renewable energy sources are now being focused on for usage in electric vehicles. Although majority of electric vehicles run solely on batteries, they have eliminated local emissions but not pollution. To tackle this issue, this research looks into the performance and power management aspects of an electric vehicle's hybrid power system, with a particular emphasis on the interactions between fuel cells, batteries, and photovoltaic (PV) cells. Stable operation is ensured via a bi-directional buck-boost converter, which maintains the voltage from all sources around reference 430 V. Initially, the fuel cell supplies electricity under low light conditions. The PV system and battery take over when the irradiance surpasses 100 W/m2, with the battery first draining and then charging in tandem with the increase in irradiance. 1750 RPM is the constant motor speed that is reached after making the required torque adjustments. A model full electric vehicle with multiple sources has been proposed with an efficient power management algorithm. When the battery is in stationary mode and the state of charge (SOC) is less than 100%, extra solar power is used to charge the battery. The model also takes into consideration using the car for entertainment or gadget charging when the ignition is off. The biogas output can be regulated using an inferential control technique using artificial neural network (ANN) based on the fuel demand or consumption. The system also includes anaerobic digestion of organic waste to provide hydrogen for the fuel cell sustainably from biogas. Power, current, SOC profiles, motor performance graphs, and other validations show that the extensive simulations exhibit efficient power management and a strong model for hybrid electric car power systems. The model has been simulated in the MATLAB Simulink environment and has been tested under realistic conditions.

Intelligent Power Management of Electric vehicle with onboard PV by ANN-based Model Predictive Control

This paper presents a novel configuration of Hybrid Electric Vehicle (HEV) with fuel cell as primary source and an on-board Photovoltaic (PV) array as secondary source. It incorporates an advanced Model Predictive Control (MPC) system that utilizes Artificial Neural Network (ANN) technology to control induction motor of electric vehicle. The system has three main parts: a fuel cell, an electrolyzer, and a PV array. Each part has a different job in supplying power to the vehicle. The PV array functions to supplement the fuel cell by providing power when ample irradiation is available. When the car isn't being used, the extra power from the solar panels goes to the electrolyzer. There, it turns into chemical energy, making hydrogen. This hydrogen is stored in the onboard hydrogen tank for future use. To fulfil the voltage needs of both the motor and energy sources, a quadratic bidirectional buck-boost converter (QBBC) is utilized. This converter efficiently manages the voltage output while ensuring compatibility with various energy sources. The system undergoes comprehensive analysis under different irradiance and speed conditions to evaluate its performance and efficiency. To make the solar power system more efficient and cost-effective, a Maximum Power Point Tracking (MPPT) algorithm is used. This algorithm helps get the maximum power from the PV system. An improved incremental conductance algorithm is used for this, making sure it accurately finds the best power point. The control strategy incorporates both outer voltage and inner current control, to effectively control the DC output voltage of the QBBC. The vehicle's drive system employs an indirect vector-controlled induction motor. To regulate the motor's speed effectively, an advanced ANN-MPC system is used, providing precise control and high efficiency. This paper introduces a novel approach for predictive torque control of AC machines, eliminating the need for weighting factors. An ANN estimator is used to accurately expect the motor speed, which improves the overall performance of the control system. By using MATLAB/SIMULINK to test how well the proposed Electric Vehicle (EV) setup works and make sure it's effective in real-life situations. Through this comprehensive approach, the paper contributes to advancing the development of efficient and intelligent electric vehicle systems..

Bidirectional Charger for Electric Vehicle Applications

The rise in EV mobility has encouraged the growth of V2G technology. The vehicle-to-grid technology allows bidirectional power flow between the battery of the EV and the grid. In the G2V mode of operation, EV batteries are charged from the grid. Bidirectional buck-boost converters allow power flow control, load balancing, and distributed resource integration, contributing to grid stability and resilience. It also helps in the synchronization of renewable energy sources with the grid by stepping up or down the voltage to match the grid requirements. The proposed system consists of a bidirectional DC-DC converter, which is used to control the power flow in both directions. A MATLAB Simulink model for the converter has been simulated with a PI controller to operate in a closed-loop mode. In addition to the simulation, a prototype model of the converter has been developed.

Design of a bidirectional EV charger using unit template-based current-controlled synchronous reference frame hysteresis

Abstract Existing distribution networks were not designed with large-scale electric vehicle (EV) charging infrastructure in mind. Integrating EV charging stations with the distribution grid might lead to power quality (PQ) issues at the point of common coupling (PCC). This work proposes a two-mode, unit template-based synchronous reference frame hysteresis current-controlled (SRF-HCC) three-phase Level 2 EV charger. Mode one focuses on charging the EV battery from the grid (G2V) and utilizes current and voltage control techniques to enhance battery life and performance. Whereas mode two enables the EV’s stored energy to be discharged to the grid (V2G) by the EV user, allowing the sale of power to support the transient effect of the grid voltage and frequency and enhancing the grid’s PQ. The HCC generates switching pulses for both the AC-DC and buck-boost converters. The SRF-based unit template-based control (SRF-UTC) method ensures system stability, voltage, and frequency regulation for power exchange with the grid by combining its efficiency with that of the HCC. The EV charger proposal comprises three primary components: a 3-phase bidirectional AC-DC converter, a bidirectional buck-boost converter, and a filter circuit. The proposed system was modeled using MATLAB/Simulink and evaluated in two case studies to assess its performance.

СИНТЕЗ ДВОКОНТУРНИХ СИСТЕМ КЕРУВАННЯ НАПРУГОЮ РЕВЕРСИВНИХ ПІДВИЩУВАЛЬНИХ DC-DC ПЕРЕТВОРЮВАЧІВ

The paper deals with the design and analysis of cascaded DC-link voltage control systems for bidirectional buck-boost DC-DC converters. Its model is significantly nonlinear and non-minimum-phase, which makes it impossible to achieve high dynamic quality indicators using standard methods of linear control theory. A new method for design and analysis of DC-DC converters control systems based on partial feedback linearization and the subsequent application of linear PI voltage and current controllers is proposed. It provides that the resulting model is composed of the feedback inter-connected linear asymptotically stable subsystems with bilinear properties. The resulting system is linearized in the vicinity of the trajectories corresponding to the power balance equation. Such form allows to apply the theory of cas-caded systems with two time-scale separation of the control loops dynamics. It not only ensures system stability but also allows to specify the process quality indicators using methods available to control engineers. References 14, figures 9.

AUTONOMOUS MOBILE ROBOT WITH HYBRID PEM FUEL-CELL AND ULTRACAPACITORS ENERGY SYSTEM. DEDALO 2.0

This paper presents a hybrid configuration combining a hydrogen fuel cell and ultracapacitors to create an energy storage system. Hybrid topology is constructed using a SEPIC converter, which connects the fuel cell with the DC bus whereas a bidirectional Buck-Boost converter links the ultracapacitors group with the DC bus. The main aim is to increase the efficiency of the hybrid power system applied about an autonomous mobile robot. An active Fuel Cell voltage control strategy is presented to manage the power flows. In addition, the overall efficiency of the proposed hybrid power system at overload operation is higher than the conventional one. In this paper, an autonomous mobile robot was converted from a conventional lead-acid or lithium-ion battery to a hybrid PEM Fuel-Cell and ultracapacitors as the power source. The integration of UCaps as element of energy storage on the robot was studied with the aim to improve the energetic solution

Fully Soft Switched Bidirectional Buck–Boost Converter With Improved Voltage Conversion Ratio and Single Auxiliary Switch

In this paper, a fully soft-switched bidirectional buck/boost converter with improved voltage conversion ratio (VCR) and minimum semiconductor devices is proposed. An auxiliary circuit which employs only one active switch along with coupled inductors technique is utilized to increase VCR and provide soft switching condition for all semiconductor devices. Soft switching condition is provided at a wide power range while the leakage inductance energy of coupled inductors is absorbed in both power flow directions. The main switches are turned on at zero voltage-zero current switching and turn off at zero voltage switching, while the switches body diodes used as the converter diodes turn off at zero current switching which alleviates the diodes reverse recovery problem. Soft switching operation and low component count especially the active switches have contributed to realize a proper converter efficiency. Moreover, the converter has maintained continuous current at low voltage side, common ground between the high and low voltage sides and switches voltage stress similar to the basic bidirectional buck/boost topology. A converter prototype at 300W and 100kHz is implemented to confirm the converter theoretical operation and analysis.

Design and Development of Bidirectional Converter based on V2G and G2V Operation

The rapid progression of electric vehicles (EVs) in the transportation sector poses a potential challenge of increased peak energy demand on existing grid structures. Consequently, the significance of V2G power conversion technology becomes paramount in managing sudden surges in energy requirements. To address this issue, the authors propose a “Bidirectional Converter Based on V2G and G2V Operation” which focuses on facilitating energy transfer between vehicles and the grid through bidirectional converters, catering to both V2G and G2V operations. In this work, the authors analyzed a bidirectional buck-boost converter interface with an H bridge AC/DC converter together with the related control method in a reduced topology. The efficiency of the developed system is evaluated with the help of a developed simulation model in MATLAB/SIMULINK. The developed model was tested under various conditions and was able to perform effectively.

A Comparison Between the Quality of Two Level and Three Levels Bidirectional Buck-Boost Converter Using the Neural Network Controller

A Comparison Between the Quality of Two Level and Three Levels Bidirectional Buck-Boost Converter Using the Neural Network Controller

A Comparative Study of the Performances of the LQR Regulator versus the PI Regulator for the Control of a Battery Storage System

Background: This paper is consecrated to the development of a new approach to control a bidirectional DC-DC converter dedicated to battery storage systems by applying an optimal control based on a linear quadratic regulator (LQR) combined with an artificial neural network (ANN) algorithm. A state representation of the Buck-boost converter is performed. Then the ANN-LQR control strategy is compared to a classical control based on the proportional-integral controller combined with an ANN algorithm. The ANN algorithm generates the reference charging or discharging current based on a comparison between the power generated and the power consumed. In order to obtain an accurate comparison, two identical systems are designed, each consisting of a photovoltaic system optimized by an incremental conductance algorithm (INC) that powers a dynamic load and a backup storage system consisting of a lithium-ion battery. A management and protection algorithm is developed to protect the batteries from overcharge and deep discharge and to manage the load availability on the DC bus. The simulation results show an improvement in the performances of the storage system by the ANN-LQR control compared to the ANN-PI method and an increase in the stability, accuracy, efficiency of the system is observed. : Photovoltaic (PV) energy is one of the most promising technologies for combating climate change and meeting the urgent need for green renewable energy and long-term development. PV energy generation has a number of advantages: Solar energy is limitless and available anywhere on the planet. However, photovoltaic energy is intermittent and depends on meteorological conditions; also, the energy consumed is unpredictable. For this reason, a storage system is necessary to overcome these problems. Objective: The objective of this study is to develop an optimal control using a Linear Quadratic Regulator (LQR) combined with a neural network algorithm (ANN) to improve the performance of an electrical energy storage system and compare the results obtained with the classical control based on the PI regulator. Methods: The state representation of the bidirectional Buck-boost converter was performed in order to apply the optimal control and determine the gain K and the ANN algorithm allowed to determine the charge and discharge current according to a comparison between the power produced and consumed. Results: The simulation results obtained by two control methods can be used to compare and select the appropriate control method to achieve optimal efficiency of the storage system. Conclusion: The combined ANN-LQR technique offer better performances and stability of the installation compared to the ANN-PI controller.

Ultracapacitor as selectable energy buffer in electric vehicle application

A method of ultracapacitor integration with a regenerative braking system for use in electric drive trains is presented in this paper. An ultracapacitor (UC) is an intermediary to store and provide energy on the DC bus in certain scenarios, such as during acceleration and regenerative braking. UC is used to avoid direct inrush loading on the battery, which the electric drive system may cause. The energy from UC is injected into the DC bus in compliment to the battery, for which a dedicated power source switch called the “Main Charge Controller” (MCC) is responsible. The charge discharge of UC is done through a bidirectional buck-boost converter (BDBBC). The use of UC to offload high energy demand from the battery and store energy recovered during regenerative braking helps improve the vehicle's life and per-charge range. The stored energy in UC can be obtained from the battery at the start. UC can also be charged at the time of charging. The design and the presented control are ideal for lightweight electric vehicles. The system uses a 39.9 kJ ultracapacitor, formed from market-available 50F 2.7 V units in a 52S configuration, storage, and a 6kWh battery. The simulated vehicle in battery only case provides a minimum of 154 km range in rough conditions, in best case scenario it provides a 200 km range. The proposed design provides an increased extended range compared to simple battery-based regenerative braking, in the case of this work the hybrid solution provides an addition of more than 30 km of additional range compared to a battery-only solution which is simulated for all the same conditions except without the addition of the UC and its control and handling system, resulting in a total range of 230 km. The speed control response achieved by the user is also very fast. Electric Vehicles have range limitations due to storage technology which is a high entry barrier for consumers looking for reliable vehicles without range anxiety, as storage technology progresses adoption will become easier. This work is an attempt at using hybrid storage and selective use of it, for improved range and sharper speed response. However, this work does not explore the aging of the storage components due to increased operational load and thermal stresses or application to alternate battery chemistries. This work is primarily focused on the vehicles that use lithium-based batteries.

MPPT DC-DC Buck-Boost Converter for Off Grid Hybrid Solar-Wind-Battery System in Ikuza Island, Tanzania

Ikuza Island in Tanzania faces lack of electricity. Therefore, this paper undertakes to design hybrid renewable energy sources for the island by specifically focusing on the buck-boost converter for the energy conversion from these renewable resources. The design of the bidirectional buck-boost converter for maximum power point tracking in off-grid hybrid renewable energy systems is multifaceted due to the inhomogeneity nature of the renewable energy sources. The bidirectional buck-boost converter, solar PV, wind-based generator, and energy storage system were designed and simulated in MATLAB/Simulink software. The designed system was tested with varying solar irradiance (750 to 1000 W/m2), temperature (20 to 25°C) and wind speed (150 to 157.5 radians/s) at constant load of 260 A while load variation involved varying the load current from 0 to 260 A at solar irradiance, temperature, and wind speed of 1000 W/m2, 25 °C and 157.5 radians/s, respectively. The variation of DC link bus voltage at different load conditions was reported. The simulation results show that the designed converter is able to maintain DC link voltage at 600 V. Moreover, the DC link voltage showed a maximum drop of approximately 0.67% during the constant load condition. Contrarily, a significant improvement is observed when the designed converter operates with the hybrid system of solar PV, PMSG-based wind generator and with energy storage system.

A Grid Connected PV Array and Battery Energy Storage Interfaced EV Charging Station

In this work, a charging station for EV (Electrical Vehicle) integrated with a BES (Battery Energy Storage) is presented with enhanced grid power quality. The positive sequence components of the three phase grid voltages are evaluated for the estimation of the unit templates and the reference grid currents. The EV and battery energy storage are connected at DC link using a bidirectional buck-boost converter. During the daytime, EV takes power from the solar array while in its absence it consumes the power from the grid. Additionally, when the system is connected to the grid, the point of common coupling voltages synchronizes with the voltages of the grid. Tests are conducted on a hardware prototype developed in the laboratory for the validation of the satisfactory response under different dynamics conditions.

Modelling of Bi-Directional Buck-Boost Converter for Electric Vehicle

Abstract: The rapid growth of electric vehicles (EVs) has necessitated the development of efficient and versatile energy storage systems. In this study, we present the modelling and implementation of a switching bi-directional buck-boost converter based on electric vehicle hybrid energy storage. The proposed converter offers a flexible and reliable solution for managing energy flow between different storage elements in an EV, such as batteries and ultra-capacitors. First, a comprehensive mathematical model of the converter is developed, taking into account the dynamic behaviour of the energy storage components. This model enables us to analyse and optimize the converter's performance in terms of efficiency, voltage regulation, and power delivery capabilities. Furthermore, simulation studies are conducted to validate the accuracy of the model and assess the converter's performance under various operating conditions. Based on the modelling and simulation results, a practical implementation of the converter is carried out using high-quality electronic components. The design considerations, including component selection, circuit layout, and control strategy, are discussed in detail. The implemented converter is then evaluated experimentally to validate its performance and verify the effectiveness of the proposed modelling approach. The results demonstrate that the switching bidirectional buck-boost converter effectively manages the energy flow between the different storage elements in the hybrid energy storage system. It achieves high conversion efficiency, voltage regulation, and power transfer capabilities, enhancing the overall performance and range of electric vehicles. The developed model and implementation provide valuable insights for the design and optimization of similar converter topologies for electric vehicle applications. Overall, this study contributes to the advancement of energy storage systems in electric vehicles, facilitating the adoption of sustainable and efficient transportation solutions in the future

Development and Application of an Energy Management System for Electric Vehicles Integrated with Multi-input DC-DC Bidirectional Buck-Boost Converter

The rise in environmental pollution, demand for fossil fuels, and higher fuel economy vehicles has raised concerns about the creation of new and efficient transportation vehicles in recent days. These days, most developments in electric vehicles concentrate on making the vehicles more pleasant to ride in. Nonetheless, the emphasis now should be on energy and its most efficient use. To do this, you must give your attention to the origin of the automobile. The answer to this problem may be found in hybrid energy storage systems (HESS). This work is concerned with the design and implementation of an effective energy management system in electric vehicles (EVs) equipped with an active HESS consisting of a battery and a super capacitor via the incorporation of load sharing into this hybridization under a variety of load demand scenarios. To address the demands of high fuel efficiency vehicles, automotive firms are focusing on the development of diesel-engine operated vehicles, electric vehicles, fuel-cell vehicles, plug-in electric vehicles, and hybrid electric vehicles. A Multi-input Bidirectional Buck-Boost (MIB3) DC-DC converter is proposed in this dissertation to provide a greater conversion ratio to the input DC voltage. The multi-input converter recommended has fewer components and a simpler control method, making it more trustworthy and cost-effective. This converter also has bidirectional power flow functionality, making it suitable for charging the battery during regenerative braking in an electric or hybrid vehicle. Three different energy sources are used in the suggested topology: a photovoltaic (PV) panel, a battery, and an ultra-capacitor

A Single-Magnetic Bidirectional Integrated Equalizer Using Multi-Winding Transformer and Voltage Multiplier for Hybrid Energy Storage System

A single-magnetic bidirectional integrated equalizer using the multi-winding transformer and voltage multiplier for the hybrid energy storage system is proposed. The multi-winding transformer and voltage multiplier, driven by the current ripple of the inductor in the bidirectional buck-boost converter, are used for the battery string and supercapacitor string voltage balance, respectively. Compared to the previous balance circuits, for the schedule of the proposed equalizer, only one winding and one diode are used for each battery. Meanwhile, one capacitor and two diodes are used for each supercapacitor, simplifying the balance circuit. This method has the advantages of low cost, suitable for cells with different voltage levels, multiplexed converter switches, and extremely simple structure. It does not have any active switch for the voltage balancing function. A prototype for four supercapacitor cells and four batteries is set up. The results show that the proposed circuit balances the HESS when the DC-DC converter works, which verifies the theoretical analysis.

Analysis and Control of an Input-Parallel Output-Series Connected Buck-Boost DC–DC Converter for Electric Vehicle Powertrains

Many electric vehicle powertrains use a boost type dc-dc converter to step-up the battery voltage for optimization and improving vehicle performance. The converter allows variation of inverter dc-link voltage to further reduce losses. By focusing on boost operation only, previously proposed drivetrains have not fully utilized the benefits of variable dc-link. This paper describes a new non-isolated bidirectional dc-dc converter capable of voltage step-down as well as high-gain voltage step-up operation. Such wide voltage range operation can lead to improved efficiency of electric vehicle drivetrains. The proposed converter comprises two non-inverting buck-boost modules, configured to operate in various optimized modes depending on the load requirement. Compared to existing bidirectional buck-boost converters, the proposed converter offers lower switch stress, reduced converter size and better efficiency. The operation of the converter in different modes is described in detail, followed by small-signal modeling and an outline of the control scheme. Experimental results obtained in an all-SiC 5 kW prototype show stable operation while the converter emulates the behaviour of the dc-dc stage in a variable dc-link EV powertrain under the ECE 15 drive cycle. The prototype demonstrated peak efficiencies of more than 98.5% and 98% for voltage step-up and step-down operations, respectively.