Bidirectional DC-DC Converter Research Articles

Bidirectional DC-DC Converter and Improved Electrical Vehicle Dynamic Response Control

Background: In automotive applications where bidirectional power flow is necessary to lighten the power system, dual active bridge (DAB) converters are frequently employed. Variations in the required output voltage, erratic input voltage, and shifting loads all have an impact on this converter. As a result, converter performance has to be improved. To increase efficiency, the current stress of the DC-DC converter must be optimised. This paper proposes a control scheme for the coupled inductor bidirectional DC-DC (CIB DC-DC) converter utilising both model predictive control (MPC) and a proportional-integral (PI) controller. The integration of these control techniques aims to enhance the performance and efficiency of the converter. Methods: The MPC algorithm is employed to predict the converter's future behaviour based on a dynamic model, taking into account system constraints and performance criteria. By optimising the control action over a finite time horizon, the MPC algorithm ensures an optimal response, considering the current state and anticipated changes. Additionally, a PI controller is incorporated to augment the control strategy. The proportional component of the PI controller enables a fast initial response to the error between the desired and actual converter outputs. The integral component eliminates steady-state errors and provides robustness against disturbances, resulting in improved overall system performance. Results: The proposed control scheme is implemented and evaluated through simulations and experimental tests on a prototype converter. The results demonstrate the effectiveness of the combined MPC and PI controller approach. Conclusion: The coupled inductor bidirectional DC-DC (CIB DC-DC) converter using MPC can provide precise control of power flow between two voltage domains, enabling efficient bidirectional power transfer. The predictive capabilities of MPC allow it to adapt to varying load conditions and respond quickly to changes, ensuring stable operation and accurate regulation of voltage and current. Overall, the coupled inductor bidirectional DC-DC converter controlled using MPC over PI offers improved performance, efficiency, and flexibility compared to traditional control methods. MPC can handle the complex dynamics response and non-linear characteristics of the converter, making it suitable for bi-directional vehicle charging applications, where precise control and high efficiency can be achieved.

A bidirectional power converter connecting electric vehicle battery and DC microgrid

One way to increase electric vehicle (EV) battery utilization is to connect it to a dc microgrid. The EV battery can assume the role of an energy storage from the grid point of view. A bidirectional DC-DC converter will be needed to transfer power between them back and forth. This paper proposes the converter design considering its functional objective, including interleaved phase number determination. Efficiency performance evaluation is presented by power loss analysis with the parasitic-parameters consideration of the components. Finding optimum switching frequency based on power loss analysis is performed independently between input and output sides of the converter. Finally, experiments using a scaled-down prototype are shown to verify the analytical analysis of the converter. The experimental results properly validate the power loss analytic analysis carried out in this paper with a maximum error of 2.04% at 1131-watt, 60 V battery voltage, and 140 V grid voltage. Maximum efficiency 96.97% is obtained at 301-watt, 130 V battery voltage, and 151 V grid voltage. Overall, the converter has a simple structure, capable to be operated in various levels of input and output voltages with a minimum battery side current ripple.

Investigation on implementing the swarm nano grid system for effective utilization of solar-powered agro-industries

The agro-industry is the backbone of the global economy, even in the twenty-first century. The agro-industry would not be what it is now without irrigation. The production and use of renewable energy in this sector of the agricultural economy have also expanded rapidly in recent years. Base-load power production and conversions dominate the literature. This research examines user concerns. The swarm nano grid system fixes this. The pulse width modulation (PWM) sinusoidal inverter converted stable DC power from the bidirectional DC-DC converter into sinusoidal AC voltage for the irrigation pump induction motor. Solar panels, batteries, and converters are costly, but they pay off. The nano grid distributes excess power generated during low demand to local loads. This technique works well when the load can be disconnected from the power grid. MATLAB is used to keep an eye on the reliability and efficiency of the induction motor. In the first simulation, solar power generation is modeled using the MATLAB Simulink software in two distinct modes. A PWM sinusoidal inverter that is driven by solar energy is what provides power to the 5.67 kW induction submersible motor. The simulation result provides a conceptual model of how induction motors powered by renewable energy sources function in practice.

Experimental investigation of bidirectional series resonant DC-DC converter in different operating modes

This paper presents a study of bidirectional series resonant DC/DC converter. The main operating modes of the converter with phase-shift control technique are observed. An experimental survey with a laboratory model of such type of converter working over the resonant frequency is made. The functionality of the studied device operating in a wide area of loading is demonstrated with waveforms of the main parameters. The conducted measurements are used to build the experimental output characteristics of the converter. A similarity of the experimental results with the theoretical are denoted, and the ability to achieve current source characteristics for the whole range of loading is proven. The possibility of the studied converter for operation both in forward and reverse modes of energy flow is proved, which positions the device as an appropriate variant for implementation in the storage system control area.

A regulatory power split strategy for energy management with battery and ultracapacitor

Electric vehicle batteries face fast degradation due to the high frequency of charging/discharging cycles and great peak power demands. Lifetime, continuity of supply and power density of these batteries affect the performance of electric vehicles (EVs). Hybrid energy storage systems (HESS) offers a feasible solution by incorporating other energy storage elements like ultra-capacitor (UC) along with battery. Their combination provides higher efficiency and better performance in terms energy/power density. UC can behave like a power buffer when the EV is accelerating and regenerating. The HESS needs a controller that can split the available power between different sub systems as per demand. This paper presents a regulatory control strategy useful in HESS with battery and UC for the speed regulation of a brushless DC (BLDC) motor using a 3-port bidirectional DC-DC converter. The regulatory control strategy monitors the state of charge (SOC) of UC and a fuzzy logic controller regulates the power flow between HESS and the motor. Simulation in MATLAB validates the efficacy of the strategy. Simulation results and hardware evaluation confirm that the regulatory control scheme is effective in splitting the available power according to the load demand and achieves better energy efficiency.

A novel hybrid PI–backstepping cascade controller for battery–supercapacitor electric vehicles considering various driving cycles scenarios

AbstractThe integration of supercapacitors as hybrid energy storage systems in electric vehicles has attracted the attention of many researchers and has been considered as a promising solution. Bidirectional DC/DC converters (BDDCs) play a fundamental role in HESS, as they manage the power flow by controlling currents and regulating the DC bus voltage. However, they encounter the challenge of uncertainties and high fluctuation power loads, necessitating the fast dynamics, stability, and high robustness of the controller. This paper proposes a novel hybrid proportional–integral and backstepping cascade controller to regulate the DC‐bus voltage under uncertainties and load variations, and to control the current references of the on‐boarded sources. To confirm the asymptotic stability of the whole system, a nonlinear stability analysis is conducted using the Lyapunov theorem. A power management strategy is applied to distribute the power loads and generate reference currents for the BDDCs controller. Simulations results under various driving cycles using MATLAB/Simulink demonstrate the superiority of the proposed controller compared to conventional proportional–integral and backstepping controllers. A real‐time controller‐hardware‐in‐the‐loop test bench is developed to validate the effectiveness of the proposed strategy.

Isolated bidirectional DC-DC Converter: A topological review

Bidirectional DC-DC converters (BDCs) are certainly an important power electronic converter for managing bidirectional power flow in various applications. It offers the ability to flow power in both directions, which is useful in systems with renewable energy sources and energy storage. BDCs are becoming increasingly important in various applications, including renewable energy systems, electric vehicles, and energy storage. The development of new BDC topologies and control strategies is expected to further improve their efficiency and performance. Non-Isolated Bidirectional DC-DC Converters (NBDCs) and Isolated Bidirectional DC-DC Converters (IBDCs) are the two main types of BDCs with different isolation properties and trade-offs in terms of size, cost and performance. Topological classification of BDCs further distinguishes various BDC types based on their configurations and voltage-boosting techniques. IBDCs are preferred over NBDCs due to high-power applications, and wide voltage range with higher efficiency; the performance of IBDCs is improving day by day. To provide a framework for comparison in implementing novel configurations or identifying the best converter for a given application, this study is concentrated on each topology and its usual applications. Soft switching converters are also discussed pointed to Resonant Power Converters (RPCs) for the application into Electric Vehicles (EVs). It is worth noting that the choice of BDC depends on the specific requirements of the application, such as power level, voltage range, efficiency, and cost. A detailed comparison, application, advantage and disadvantage table can be useful in comparing the characteristics of different BDCs and selecting the most suitable one.

GaN based isolated bidirectional multiport DC-DC converter for electric vehicle charging

The research work proposes an efficient Gallium Nitride (GaN) based isolated bidirectional DC-DC (IBDC)-Triple Active Bridge (TAB) based multi-port converter (MPC) for electric vehicle (EV) charging. The developed GaN IBDC-TAB based MPC utilizes fewer components compared to conventional IBDC charging system if designed for two output ports. The proposed GaN IBDC-TAB based MPC incorporates one input port, Port 1, and two output ports, Port 2 and Port 3 for Level-1 and Level-2 EV charging systems respectively. In addition, the developed GaN IBDC-TAB can be operated in Single Active Bridge (SAB), and Dual Active Bridge (DAB) modes as per operational requirements. A 12 kW GaN IBDC-TAB based MPC is designed and evaluated using LTspice XVII software. In TAB mode of operation, Port 2 delivers 1.5 kW, and Port 3 delivers 10.6 kW. The maximum efficiency of 98.87 % is obtained in simulation for the MPC converter in TAB mode. For experimental validation, an approximately 1 kW prototype is presented with Port 1, Port 2, and Port 3 voltages as 230 V, 120 V, and 200 V respectively with an operating frequency of 100 kHz. The single-phase-shift control strategy is implemented for controlling the transmitted power in the developed GaN IBDC-TAB based MPC.

A new configuration for enhanced integration of a battery-ultracapacitor system

The principal shortcoming of the batteries in electric vehicles is their limited specific power. The potential solution is having a hybrid energy storage system (HESS) that integrates the ultracapacitor (high specific energy) with the battery (high specific energy), thus ensuring high specific energy and power. Classically, a bidirectional DC-DC converter integrates the two sources, but the converter introduces a delay during the charging-discharging transition of the ultracapacitor. This work proposes a novel converter topology that interfaces the two sources, eliminating an existing transition delay, providing a fault-tolerant operation in case of a switch failure, and efficiently charging the ultracapacitor. Additionally, an algorithm is presented that facilitates energy sharing between the battery and the ultracapacitor, preventing overloading of the battery and ensuring that the ultracapacitor contributes to the peak load demand. The proposed configuration and energy management algorithm are validated experimentally using a 24V laboratory prototype.

Meta Heuristic Algorithm Based Novel Dstatcom Architecture for Power Quality Improvement

Electric utility systems are increasingly favoured as local energy systems due to their ability to integrate renewable energy, improve energy efficiency, and enhance the resilience of the power grid. However, while these benefits are significant, they also present certain complexities related to control and power quality (PQ). PQ is crucial within utility systems to ensure the proper functioning of connected devices and the overall health of the system. Therefore, both voltage quality and current quality are of utmost importance. Control strategies combined with advanced power electronics devices (PED) provide a robust framework to address PQ challenges. This paper introduces a novel approach for constructing a distributed Static Synchronous Compensator (DSTATCOM) utilizing innovative 125-level asymmetric multilevel DC link inverters to enable multilevel operation. A modified 125-level multilevel inverter aimed at enhancing power quality is proposed herein. By employing a minimal number of components, this inverter can generate 125-level voltages per phase, serving as a DSTATCOM to address power quality issues such as sag, swell, and harmonics. Bidirectional DC-DC converters are employed for purposes other than just providing power to the inverter's DC connections replacing DC sources. Additionally, the Coati Optimization Algorithm (COA), a newly introduced metaheuristic approach inspired by observed behavioural patterns in coatis in their natural habitat, is presented. COA is designed to emulate two primary behaviours of coatis: (i) their hunting strategy when pursuing iguanas and (ii) their evasion tactics when confronted by predators. To validate the effectiveness of the Coati Optimization algorithm, simulation is carried out with Matlab Simulink, and the outcomes of the simulation for the proposed scheme are provided in this paper. The efficacy of Solar-PV integrated 125-level asymmetric multilevel DC link inverter in enhancing power quality by adhering to the IEEE-519 Standards is demonstrated.

Bidirectional DC - DC Converter Topology for Electric Vehicles Using Fuzzy Logic Controller

This project organizes an application of hybrid electric vehicle systems operated with novel designed bidirectional dc-dc converter (BDC) which interfaces a main energy storage (ES1), an auxiliary energy storage (ES2) and dc bus of different voltage levels. Proposed BDC converter can operate both step up and step-down mode. In which step up mode represents low voltage dual source -powering mode and step-down mode represents high voltage dc link energy –regenerating mode, both the modes are operated under the control of bidirectional power flow. This model can independently control power flow between low voltage dual source buck/boost modes. Here in, the circuit configuration, operation, steady-state analysis, and closed-loop control of the proposed BDC are discussed according to its three modes of power transfer. In this project fuzzy logic controller is used and also system results are validating through MATLAB/SIMULINK software. Index Terms—Bidirectional dc/dc converter (BDC), dual battery storage, hybrid electric vehicle, Fuzzy logic controller.

Improved Adaptive Network-Based Fuzzy Inference System Approach for Power Flow Analysis in Interconnected DC Microgrid

High-performance power conversion needs are becoming more and more important for microgrid applications. In actuality, many contemporary DC distribution systems use isolated bidirectional dc-dc converters. Hence, in this paper, an Improved Adaptive Network-based Fuzzy Inference System (IANFIS)is developed to control the output power of the components and reduce the variation among the consumption and generation of the power while managing a constant DC bus voltage. This work proposes a power management control strategy that ensures the power balance of a stand-alone DC microgrid where DAB converters link the battery energy storage (BES) unit and the renewable energy source (RES). The generation side, or photovoltaic (PV) system and BES, is coupled to the storage systems and renewable energy sources. Furthermore, a DC microgrid is connected to the load demand. The load demand is compensated with the help of the storage and generation systems with the help of a dual active bridge converter. The DAB is connected with the dual DC microgrid system for managing power flow among the two DC microgrids. This dual active bridge converter is utilized to balance the power among Dual DC microgrids. The proposed methodology is developed to manage the power among generation and load demand management. The proposed method is evaluated on a dual active bridge converter connected microgrid system with the components of PV and BESS respectively.

A Comprehensive Investigation into Bidirectional DC-DC Converters with Soft Switching for Electric Vehicles

Electric vehicles (EVs) are one of the the promising solutions for the environmental issues such as carbon emission and global warming. The high voltage traction battery in EVs is charged from utility grid by an EV charger. The Society of Automotive Engineers (SAE) standardize EV charges into two categories on-board chargers and off-board chargers. Usually, the on-board chargers are located inside the vehicle whereas, off-board chargers are not mounted on the vehicle. For onboard chargers, size and power density of charger become a prior matter of concern. The only way to reduce the size of a converter and thereby increase the power density is to operate power electronic conversion system (PECS) at very high switching frequency (HSF) resulting in reduced size of magnetic component in the charger configuration. However, HSF operation may lead to a high electromagnetic interference (EMI), loss in switch and switch duty. The work in this paper is focused on the development of high frequency bi-directional DC-DC converter (BD2C) stage priory used in on-board chargers due to distributed sources of energy as well as to manage the power distribution in the configuration. The power electronic BDCs are derived from boost and buck unit. The boost derived converter are current fed converters and offers advantages in terms of inherent voltage gain, short circuit protection and lower input current ripple. The voltage spikes across switches, high rated device selection, hard switching, snubber and auxiliary circuit requirements are some of the undesirable factors. This occurrence happened due to unbalance power transfer by the power electronics converter. Similarly, voltage fed converter offers good voltage control during power transfer.

Enhanced energy management of DC microgrid: Artificial neural networks-driven hybrid energy storage system with integration of bidirectional DC-DC converter

Standalone microgrids using Photovoltaic (PV) systems might be a feasible alternative for powering off-grid populations. However, this form of application necessitates the use of energy storage systems (ESS) to control the intermittent nature of PV production. This paper proposes a novel energy management strategy (EMS) based on Artificial Neural Network (ANN) for controlling a DC microgrid using a hybrid energy storage system (HESS). The HESS connects to the DC Microgrid using a bidirectional converter (BC), that enables energy exchange between the battery and supercapacitor (SC). The effectiveness of the proposed approach in relation to the traditional control method is based on performance metrics such as overshoot and settling time. The proposed ANN control attains 18 % overshoot while step increases in PV generation and attains 21 % overshoot while decreasing PV generation. The results show that the proposed control method ensures continuous power supply from the PV system by optimising load balancing under various operating conditions, maintaining state-of-charge (SoC), and improving the voltage profile.

Mode decomposed passivity-based speed control of DC drive with bidirectional Zeta-SEPIC DC-DC converter for light electric vehicles

Currently, light electric vehicles are rapidly developing in various kinds. To power these vehicles with batteries, the simplest electric drive system is a DC motor controlled by a DC-DC converter. This work utilizes a bidirectional Zeta-SEPIC DC-DC converter with an integrated DC motor. This implementation enables control of motor speed and torque in traction and regenerative braking modes. Additionally, it allows for the use of a lower voltage battery compared to the motor's rated voltage, reducing battery weight and increasing safety. In this work, a decomposition approach is applied. Two separate port-controlled Hamiltonian subsystems are obtained to adjust the motor angular velocity in the traction (Zeta) and braking (SEPIC) modes of the DC-DC converter. The Passivity-Based Control (PBC) method is used to synthesize the drive control subsystems in these modes. This method is based on the energy laws of processes in systems and provides asymptotic stability of nonlinear systems, in this case, two fourth-order subsystems for speed control. Two third-order current control subsystems synthesized by the PBC were used to limit the motor current at a given level. The synthesis resulted in sets of possible structures of control influence formers (CIFs) for all PBC subsystems using Zeta and SEPIC DC-DC converters. The study analyzed the operation of the obtained structures of the CIFs, selected the most effective ones, and determined the laws of adaptation of their parameters to the value of the motor angular velocity through computer simulation in Matlab/Simulink. The results of the simulation showed that the drive operated well in both static and dynamic modes.

Energy management strategy for photovoltaic powered hybrid energy storage systems in electric vehicles

Nowadays, electric vehicles (EVs) using additional energy sources frequently deliver a safe ride without concern about the distance. The energy sources including a battery, an ultra-capacitor (UC), and a photovoltaic (PV) are considered in this research for driving the EV. Vehicles that only use battery-oriented technologies experience problems with charging and quick battery discharge. EVs are used with an ultracapacitor to decrease the quick discharge effects and increase the lifetime of the battery. Furthermore, bidirectional DC-DC converters are a type of power electronics device used to verify the smooth transfer of generated power from energy sources to the motor throughout various stages of the driving cycle. Therefore, this study proposes a perturb and observe (P&O) energy management control technique based on tuna swarm optimization (TSO). The suggested TSO-P&O completely uses UC while regulating the battery because it lowers dynamic battery charging and discharging currents. Due to the aforementioned aspect, the suggested TSO-P&O increases battery life and demonstrates a very dependable, long range power source for an electric car. The TSO-P&O technique achieves the EVs by obtaining the maximum speed of 91.93 km/hr. with a quicker settling time of 4,930 ms when compared with the existing zero-fuel zero-emission (ZFZE) method.

A Novel Soft Switching Non-Isolated Bidirectional dc–dc Converter Without Any Extra Auxiliary Switch

In this paper, a new zero-voltage-switching (ZVS) non-isolated bidirectional DC-DC converter without any extra auxiliary switch is introduced. In the proposed converter, by applying an auxiliary circuit, soft switching condition is provided for all semiconductor elements regardless of the power flow direction and without any extra voltage stress. Each of the main switches provides soft switching conditions for the other switch. Additionally, each of the switches can be used as a synchronous rectifier switch in both power flow directions. The auxiliary circuit only consists of two coupled inductors with the converter main inductor and two diodes, which operate with a zero-current-switching (ZCS) condition. Since, all of the converter inductors are implemented on a single core, the presence of coupled inductors doesn’t increase the converter volume considerably. The detailed operating analysis of the proposed bidirectional converter and the design method of the main circuit is presented. Also, the theoretical analysis of the proposed bidirectional converter is verified with a 100W experimental prototype converter.

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.

Disturbance observer-based fixed time control for bidirectional DC-DC converter with input voltage and load uncertainty

The bidirectional DC-DC converter serves a vital role in the energy recovery system of new energy vehicles. However, external interference and parameter uncertainty can easily affect its dynamic performance. A disturbance observer-based fixed time control strategy for bidirectional DC-DC is proposed to address the impact of input voltage and load uncertainty on bidirectional converters. Firstly, the bidirectional converter model undergoes coordinate transformation, and disturbance observers are designed to compensate for input voltage and load disturbances. Secondly, based on the fixed time control theory, a fixed-time controller is devised for the bidirectional DC-DC converter to facilitate fast tracking and adjustment of output voltage without requiring measurement of input voltage and load current. Finally, simulation and experiment evaluations are conducted to assess the proposed scheme’s effectiveness in output voltage regulation.

Development of constant switching frequency model predictive control for DFIG-based wind energy conversion system in standalone and grid connected operation

This paper presents a constant switching frequency (CSF) model predictive control (MPC) for a doubly-fed induction generator (DFIG)-based wind energy conversion system (WECS) in standalone and grid-connected operations. The system comprises a cascade connection of a rotor side converter (RSC) and a grid side converter (GSC) with a common DC-link. A battery energy storage system (BESS) is also connected to the common DC-link via a bi-directional dc–dc converter (BDDC). The RSC is controlled through CSF-model predictive current control (CSF-MPCC) scheme in both standalone mode (SAM) and grid-connected mode (GCM) of operations. The GSC control employs the CSF-MPCC scheme in grid-connected operation, whereas CSF-model predictive voltage control (CSF-MPVC) scheme is implemented in standalone operation. Moreover, the power balance is achieved by controlling the BDDC using MPCC to discharge or charge the BESS in response to surplus or deficient power generation. The effectiveness of the proposed control approach for DFIG-based WECS in both SAM and GCM is verified through MATLAB-based simulation and experimental results under different dynamic conditions like variable wind velocity changing from 12 m/s to 8 m/s, different grid demands from 3 kW to 1.5 kW and load change of 4 kW to 6.5 kW. Moreover, the robustness of the proposed control is corroborated by parametric sensitivity, time delay, and grid unbalance, along with its low-voltage ride-through (LVRT) capability during an LLLG fault.