W. Razia Sultana
Bio: W. Razia Sultana is an academic researcher from VIT University. The author has contributed to research in topics: Maximum power point tracking & Inverter. The author has an hindex of 1, co-authored 5 publications receiving 3 citations.
••03 Sep 2020
01 Jan 2021
TL;DR: In this article, the authors presented a case study of application of dragonfly algorithm, a recently developed swarm intelligence algorithm, inspired by the static and dynamic swarming behaviors of dragonflies, to improve the efficiency of solar photovoltaic (PV) systems.
Abstract: The demand for various sources of energy is unpredictably escalating in an astonishing rate. Conventional energy sources have started declining at a tremendous rate due to this increased demand. Environmentalists have started worrying about the future and have initiated many steps in order to fulfill present demands and also make sure that we do not compromise with the upcoming generations. Solar energy, one of the clean form energies found till date, is still a researchable topic among all scholars. Photovoltaic arrays use MPPT techniques in order to achieve high power even at undesirable environmental conditions. This helps the arrays to operate in the MPP region more often. This paper presents a case study of application of dragonfly algorithm, a recently developed swarm intelligence algorithm, inspired by the static and dynamic swarming behaviors of dragonflies, to maximum power point tracking (MPPT), to improve the efficiency of solar photovoltaic (PV) systems. The search for more techniques to tap solar energy has been a thirst among various researchers around the world. A conventional MPPT algorithm, incremental conductance method, was utilized for comparison with dragonfly algorithm in this paper. The results were evaluated and compared under different testing conditions, such as partial shading conditions. It was observed that dragonfly algorithm outperforms incremental conductance method and improves system efficiency. The dragonfly algorithm also seems to have an upper hand over other conventional methods as well.
15 Jul 2020
01 Jan 2021
TL;DR: In this article, the authors provide an overview simulation and brief discussion about model predictive control of quasi-z-source inverter in shoot-through case and also non-shootthrough case.
Abstract: This paper provides an overview simulation and brief discussion about model predictive control of quasi-z-source inverter in shoot-through case and also non-shoot-through case. Model predictive control strategy related with different tasks related to closed-loop control of voltages and currents such as current across inductor and voltage across capacitor provides high dynamic performance and is useful toward controlling of power converters and drives. The steady-state and transient conditions are analyzed for both buck and boost case with experimental results. This approach improves overall performance of inverter and reduces switching losses of inverter.
••01 Jan 2021
TL;DR: In this paper, a power distribution board (PDB) was designed to achieve the primary goal of supplying power to various systems of the race car keeping in mind the overall design concept-reliability, performance and efficient packaging.
Abstract: The power distribution board (PDB) was designed to achieve the primary goal of supplying power to various systems of the race car keeping in mind the overall design concept-reliability, performance and efficient packaging. Our power distribution system was subdivided into four parts—switching regulator, buck, overvoltage protection circuit and overcurrent protection circuit. The buck circuitry had been designed to provide filtered 5 V supply to various sensors and microcontrollers employed in the car. Subsequently, the overvoltage protection circuitry was designed to protect the buck from getting damaged due to failure of other subsystems, and the overcurrent protection circuitry was designed to protect the subsystems from getting damaged due to spikes caused by short circuits or failures of various components employed in the car. The switching regulator had been employed in the race car to control the actuation of engine-related components. All these circuitries were integrated into a single power distribution board (PDB) to manage the overall power distribution within the car, following which, thermal analysis techniques were employed to examine the PDB. Various heat dissipation techniques like the employment of thermal vias were used to minimize the effect of heat within the PDB. The systems deployed greatly increased the efficiency and reliability of the power distribution module of the car. This effort was motivated by the requirement of Pravega Racing, VIT University's official Formula Society of Automotive Engineers (SAE) Combustion team to deploy a reliable and efficient PDB for distribution of low voltage (LV) power throughout various components of the car.
TL;DR: An accurate online parameter estimation method is proposed for lithium-ion batteries (LIBs) to increase the accuracy of the battery model and an adaptive sliding observer is developed to estimate the SOC and capacity based on the proposed parameter estimator.
TL;DR: The proposed adaptive battery model is developed based on a second order equivalent circuit model, which has a good representation of lithium‐ion batteries dynamics and can significantly improve the fault diagnosis accuracy of batteries.
TL;DR: In this article , a modified firefly algorithm was proposed to obtain the maximum power point condition in a solar photovoltaic (PV) system. But due to the low efficiency of the resulting photoelectric power, the proposed algorithm outperforms all traditional algorithms such as firefly and perturbation and observation technique.
Abstract: Abstract Solar photovoltaic (PV) cells play a major role as natural, renewable energy sources. It is characterized by having nonlinear photoelectric voltage and current characteristics. These properties depend on the amount of solar radiation and temperature. PV can be used as an electrical charge circuit. But due to the low efficiency of the resulting photoelectric power, it should operate in conditions of maximum power point. There are several algorithms for achieving this maximum power point condition. In this paper, a PV system is proposed to obtain the maximum power point using a modified firefly algorithm. The modifications have been made both in fireflies’ locations and their random movement. Several simulations are implemented using MATLAB to verify the performance of the proposed system. From the simulation results, the proposed algorithm outperforms all traditional algorithms such as firefly and perturbation and observation technique. Moreover, the impacts of some variants of the proposed technique are studied. The variants are the number of the fireflies, the randomness, the maximum iterations, and the effect of changing the sampling time. A proposed modified firefly is presented with an MPPT controller in the PV system to ensure operating the PV at the MPP. Additionally, the mathematical expressions are explained. Moreover, MATLAB simulation programs are done to compare the performance of the proposed scheme with other related ones.
06 Jul 2008
TL;DR: In this article , the state estimation of Li-ion batteries can be precisely predicted using Artificial Intelligent methods, which can be combined with a battery management system to improve electric vehicle performance.