7 research outputs found
Integration of Photovoltaic-Based Transformerless High Step-Up Dual-Output–Dual-Input Converter with Low Power Losses for Energy Storage Applications
No full textThe synchronous integration of numerous input and output loads is possible with multi-input (MI) and multi-output (MO) DC–DC converters. In this paper, the non-isolated DC–DC converter described, which has a high step-up capability and multiple ports for outputs and inputs for energy storage system (ESS) applications. The voltage level of the converter is changeable. The capacity to provide the large voltage increases with a low duty cycle portion, the ease with which each duty cycle can be controlled, and minimal power losses are all advantages of the proposed design. The proposed system offers advantages for applications requiring energy storage. In the continuous conduction mode (CCM), the operation principles, steady-state evaluation, and extracting of the voltage and current coefficients are performed. The supply sources can be inserted or withdrawn without causing a cross-regulation issue in the proposed converter. Ultimately, the functionality of the proposed structure is examined using simulation and the laboratory prototype that has been implemented. The proposed converter achieved 94.3% efficiency at maximum power. In addition, the proposed converter attained minimum losses with a difference of 28.5 W when compared to a conventional converter
Real time SOC estimation for Li-ion batteries in Electric vehicles using UKBF with online parameter identification
No full textAbstract In the recent era, Lithium ion batteries plays a significant role in EV industry due to their high specific energy density, power density, low self-discharge rate, and prolonged lifespan. Modeling the battery precisely and estimating its State of Charge with great precision is essential to improve the performance of the lithium-ion batteries. Though numerous methods has been proposed for estimating the SOC, accurate estimation approach is not proposed yet since all these approaches consider the discrete-time dynamics of the battery. Hence in this proposed approach, the implementation of Thevenin 2RC battery model in conjunction with the Unscented Kalman Bucy Filter (UKBF) for SOC estimation is suggested. Thevenin 2RC battery model is used to captures the nonlinear relationship between the battery’s voltage, current, and SOC. The UKBF is then used to estimate the SOC by fusing the battery model with noisy measurements of the battery’s voltage and current. The UKBF is able to handle the nonlinearity of the battery model and the noise in the measurements, resulting in a more accurate estimate of the SOC by capturing the continuous-time dynamics of the battery. The model is simulated in Matlab Simulink. With similar covariance noise and measurement noise taken into consideration, the battery’s SOC is estimated using the EKF, UKF, and UKBF. The performance comparison indicate that the UKBF approach provides an accurate estimation of the SOC, with a significantly lower RMSE of 0.003276
Intelligent RBF-Fuzzy Controller Based Non-Isolated DC-DC Multi-Port Converter for Renewable Energy Applications
No full textIn this article, a multi-port non-isolated converter is implemented for renewable energy applications. High voltage gain is accomplished with a switched capacitor and coupled inductor, and power transfer between the inputs, battery, and load can be realized using three power switches. The power collected in the leakage inductance is reused to decrease the voltage stress on the power switch. Various functioning periods are also examined, and design requirements are offered. The proposed converter uses fewer parts to realize power flows and obtain high voltage gain compared to comparable converters. Additionally, under partial shading conditions, the traditional maximum power point tracking (MPPT) approaches are not able to collect the global maximum power point (MPP) from the numerous local MPPs. This work proposes an artificial neural-network-based MPPT technique with variable step size for tracing speed, MPP oscillations, and operating efficiency. The proposed converter experiment is also constructed and successfully tested in a laboratory environment
A Review on Hydrogen-Based Hybrid Microgrid System: Topologies for Hydrogen Energy Storage, Integration, and Energy Management with Solar and Wind Energy
No full textHydrogen is acknowledged as a potential and appealing energy carrier for decarbonizing the sectors that contribute to global warming, such as power generation, industries, and transportation. Many people are interested in employing low-carbon sources of energy to produce hydrogen by using water electrolysis. Additionally, the intermittency of renewable energy supplies, such as wind and solar, makes electricity generation less predictable, potentially leading to power network incompatibilities. Hence, hydrogen generation and storage can offer a solution by enhancing system flexibility. Hydrogen saved as compressed gas could be turned back into energy or utilized as a feedstock for manufacturing, building heating, and automobile fuel. This work identified many hydrogen production strategies, storage methods, and energy management strategies in the hybrid microgrid (HMG). This paper discusses a case study of a HMG system that uses hydrogen as one of the main energy sources together with a solar panel and wind turbine (WT). The bidirectional AC-DC converter (BAC) is designed for HMGs to maintain power and voltage balance between the DC and AC grids. This study offers a control approach based on an analysis of the BAC’s main circuit that not only accomplishes the function of bidirectional power conversion, but also facilitates smooth renewable energy integration. While implementing the hydrogen-based HMG, the developed control technique reduces the reactive power in linear and non-linear (NL) loads by 90.3% and 89.4%
Smart hybrid power management system in electric vehicle for efficient resource utilization with ANN
No full textThe novel hybrid power system integrating energy storage, electric vehicle (EV) charging infrastructure and renewable energy sources improve sustainability and resilience. This work proposes a power management system controlled by artificial intelligence for EV charging infrastructure. The battery’s state of charge (SoC) is continuously monitored by artificial neural network (ANN) algorithm improves the health of the battery and efficient operation of the system. The buck boost DC-DC converter performs dynamic switching mechanism, which adjusts to changing solar conditions and energy demands, guarantees a steady power supply. Depending on the situation, the ANN algorithm used in the battery’s SoC control mechanism decides whether to priorities the EV charging or the inverter to supply the grid. The work is evaluated with the MATLAB simulation for different conditions and results are compared with different controllers such as PI, PID, and ANN. The experiment performed uses internet of things (IoT) for transferring the data from the EV motor, acts as an input for the controller to perform the novel hybrid power management operation with cloud technology. The experimental prototype evaluates the results connected to the photovoltaic (PV) system and battery management system (BMS) which lowers reliance on non-renewable resources, increases overall energy efficiency, and ensures a steady supply of power under a various condition
Analysis and validation of multi‐device interleaved DC‐DC boost converter for electric vehicle applications
No full textAbstract In Electric Vehicle (EV) application, voltage conversion is significant to obtain the desired operating voltage from the source voltage. A conventional boost converter can handle such applications, but it may add losses throughout the conversion process. This work focuses on the design and implementation of a multi device Interleaved DC‐DC converter with greater voltage gain, lower voltage stress across the switch, and improved efficiency when compared to the standard Boost converter and conventional Interleaved Converter. The suggested converter has three times the voltage gain of a standard Boost DC‐DC converter. These converters are used in applications that demand a constant DC voltage, such as electric vehicles. The proposed converter's mathematical modelling and modes of operation are discussed. The proposed DC‐DC converter's feasibility is validated using real‐time simulation (OPAL‐RT), and the results are presented in detail
Analyzing the Electronics of Image Sensors and Their Functionality to Develop Low Light-Emitting Source Image
No full textBioluminescence imaging has been used to visualize the biological effects of human beings and is a promising technique in a recent modality. In this study, the digital image technique is used to improve quality and recover images. The optical fluence that emerges from the source is generated using a camera, and a low resgolution is observed. In this paper, the diurnal change of ultra-weak photon emission was successfully imaged with an improved, highly sensitive imaging system using a charge-coupled device (CCD) camera. The changes in energy metabolism might be linked with diurnal changes in photon emission, and when observed, the body emits extremely weak light spontaneously without external photoexcitation. Therefore, to obtain accurate information, a combined Barn Door Star Tracker approach has been proposed to improve the accuracy of the method and has been implemented to test on celestial bodies. The ability to temporally assess the location of star movement can be monitored accurately with bioluminescence imaging
