Narrow Results

The lifecycle of the battery is mostly exaggerated by the overall energy throughput speed, accumulated heat, and rapid utilization. The adequate utilization and operation of the battery are improved in the flexibility range by the permutation of the battery and the ultracapacitor in the electric vehicle. The overall system performance is determined by the energy management system which plays a significant part in dual-energy storage systems. The major intent of this research is to enhance the performance of electric vehicles which is achieved by maintaining the charge of depleting and charge of sustaining level in the battery and the state of charge in the ultracapacitor. The proposed method controls the state of charge of the battery and the ultracapacitor to make sure the availability of charge throughout the complete settling rate of the battery in the electric vehicle. To attain this condition, the dual converter-based two-stage Artificial Neural Network is initialized. In the first stage of the Artificial Neural Network, the charge sustained in the ultracapacitor is controlled during acceleration which completely depends on the velocity of the vehicles. In contrast to that, in the second stage of the Artificial Neural Network, charge depleting in the UC is trained by connectionless with varying vehicle velocities at deceleration rates. The production and investigation of parameters are not effectively optimized using conventional methods hence the herding and howling characters are combined together and proposed energetic and problem-solving optimization-based metaheuristic algorithm that efficiently tunes the parameters. The SOC rate of the battery for three driving cycles using the proposed method follows FTP75 71.309% at 2474th s and J1015 attained 90.840% at 660th s and the UDDS attained 81.647%. The SOC rate of the Ultracapacitor for three driving cycles using the proposed method follows FTP75 63.518% at 2474 s, J1015 attained 69.332% at 660 s and UDDs attained 67.049%.

The experimental arrangement is executed in MATLAB-Simulink. The state of charge of the battery and the ultracapacitors for the varying drive cycles as FTP75, J1015, and UDDS are experimentally validated and verified with the prevailing methods. The developed method reveals better performance for enhancing the lifespan of the power storeroom system in electric vehicles.

Numerous studies have recently focused on enhancing the efficiency of solar chimney power plants (SCPP) and increasing their output power during periods of limited solar radiation. One such study proposes a novel solution: combining an SCPP with a gas power plant to create a hybrid power plant that generates power consistently, day and night. The system involves burying pipes underground and channeling the hot gas from the gas power plant through them, rather than releasing it into the atmosphere. This process increases the temperature of the soil beneath the canopy, which in turn raises the air temperature and the velocity of the air. The resulting decrease in air density leads to an increase in output power. Our results show that the performance of solar chimney of soil ground with buried pipe is about 30% higher than sand domain.

By using the density functional theory (DFT), we explored ferromagnetic and electronic transport aspects of CaM₂S₄ (M = Ti, Cr) spinels. For both spinels, we used PBEsol generalized gradient approximation (GGA) to investigate structural parameters and noted that studied spinels are good compared with the existing parameters. A novel exchange correlation potential, modified Becke and Johnson (mBJ), was utilized for the investigation of electronic, magnetic and transport aspects because we assure our predicting results of electronic bandgap to be consistent to the experiments. The energy difference between ferromagnetic and nonmagnetic states is calculated to check the structural stability of ferromagnetic state. Further, the calculations of band structures and density of state have been explored to check ferromagnetic nature of semiconductor spinels that was further confirmed on the basis of exchange splitting energy and magnetic parameters. In addition, exchange constants ($N_0\alpha$ and $N_0\beta$) and crystal field energy $(E_{\mathrm{\text{cry}}}=E_{t2g}-E_{\mathrm{\text{eg}}})$ along with magnetic moments were also calculated. Our calculated results of magnetic parameters indicate that these spinels are considered as suitable candidate for spintronic applications. Furthermore, to check the reliability of these spinels in energy storage systems, the electronic transport aspects were calculated in detail.

A non-metallated porphyrin, 5,15-di([2,2′-bithiophen]-5-yl)-10,20-diphenylporphyrin (BTPP) has been synthesized and utilized as an electrode material for lithium organic batteries (LOBs). Benefiting from the bipolar characteristics of the porphyrin core and extended $\pi$-conjugation with bithiophene units, BTPP displayed as cathode material a discharge capacity of 128 mAh. g${}^{-1}$ at a current density of 0.2 A. g${}^{-1}$, with an average discharge voltage of 3.2 V and showed a good rate capability. At a high current density of 10 A. g${}^{-1}$, it delivered a discharge capacity of 32 mAh. g${}^{-1}$.

Recently, the Distributed Generation (DG) structure has become an important aspect of daily planning and has achieved a variety of functions while maximizing the functionality of utilities. It should balance the energy equilibrium of the system components and the production limit. Uncertainties arise during the operation of the DG, represented by generator power, load requirements and fluctuations in electricity prices. The reactive power problem is the major concern associated with the DG system. This paper analyzes both DG and an energy storage system along with their optimal performance using a specific algorithm. For optimal analysis of DG and ESS, an Improved Artificial Bee Colony Algorithm (IABC) is proposed. The IABC evaluates the performance of distribution network. It takes DG and ESS into account for analyzing optimal design problems, the main goal of which is to minimize their reactive power dispersion functions. In addition, there are barriers to reducing the DG’s operating costs. The proposed method is implemented on the MATLAB platform and tested using the IEEE 33-bus system. To confirm the effectiveness of the proposed method, it will be compared with the existing methods such as artificial bee colony (ABC) and levy-based method, respectively.

This work presents a prototype flywheel energy storage system (FESS) suspended by hybrid magnetic bearing (HMB) rotating at a speed of 20000rpm with a maximum storage power capacity of 30W with a maximum tip speed of 300m/s. The design presented is an improvement of most existing FESS, as the design incorporates a unique feature in that the upper and the lower rotor and stator core are tapered which enhances larger thrust and much lower radial force to be exerted on the system. Without any adverse effect being experienced by the model. The work also focuses on the description of developing a prototype FESS suspended by HMB using solid works as a basis of developing in the nearer future a more improved FESS suspended by HMB capable of injecting the ever increasing high energy demand situation in the 21st century and beyond.