ASHWINI KUMARI P
@reva university
Assistant Professor/EEE
REVA UNIVERSITY
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment, Computer Science, Control and Optimization
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
P. Ashwini Kumari, C. H. Hussaian Basha, Rajendhar Puppala, Fini Fathima, C. Dhanamjayulu, Ravikumar Chinthaginjala, Faruq Mohammad, and Baseem Khan
Springer Science and Business Media LLC
AbstractSolar Photovoltaic (SPV) technology advancements are primarily aimed at decarbonizing and enhancing the resiliency of the energy grid. Incorporating SPV is one of the ways to achieve the goal of energy efficiency. Because of the nonlinearity, modeling of SPV is a very difficult process. Identification of variables in a lumped electric circuit model is required for accurate modeling of the SPV system. This paper presents a new state-of-the-art control technique based on human artefacts dubbed Drone Squadron Optimization for estimating 15 parameters of a three-diode equivalent model solar PV system. The suggested method simulates a nonlinear relationship between the P–V and I–V performance curves, lowering the difference between experimental and calculated data. To evaluate the adaptive performance in every climatic state, two different test cases with commercial PV cells, RTC France and photo watt-201, are used. The proposed method provides a more accurate parameter estimate. To validate the recommended approach's performance, the data are compared to the results of the most recent and powerful methodologies in the literature. For the RTC and PWP Photo Watt Cell, the DSO technique has the lowest Root Mean Square Error (RMSE) of 6.7776 × 10–4 and 0.002310324 × 10–4, respectively.
P. Ashwini Kumari and P. Geethanjali
AIP Publishing
K. R. Deepa, Nayana shetty, N Shamala, P. Ashwini Kumari, R. Likitha, and K. A. Manohar
Springer Nature Switzerland
Ravishankar H, Deepa K R, Savitha B. Hosur, Manjunatha B, Ashwini Kumari P, and Nanditha Varshini E
IEEE
Wireless communication has been one of the highly emerged technologies in mankind, especially broadband wireless access is one of the popular and highly effective solutions for providing broadband service at a lower price. However, certain issues degrade the Quality of Services such as scheduling, uplink, and bandwidth allocation; researchers have worked hard in these areas, optimize these mechanisms, and achieved significant results. However, these mechanisms ignored the stability of the model and the control parameter impact. Model stability plays a significant role as the number of SS aka subscriber stations and users increases, the model becomes unstable, and this affects the QoS. Hence considering the drawback of the existing model. Here, novel and particular mechanism is developed for model stability and analyze the control parameter effect for achieving high QoS. model evaluation is carried out by considering the parameter such as packet transmission and throughput on different number of the subscriber station and total number of users in the model. Moreover, proposed mechanism achieves double the performance of the existing model.
Ashwini Kumari P, Pradeep Kumar S, Manohar K A, Sagar B S, Parameshachari B. D, and Deepa K. R
IEEE
Lithium-Ion batteries are used popularly in many technologies used in day-to-day life. Engineering research on Lithium-Ion battery efficiency assessment is underway due to its large size acceptance. This paper develops the SOC estimation using the data driven method. Recurrent Neural Network based implementation is developed using the dataset val-ues obtained from a experimental data of 3Ah bat-tery LG HG2. Parameters including voltage, current, temperature, average voltage and average current is observed in the experiment available for research. A dataset that includes different battery parameters with temperature, voltage and current are mapped to the State of Charge of the battery. This dataset is used to train the Recurrent Neural Network in this paper for SOC estimation. The major goal of this research is to establish the appropriate Recurrent Neural Net-work (RNN) design procedure for a SOC estimator. Performance evaluation of the algorithm this used is done and tabulated. Python scikit learn toolbox is used to develop the algorithm and results is found to be satisfactory.
Bansilal Bairwa, ShriHarinayaka P, Sagar B S, and Ashwini Kumari P
IEEE
The aim of this project is to examine the impact of aging, on various types of electric vehicle batteries. This ambient temperature range from 0 degrees to 50 degrees has been considered, this wide range of temperature shows the arctic to desert areas for electric vehicle operation. In this investigation mainly lead-acid batteries, lithium-ion batteries, nickel-cadmium batteries, and nickel metal hayride batteries have been considered. Various types of drive cycles have been used to check the battery age for electric vehicle applications. The proposed work has been performed with the help of MATLAB Simulink, the obtained results show good agreement with published work in the same domain. Results have been compared with published literature for batteries.
Ashwini Kumari Puttaramaiah and Purushothaman Geethanjali
Institute of Advanced Engineering and Science
The depletion of fossil fuels and rising environmental concerns have paved the way for the development of clean renewable energy sources. Photovoltaic (PV) cells are represented by electrical equivalent circuits. Finding the right circuit model parameters for PV cells is critical task. Estimating accurate parameters helps in better performance assessment, control, efficiency calculation and maximum power point tracking. This manuscript describes a new approach for obtaining PV system parameters using ensemble of constraint handling techniques (ECHT) with evolutionary algorithms (EA). Four distinguished technologies of solar PV cells are considered to estimate the parameters with best accuracy. Experiments reveal that ECHT outperforms each individual constraint handling approach by competing with state-of-the-art algorithms. The experimental data for these Kyocera cells is compared with estimated values obtained from the proposed algorithm using MATLAB 2021B for different irradiation. The performance plots show excellent match between the real and simulated values. The root mean square error (RMSE) values for research tax credit RTC France were found to be 7.325513*10-4 and Kyocera processing the normalize RMSE of 0.414%. On comparison with recent algorithms the proposed method achieves the lowest root mean square error (RMSE) meeting the main objective of proposed work.
H. Rajini, Adithya Ballaji, S. Saahithi, Manish Bharat, and P. Ashwini Kumari
AIP Publishing
S. Saahithi, Manish Bharat, H. Rajini, K. M. Bhargavi, and P. Ashwini Kumari
AIP Publishing
Ashwini Kumari P, Pradeep Kumar. S, Divya B V, Latha N, Rajini H, and Saahithi S
IEEE
Power electronic inverters are gaining extensive attention in various industrial drive applications. Incorporating renewable energy sources with energy storage devices with efficient power electronic converters overcomes the major difficulties associated with carbon foot prints. Multi-level inverters are designed to achieve high power ratings, with reduced number of switches. Many of the researchers are focusing on issues that can minimize harmonics in order to obtain higher voltage levels. In this paper 13 level symmetric multi-level inverters, having a reduced number of switches by using particle swarm optimization technique, capacitors, diodes, are compared with other topologies and are simulated using MATLAB. Microcontroller is used to develop the required gating pulses for the inverter switches. The prototype hardware is developed which generates 13 level output voltage and the effectiveness was demonstrated using harmonic analysis with THD of 3.36%.
Viswanatha V, Ramachandra A. C, Sathisha B M, Ashwini Kumari P, Venkata Siva Reddy R, and Srinivasa Murthy R
IEEE
In this paper, the communication between Arduino Mega microcontroller and mini thermal printer is implemented by hardware and software integration. The microcontroller is programmed to transfer the data from microcontroller to printer using a serial communication protocol such as universal asynchronous receiver and transmitter (UART) via Serial communication devices such as MAX232 converter, DB9 connector which is nothing but RS232 serial port, and universal serial bus (USB) communication port. Data sent by the microcontroller is made to print from the printer and it is shown in the result section. Digital pins '3' and '4' on the microcontroller are used as virtual Rx and Tx serial lines while leaving the main serial port open for debugging purposes. Interfacing between UART of microcontroller, MAX232, serial port, and the USB port of printer are well established with the complete schematic diagram. The mini thermal printer prints whatever is sent by the microcontroller. A simple code similar to the one used for the serial monitor works for the printer. The baud rate needs to be set at 9600 for the microcontroller to communicate with the printer. The system is designed to print data wirelessly using Bluetooth HC05 for restaurant and hospital management applications. The system has high adaptability. It can be used in many situations not only for restaurant and hospital management.
Deepa K R, Chaitra A S, Jhansi K, Anitha Kumari R D, Ashwini kumari P, and Mallikarjun M Kodabagi
IEEE
The internet of things (IOT) was developed to provide internet-based remote access, monitoring, and control of home equipment. When the Internet of Things is applied to the home, it transforms a simple home into a smart home that is safer and more automated. Now a day’s in Worldwide the use of advanced technology using smart automation is exponentially increasing in residential sector. One of the biggest worries for designers, property owners, and builders is the possibility of a fire. There have been individual sensors utilized to detect fire for a long time, but they are unable to determine the degree of fire and make emergency response teams aware. To address this issue, the fire department, medical services, and local police stations are all notified of the fire simultaneously, protecting valuable properties and lives. Algorithms for machine learning are used to interpret signals from integrated detectors, such as heat, smoke, and flame to determine the fire's potential and distributing the anticipated result via GSM modem and IoT technologies to numerous parties. Structured for quick edge detection has also been employed to condense and forecast output. The developed end product also has reduced false alerts, which makes the system more reliable.
Ashwini Kumari P, Pradeep Kumar. S, Deepa K. R, P Geethanjali, Bansilal Bairwa, and Ravishankar H
IEEE
Electrical properties derived from the current– voltage (I–V) and power-voltage (P-V) characteristics of solar cells provide essential information about performance losses and device efficiency. Accurate evaluation of model parameters is desirable for predicting the performance of solar cell under varying climatic conditions. The conversion efficiency of a photo voltaic cell depends on various parameters of the cell such as light generated current, diode saturation current, series resistance, shunt resistance and ideality factor. This paper addresses two approaches to extract the parameters of single diode model. The error analysis proves the need for parameter estimation whose reliability depends on various assumption and energy conversion rations. The effectiveness of modelling is investigated using MATLAB/SIMULINK which clearly reveals that the numerical methods are best suited for parameter estimation under stochastic environmental condition. An experimental analysis was carried out on a 75 Watt Mono-crystalline photovoltaic. Finally, a low cost prototype of solar lawn cutter was proposed as a potential application to incorporate the promising sustainable technology
Viswanatha V, Ramachandra A. C, Venkata Siva Reddy R, Ashwini Kumari P, Srinivasa Murthy R, and Sathisha B M
IEEE
Digital technologies empower the transformation into data-driven, intelligent, agile, and autonomous farm operations and are typically considered a key to addressing the grand challenges in agriculture. To avoid unscientific water supply for plantation as well as to save the water and also yield the better crop, therefore, to increase production efficiency out of smart irrigation and to send the status of irrigation at standard environmental conditions, The Internet of Things (IoT) based prototype is designed and implemented. The prototype automatically turns ON /OFF the motor pump based on the moisture level of the soil by taking the temperature and humidity of the environment near the plantation into consideration (In India, the standard parameters for watering the vegetable plantation are Humidity>60%, Temperature < 25°C and Humidity<40% ). The prototype is designed with an ESP32S microcontroller with DHT 11 and a moisture sensor. Arduino IDE development tool is used for programming ESP32S using embedded C programming language. The prototype is configured, programmed, and connected to the Arduino IoT cloud. The data of temperature, humidity, and moisture are received via message queuing telemetry transport (MQTT) protocol on IoT cloud through public IP therefore the data can be accessed worldwide. The authorized person can access the data and control the motor pump from anywhere across the world. The test data obtained out of the prototype over the cloud and at the system are presented in the result section.
Pradeep Kumar S, Ashwini Kumari P, Manjunath Lakkannavar, Subhra Chakraborty, Ramachandra A C, and Dinokumar Kongkham
IEEE
In the beginning, it is important to show that a smaller number of range estimations will likely be enough to offset the time-changeability of range inhabitance and the veiled station issue. In order to improve the precision of spectrum recovery detection, I'd like to second the idea of framework plan detection. Simulators are used to validate our theoretical findings and show that collaboration increases the likelihood of identification even when each auxiliary client provides only a few estimates. Furthermore, show that it is sufficient to consider a subset of close-by optional customers in order to obtain comparable results. It is suggested to use a conveyed compressive inspecting technique, which takes less estimates when conquering, for acceptable wideband spectrum sensing.
Bansilal Bairwa, C N Raghu, P Ashwini Kumari, and Sujo Oommen
IEEE
Power quality problem is a very big problem in power system, some equipment is installed in the power system to solve it, among them dynamic voltage restaurateur is one of the best equipment. Many types of control techniques can be installed in dynamic voltage restaurateurs. Three types of control methods have been adopted in this research work. Various types of the control techniques such as PI control technique, PR control technique, and hysteresis control technology has been investigated. In this study, two major effects of power quality have been taken, which include voltage sag and voltage swell. These two power quality problems are included up to 30 percent, which is solved through all three methods. Based on the analysis of control technology, the “PI control” method is the best method for Dynamic Voltage Restorer. In this study, Designed control strategies using PI PR Hysteresis controller, with comparative analysis for the implemented for the DVR. PI PR control strategies are designed for medium-level voltage and Hysteresis control strategy design for low-level voltage.
B V Divya, N Latha, and P Ashwinikumari
IEEE
Nowadays IOT is used for monitoring the system data online. Data can be accessed by different users from any place to control different parameters of the machine using sensors. This paper focuses on online control of speed and temperature for given single phase induction motor. The Simulation of inverter for controlling the speed is carried out using PSIM. Data acquisition system collects information from the sensors and is stored in cloud. Further this data can control and monitor the power consumed by individual load.
P. Ashwini Kumari and P. Geethanjali
Springer Singapore
Ashwini kumari P, Byregowda B K, Vijayakumara Y M, Ravikumar H R, Dr S N Sheshappa, and Pradeep Pradeep
Seventh Sense Research Group Journals
P. Ashwini Kumari and P. Geethanjali
Elsevier BV
P. Ashwini Kumari and P. Geethanjali
Elsevier BV