Single Ended Primary Inductance Converter Research Articles

Performance evaluation of bridgeless isolated SEPIC-Luo converter for EV battery charging using PI and ANN controller

Electric vehicle (EV) rechargeable battery packs that employ traditional power factor correction (PFC) circuit design have performance limitations due to their substantial conductivity loss that ensures at the input of a diode bridge rectifier (DBR). This study suggests a bridgeless (BL) isolated single ended primary inductance converter (SEPIC) - Luo converter to address the problem. As a result, the input current exhibits a power factor operation of unity throughout the charging process. DBR elimination and current conduction through a remarkably small number of circuits both significantly reduce conduction losses. The use of an artificial neural network (ANN) and proportional integral (PI) controller enhances the converter's performance with a stable DC link voltage. The suggested converter overall operation is thoroughly described in terms of variety of operating modes and simulation-based effectiveness. Here, with the assistance of the hysteresis current controller (HCC), the input current disruptions are reduced. Constant current and voltage management is used to successfully charge the EV battery, resulting in improved efficacy and inherent PFC. By utilizing simulation outcomes achieved from MATLAB, the performance of proposed BL isolated SEPIC-Luo in boosting the power quality of EV charger system is examined.

Investigation of a power factor correction converter utilizing SEPIC topology with input current switching

The single-ended primary-inductor converter (SEPIC) is a popular converter topology that can be employed in diverse application fields where the needed output voltage is greater or lesser than the input voltage. The non-inverted output voltage of a SEPIC converter provides additional advantages when compared to a buck-boost or Ćuk converter. Furthermore, the position of the capacitor in the SEPIC converter provides inherent isolation and circuit safety. One drawback in the conventional bridge-diode SEPIC AC-DC converter is the lack of controllability which can be overcome by adding extra active switch(es) or by replacing the passive diode(s) with active switch(es). However, introducing more active switches increases the control complexity and may increase the requirement for additional driver circuits. To address this trade-off, this article proposes a single-phase AC to DC modified SEPIC converter with input current-switching capability without adding any extra active switch(es). The existing active switch of the DC-DC SEPIC converter was shifted towards the input side and thus no additional switch has been introduced. This allows the option of input-current switching without any additional complexity in the control or driver circuit. The circuit topology, principles of operation, and ideal voltage gain equations for the suggested circuit have been derived and included in this research work. The proposed circuit has been simulated in both open-loop conditions and closed-loop control with varying duty cycles and output load. Results from the simulation show that the proposed converter provides better efficiency (∼90 %) and lower total harmonic distortion (THD) (10 %) for varying duty cycles when compared to a conventional converter. The converter also shows good dynamic response. A low-power 15V hardware prototype has been built to experimentally validate the performance of the proposed converter. Experimental results illustrate that the suggested converter can improve the power factor by up to 0.968 while operating at an efficiency above 75 %. This converter topology can be suitable for applications where high output voltage gain, high power factor, and lower THD are needed without isolation requirements.

Optimized virtual impedance solar restoration droop emulated SEPIC controller under low irradiation

This paper is focused on PV-based reduced order pade’s approximation SEPIC (single-ended primary inductor converter) virtual Impedance, restoration controller with parallel impedance emulation condition. However, the complexity of the higher-order SEPIC controller has been reduced and compared using Pade’s approximation with different reduction techniques. It covers the time response, oscillation, overshoot, dynamic performance, and controller stability. The computational time and need of the sensor are less, and better responses occur compared to the other reduction technique under the solar irradiance variation. However, in PV, the dynamic resistance is generalized by a nonlinear solar I–V (current–voltage) curve dependent on the operating point, such as irradiance, temperature, and its I–V curve. The nonlinearity effect affects the stability of the system. The SEPIC outer voltage and inner current controller with virtual impedance controller enhance the stability, and comparative response is demonstrated through the bode plot. A virtual impedance controller (VIC) cascaded with voltage restoration minimizes the voltage notching and oscillations under variation of inertia coefficients. The transient and dynamic performance of reduced order using a genetic algorithm controller has been used to demonstrate and discuss the PV-SEPIC system’s stability.

Approaches for Maximizing Maximum Power Point Tracking and Evaluating Operational Constraints in Photovoltaic Systems

Abstract: Optimization techniques have broad utility in multiple engineering fields, including activities such as modeling, system identification, parameter estimation, forecasting, and control of intricate systems. This innovation emphasizes the use of optimization approaches to control the performance of Photo-voltaic (PV) array systems. The main difficulty lies in the nonlinear correlation between current and voltage (I-V) characteristics of PV arrays, resulting in variations in the location of the Maximum Power Point under varied climatic circumstances. It is crucial to track this Maximum electricity Point efficiently in order to collect the highest amount of electricity possible from the photovoltaic devices. Maximum Power Point Tracking is a tracking procedure that optimizes power generation by dynamically altering the operating voltage to coincide with the MPP. In order to tackle this difficulty, the paper suggests a unique two-stage Maximum Power Point Tracking technique. The initial phase applies the Weightless Swarm Algorithm to evaluate the Maximum Power Point in an offline manner. The subsequent phase employs an online Adaptive Perturb & Observe technique to continuously track the MPP in real-time. In addition, an Approximate Single Diode Model is created to quickly assess the output power. In order to verify the suggested method, computer simulations are performed utilizing a Maximum Power Point Tracking system that is combined with a Single-Ended PrimaryInductor Converter

Nonlinear controller for SEPIC with single variable to tune

This work proposes a systematic approach to design a novel integral sliding mode controller (ISMC) for a single-ended primary-inductor converter (SEPIC) with only one tunable parameter where the upper and the lower bounds are derived. The designed surface results in a minimal chattering behaviour at the output voltage as well as at the duty cycle and allows for operating the SEPIC at a fixed switching frequency. The proposed controller can withstand up to a 70% variation in the input voltage and 100% variation on the load side in addition to superior performance for a cold start. The proposed controller and the corresponding mathematical formulation were simulated in a Simulink environment and experimentally tested via a scaled prototype. The proposed controller performance is also compared to a Type-II and integral Linear-Quadratic Regulators (LQR).

Enhancing MPPT performance for partially shaded photovoltaic arrays through backstepping control with Genetic Algorithm-optimized gains

As the significance and complexity of solar panel performance, particularly at their maximum power point (MPP), continue to grow, there is a demand for improved monitoring systems. The presence of variable weather conditions in Maroua, including potential partial shadowing caused by cloud cover or urban buildings, poses challenges to the efficiency of solar systems. This study introduces a new approach to tracking the Global Maximum Power Point (GMPP) in photovoltaic systems within the context of solar research conducted in Cameroon. The system utilizes Genetic Algorithm (GA) and Backstepping Controller (BSC) methodologies. The Backstepping Controller (BSC) dynamically adjusts the duty cycle of the Single Ended Primary Inductor Converter (SEPIC) to align with the reference voltage of the Genetic Algorithm (GA) in Maroua’s dynamic environment. This environment, characterized by intermittent sunlight and the impact of local factors and urban shadowing, affects the production of energy. The Genetic Algorithm is employed to enhance the efficiency of BSC gains in Maroua’s solar environment. This optimization technique expedites the tracking process and minimizes oscillations in the GMPP. The adaptability of the learning algorithm to specific conditions improves energy generation, even in the challenging environment of Maroua. This study introduces a novel approach to enhance the efficiency of photovoltaic systems in Maroua, Cameroon, by tailoring them to the specific solar dynamics of the region. In terms of performance, our approach surpasses the INC-BSC, P&O-BSC, GA-BSC, and PSO-BSC methodologies. In practice, the stabilization period following shadowing typically requires fewer than three iterations. Additionally, our Maximum Power Point Tracking (MPPT) technology is based on the Global Maximum Power Point (GMPP) methodology, contrasting with alternative technologies that prioritize the Local Maximum Power Point (LMPP). This differentiation is particularly relevant in areas with partial shading, such as Maroua, where the use of LMPP-based technologies can result in power losses. The proposed method demonstrates significant performance by achieving a minimum 33% reduction in power losses.

Analysis and circuit design of isolated forward SEPIC converter with minimum-phase stability

Purpose Conventional isolated dc–dc converters offer an efficient solution for performing voltage conversion with a large improved voltage gain. However, the small-signal analysis of these converters shows that a right-half-plane (RHP) zero appears in their control-to-output transfer function, exhibiting a nonminimum-phase stability. This RHP zero can limit the frequency response and dynamic specifications of the converters; therefore, the output voltage response is sluggish. To overcome these problems, the purpose of this study is to analyze, model and design a new isolated forward single-ended primary-inductor converter (IFSEPIC) through RHP zero alleviation. Design/methodology/approach At first, the normal operation of the suggested IFSEPIC is studied. Then, its average model and control-to-output transfer function are derived. Based on the obtained model and Routh–Hurwitz criterion, the components are suitably designed for the proposed IFSEPIC, such that the derived dynamic model can eliminate the RHP zero. Findings The advantages of the proposed IFSEPIC can be summarized as: This converter can provide conditions to achieve fast dynamic behavior and minimum-phase stability, owing to the RHP zero cancellation; with respect to conventional isolated converters, a larger gain can be realized using the proposed topology; thus, it is possible to attain a smaller operating duty cycle; for conventional isolated converters, transformer core saturation is a major concern, owing to a large magnetizing current. However, the average value of the magnetizing current becomes zero for the proposed IFSEPIC, thereby avoiding core saturation, particularly at high frequencies; and the input current of the proposed converter is continuous, reducing input current ripple. Originality/value The key benefits of the proposed IFSEPIC are shown via comparisons. To validate the design method and theoretical findings, a practical implementation is presented.

Evaluation of PV-based Buck-Boost and SEPIC Converters for EV Charging Applications

In recent decades, environmental issues have become an area of greatest concern due to changes in global climate conditions. The transportation sector is a major contributor to carbon dioxide emissions, accounting for more than 22.9% of total carbon dioxide emissions. At present, most vehicles run on gasoline/diesel as fuel which is unsustainable and unviable as fossil fuels produce carbon emissions and fuel costs are rising. To address these issues, electric vehicles (EVs) offer an attractive solution as alternative to internal combustion engine vehicles that use electricity as an energy source. It is logical to use renewable energy to charge vehicles, which makes renewable energy an end-to-end clean energy source. In electric vehicles, energy conversion plays an important role. In the energy conversion process, alternating current (AC) can be converted to direct current (DC), or direct current can be converted to alternating current. In EV fast charging applications, DC-to-DC conversion is used, which requires DC-to-DC converters. In this paper, a detailed evaluation of the Buck-Boost and Single-Ended Primary Inductance Converters (SEPIC) with PV as input is analyzed for EV charging applications to make it end-to-end clean energy. For this purpose, a 5-by-5 PV system with a Buck-Boost, SEPIC converters with particle swarm optimization technique is considered, which is simulated in a MATLAB/SIMULINK environment. The simulation results showed that the ripples in output are minimal in SEPIC which supports the smooth and efficient charging of EV battery.

LIFETIME PREDICTION OF SINGLE-STAGE LED DRIVER CIRCUIT USING BAYESIAN BELIEF NETWORK

In light-emitting diode (LED) lighting, the driver commands the lifetime and the LED bulb. It is essential to predict the driver's lifetime during its design stage. This paper proposes a viable method to predict the lifetime of the LED driver based on its failure rate. A novel single-ended primary inductor converter (SEPIC) integrated parallel ripple cancellation circuit (PRC) topology of 30 W is considered to estimate the lifetime of the driver circuit. The failure rate model is regarded as a base to predict the lifetime of LED drivers using Bayesian belief network (BBN) analysis. The weakest links are the prime components to estimate the lifetime, and they are active devices and capacitors employed in the driver circuit. The output capacitor is considered a degree of importance as per the existing literature, and the proposed course has been designed without using any electrolytic capacitor (EC) to enhance the reliability of the driver circuit. This approach ensures an effective way to access the mean time to failure (MTTF) or the lifetime of the LED driver in a lucrative manner.

Robust control of a single-ended primary inductor converter using adrc technique

Control of a single-ended primary inductor converter (SEPIC) is a challenging task as it is a fourth-order non-linear system. In this paper, an active disturbance rejection control (ADRC) scheme is proposed for the SEPIC converter with a high switching frequency. Selection of the observers and controller bandwidth is done according to the maximum sensitivity requirement to achieve robust performance towards varying input voltage and load. The effectiveness of the suggested ADRC is shown by calculating power and efficiencies for different loading conditions.

Modeling and design of a photovoltaic‐fed single‐ended primary‐inductor converter for maximum power point tracking with current mode control

SummaryIn this work, the control of a Single‐Ended Primary‐Inductor Converter (SEPIC) supplied from a photovoltaic energy source and linked at its output to a DC current sink is addressed. The system is used for maximum power point tracking under varying environmental conditions. A strategy based on two loops of control is considered. A peak current mode controller is used for the inner loop, and a Proportional‐Integral (PI) controller is used for the outer voltage loop. Then, a comprehensive time‐domain and frequency‐domain modeling of the inner loop is theoretically addressed and then verified by the switched model of the system implemented in PSIM© software. The obtained results show that the system exhibits accurate tracking of the desired PV voltage while guaranteeing a fast maximum power point tracking under sudden changes in the environmental conditions. The mathematical modeling, design procedures, and the numerical simulations are validated using experimental results obtained from a laboratory prototype.

Adaptive terminal synergetic-backstepping technique based machine learning regression algorithm for MPPT control of PV systems under real climatic conditions

This paper deals with a comparative evaluation of nonlinear controllers based on the linear regression technique, which is a machine learning algorithm for maximum power point tracking. In the past decade, most photovoltaic systems have been equipped with classical algorithms such as perturb and observe, hill climbing, and incremental conductance. The simplicity of these techniques and their ease of implementation were seen as the main reasons for their utilization in photovoltaic systems. However, researchers’ attention has recently been attracted by artificial intelligence-based techniques such as linear regression, which offer better performance within the bounds of the nonlinearity of photovoltaic system characteristics. An adaptive terminal synergetic backstepping controller is developed in this paper for a single-ended primary inductance converter. This control scheme is based on the combination of a non-singular terminal synergetic technique with an integral backstepping technique and equally a neural network for the approximation of unmeasured or inaccessible variables that guarantees the finite-time convergence. The proposed controller was further verified under virtual and real environmental conditions, and the numerical results obtained from Matlab/Simulink software under various test conditions, including load variations, show that the adaptive terminal synergetic backstepping controller gives satisfactory performance compared to the adaptive integral backstepping controller used in the same climatic conditions.

Solar photo voltaic based hybrid CUK, SEPIC, ZETA converters for microgrid applications

The emergence of converters has triggered a paradigm transfer in the field of power electronics. Recently, DC/DC converters have predominantly employed alternative energy sources and become viable technologies for low- and high-power applications. The DC/DC converter is crucial in power conversion within renewable energy systems, such as hydro, solar photovoltaic (PV), fuel cells (FC), and wind. Its primary role is to modify the voltage and current levels to meet the system's requirements. This article comprehensively examines CUK, ZETA, and single-ended primary-inductor converter (SEPIC) in several phases, including enhancing efficiency, achieving cost-effective operation and mitigating switching losses. Furthermore, this study overviews each converter's operational modes and efficiency-output power comparison. This article compares integrating solar PV and FC technologies into various converters.

Soft Switching Technique in a Modified SEPIC Converter with MPPT using Cuckoo Search Algorithm

Abstract:: MPPT refers to the process of continuously tracking and adjusting the operating point of a photovoltaic (PV) system to maximize the power output from the solar panels. The operating point at which a PV system produces the most power under a specific set of environmental circumstances is known as the maximum power point (MPP). The Maximum power point tracking (MPPT) technique is used to overcome the challenges of PV arrays with variable irradiance levels, which collects the greatest power from the PV array. Standalone PV systems, as well as gridconnected systems, can benefit from a DC-DC converter with MPPT. This study compares the standard perturbation and observation (P&O) technique with the soft-switching method used in the SEPIC converter utilizing the cuckoo search (CS) algorithm using MATLAB/Simulink. Reviewing the simulation results and assessing the SEPIC converter's performance. Background:: SEPIC soft-switching converter, the soft-switching technique is applied to the SEPIC converter topology. It typically uses additional components, such as inductor and capacitors, to enable soft-switching operation. These additional components help to control the voltage and current waveforms across the main switching devices, reducing switching losses. Methods:: The proposed method uses a soft switching technique to reduce switching losses and to improve efficiency. Soft switching is used in SEPIC (Single Ended Primary Inductor Converter) converters, a type of DC-DC converter, to enhance their performance. The projected solution further addresses the maximum power point tracking (MPPT) issue in PV systems using the Cuckoo Search (CS) method. Results:: Soft switching technique is implemented in SEPIC converters to reduce these switching losses. In this system, Zero Voltage Switching (ZVS) involves turning on the switch when the voltage across it is zero. This allows the current to flow through the switch without creating any significant switching losses. CS algorithm can track the MPP quickly and accurately, it exhibits less prone to oscillations, easily monitor the MPP under a variety of weather circumstances. However, it exhibits negligible oscillation in a steady state, which results in significant power savings. Conclusion:: The modified SEPIC converter with a soft-switching MPPT cuckoo algorithm is used with a solar-powered system. A prototype comprising a solar panel, a SEPIC converter, a driver, and a controller circuit was created. A soft-switching SEPIC converter with an MPPT cuckoo algorithm for the PV system is implemented, as are the converter operation, converter analysis, and theoretical analysis, and a controller circuit is analysed. The PV system, MPPT controller with tracking algorithm, and PMSM load were used in the system simulation. A 60-watt SEPIC converter prototype is built, and the outcomes are also tested experimentally.

A Gallium Nitride Based High Bandwidth, Extended Single-Ended Primary Inductance Converter, for Fast Balancing of Ultracapacitors

Ultracapacitors (UCs) are the preferred choice for specific power requirements. Series and parallel of UCs are required to match the required voltage and power, as the available voltage range is 2.5 to 3 VDC. Passive and active balancing is inevitable here, while some demand, high bandwidth control for fast balancing and stable operations. A novel Extended-Single Ended Primary Inductance Converter (E-SEPIC) is used to actively balance the UCs. A new, simple and effective method is formulated to achieve a higher Degree of Balancing of UCs. A two-stage E-SEPIC with Silicon (Si) and Gallium Nitride (GaN) switch based are demonstrated with an input of 12 VDC to balance up to 3 VDC UCs at the output for high bandwidth and high-power density properties. An effective method of emulating impedance of UCs using Hybrid Electro-chemical Impedance Spectroscopy is evolved. The devised novel method of balancing is effective in height of balancing with GaN based converter exhibiting higher bandwidth of around 30 kHz around 18 times better, with increased efficiency of 12% with an improved power-density of 8.25 times in comparison with that of Si based. This contribution of GaN properties in electrical performance enhancements has influenced the design of Power Electronics applications.

Design of Sepic Converter Using PID Controller

Abstract: Single-Ended Primary Inductor Converter (SEPIC) is widely used in battery charging of renewable energy and electric/hybrid vehicles due to its output gains range flexibility,less complex switching design, providing an isolation by capacitor and producing non-inverted output. This project presents a modified PID controller to obtain excellent dynamic performance with zero steady-state error. The controller design is discussed and built in discrete model simulation on MatlabSimulink. The effectiveness of the proposed modified PID control strategy is tested for the transient cases in step-changed reference voltage, and varying input voltages. The results show the proposed controller can reach zero steady-state error and produce lower ripple in voltage.

Designing a battery Management system for electric vehicles: A congregated approach

In many high-power applications, such as Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs), Battery Management System (BMS) is needed to ensure battery safety and power delivery. BMS performs cell balancing (CB), State of Charge (SoC) estimation, monitoring, State of Health (SOH) estimation, and protective operation. To safeguard and optimize battery performance, required essential functionalities must be enabled. To optimize battery system performance, safety, and longevity, including temperature management, cell balancing, and communication protocols. This article provides an architecture that includes both a hardware demonstration and a simulation of the continuous on-time control approach for systematic measurement of Voltage, current, and temperature in EVs. A single-ended primary-inductance converter (SEPIC) DC-DC converter, Analogue Front End (AFE), and balancing circuits provide the optimal supply for proposed congregated BMS process. The effectiveness of proposed congregated design performance is validated through meter and sensor measurements for voltmeter, current, and temperature. The numerical error between proposed BMS and conventional measurements is relatively low for voltage (0.09 V), current (0.05 A), and temperature (0.09 °C). In the end, the simulated results and hardware results are benchmarked that the proposed congregated BMS design can regulate temperature, prevent overcharging and over-discharging, and balance the battery cells inside a given battery module.

PID-Based control of sepic power stage with QS bacterial-based search algorithm for renewable energy applications

In response to the growing need for efficient power conversion in renewable energy applications, this study addresses the issue of harmonic distortion and low Power Factor (PF) values caused by non-linear loads, such as electronic devices. Low PF results in reduced efficiency, increased energy consumption, and higher costs for both consumers and utilities. Active correction, typically involving an active circuit implemented using a power converter, provides an optimal solution by offering high performance, precise regulation, and low harmonic distortion. This research proposes a Power Factor Correction (PFC) solution utilizing an Interleaved DC-DC Single Ended Primary Inductance Converter (SEPIC) for the power stage and a Proportional Integral Derivative (PID) controller for the control block, tuned by a Quorum Sensing (QS) bacterial-based search algorithm. The PID controller parameters are derived using a frequency-domain approach, which presents advantages such as reduced design complexity, improved stability margins, and enhanced SEPIC performance. Simulation results indicate reduced overshoot, settling time, rise time, and Total Harmonic Distortion (THD) percentage, as well as increased efficiency and power factor nearing unity. The proposed scheme also demonstrates improved dynamic performance for variations in load, line, and reference voltage. Owing to its high efficiency, precise voltage regulation, and minimized impact on the electrical grid, this solution is well-suited for renewable energy applications, where optimizing energy conversion and ensuring stable operation are crucial for the overall performance of renewable energy systems.

Average current mode controller for bridgeless PFC SEPIC converter with second-order model reduction operated in continuous conduction mode.

This paper proposes an average current mode controller (ACMC) for a single-phase bridgeless power factor correction (PFC) circuit using a single ended primary inductor converter (SEPIC) via second-order model reduction. The superiority of the proposed controller is PFC accomplished at power up to 350 W with high efficiency via the second-order model reduction. The design and implementation of ACMC on the converter operated with continuous conduction mode (CCM) is explained in detail. ACMC forces input current to follow sinusoidal current reference at different power levels and sustain high power factor (PF). The proposed controller is designed based on the theoretical analysis operation of the circuit. For verification, MATLAB/Simulink simulations are carried out and validation through an experiment test rig for 110-220 Vrms input, 100 Vdc/ 350 W output prototype at 20 kHz switching frequency. It is proven that the proposed controller strategy accomplishes high PF, high efficiency and conformity with the simulation.

Design and Implementation of Closed Loop SEPIC Converter for PV System Based Smart Home Application

The design, simulation, and analysis of the Single- ended primary-inductor converter (SEPIC), one of the least known Switch mode power converters, are presented in this study. By adjusting the switching element's duty cycle, this dc-dc converter may be utilized as a buck-boost converter. With minimal strain on components, SEPIC offers the specific benefit of offering positive polarity output voltage and ripple-free input and output current. This contrasts with conventional buck-boost converters, which have negative polarity output voltage along with extremely irregular currents and increased component stress. This makes it perfect for both commercial and personal uses, such as smart home gadgets that use PV energy. Under various input circumstances, extensive simulation has been performed in continuous conduction mode (CCM) utilizing SIMULINK-MATLAB. A PI controller has been added to optimize the responsiveness, reduce steady state error, and keep the output voltage constant. The SEPIC converter's hardware implementation verifies the simulation's findings.