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9 results on '"S. Amosedinakaran"'

1. Performance Analysis for Battery Stability Improvement using Direct Air Cooling Mechanism for Electric Vehicles

Author

S. Amosedinakaran, R. Kannan, S. Kannan, A. Ramkumar, S. Suresh, and A. Bhuvanesh

Subjects
Battery cooling, Temperature, Performance, E-Vehicle, SOC, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Safety concerns about the battery are primary challenges for the maker of the electric vehicle (EV) system. At continuous work, maintaining the optimal temperature is a crucial scientific issue. It has restricted the widespread use of batteries. Hence, maintaining the optimal temperature for E-vehicles has been analyzed in this study. To achieve more energy density in charging, the discharging cycle and compact structure have been essential. In this study, a direct air-cooling system has been addressed to reduce the temperature of the battery pack, resulting in a significant improvement in system efficiency. The 1.44 kgwatt (kW) battery back has been constructed for the E-vehicle by Simulink diagram to analyze the system. In this study, two various scenarios have been made, such as with air cooling and without cooling, to validate the outcomes. Torque and speed characteristics have been analyzed for this study. Air-cooling-based batteries for e-vehicle simulation have delivered better outcomes, such as high power charging and discharging and a discharge depth of 92%. The differential battery pack temperature has been reduced by increasing the cooling air flow rate to 2 ms−1, 4 ms−1, and 6 ms−1. To attain an even delivery of coolant air flow, a design criterion has been suggested. The outcome of the study has been evaluated through numerical analysis. more...

Published
2024
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2. Simulink and real-time implementation of the E-cycle for measuring the reliability of the model using sensors

Author

T. Viveka, NVS. Sree Rathna Lakshmi, S. Amosedinakaran, A. Bhuvanesh, A.S. Kamaraja, and P. Anitha

Subjects
Reliability, Sensors, Electric-vehicle, BLDC motor, Li-ion battery, Measurement, Electric apparatus and materials. Electric circuits. Electric networks, TK452-454.4
Abstract

Utilization of rechargeable battery based bicycles has been significantly increased in India. In this study, battery powered electric vehicles have been implemented in MATLAB 2013a Simulink and real-time hardware systems. In order to design and integrate a working model of electric cycle, one needs to know about the different components involved in a system, such as lithium-ion batteries, Brushless DC motor (BLDC), and controller systems. The detailed study about the component selection has been described in this study. The drive testing has been implemented in both Simulink and real time respectively. Within a single charging system, the proposed model of electric cycle has been derived up to 25 kilo-meter up to speed of 30 kilo-meter per second respectively. The characteristics of electric vehicles such as torque (N-m) versus time (s), speed (km/h) versus time (s) and distance (km) versus time (s) have been discussed in this study. Based on characteristics study, reliability of the electric vehicle model has been enhanced in electric bicycle system by physical model confirmation. more...

Published
2024
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3. Performance analysis of battery E-vehicle system using open loop and closed loop application

Author

S. Amosedinakaran, M. Mano Raja Paul, S. Kannan, M. Geetha, P. Anitha, and A. Bhuvanesh

Subjects
Sensor, PMAC, speed measurement, E-Vehicle, PID controller, closed loop, Electric apparatus and materials. Electric circuits. Electric networks, TK452-454.4
Abstract

Electric vehicle (E-vehicle) will be an alternate transportation vehicle in this world due to unavailability of fossil fuel. The CO2 emissions from fossil fuel based vehicle have been considerably reduced. In this study, E-vehicle has been modelled for both open loop and closed loop using MATLAB/Simulink. The rechargeable lithium-ion battery has been adopted for proposed system, and it has become prominent energy storage device especially for E-vehicle application. Speed sensor has been incorporated in closed loop system. Speedometer also added in both open and closed loop system. Performance of the E-vehicle has been analysed and compared by ratio of output to input motor power. Error deviation has been estimated. The simulation results of closed loop system have been revealed that better stability in dynamic state of input. The proposed closed loop system has been attained the better efficiency than open loop and, moreover fluctuation and harmonic level were within the tolerance level. Through closed loop system, E-vehicle has been attaining the smooth working state at minimum duration than open loop. The E-vehicle parameters such as vehicle speed, travelling distance, torque, efficiency and output power have been estimated for both open and closed loop system. With help of sensor, performance of the closed loop system has been improved. more...

Published
2024
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5. Energy Source Expansion Planning for a Real-world Deregulated Electric Utility Considering Emission

Author

K. Mala, S. Amosedinakaran, A. Bhuvanesh, S. Kannan, and M. Karuppasamy Pandian

Subjects
Electric utility, Deregulation, Mathematical optimization, Hardware_MEMORYSTRUCTURES, ComputingMilieux_THECOMPUTINGPROFESSION, Computer science, Differential evolution, Electrical and Electronic Engineering, Electricity demand, Energy source, Computer Science Applications, Theoretical Computer Science
Abstract

The Electricity Demand Prediction (EDP) and Generation Expansion Planning (GEP) make a real-world planning problem more optimal. In this study, the EDP problem has been solved using the optimizatio... more...

Published
2021
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6. Generation Expansion Planning for a Real-world Power System: Aiming Towards Cost and Environmental Emission Minimization by Penetrating Huge Renewable Energy Sources

Author

K. Mala, S. Amosedinakaran, M. Karuppasamy Pandiyan, S. Kannan, and A. Bhuvanesh

Subjects
education.field_of_study, Mathematical optimization, business.industry, Computer science, Artificial immune system, Population, Renewable energy, Dynamic programming, Electric power system, Mean absolute percentage error, Differential evolution, Genetic algorithm, Electrical and Electronic Engineering, education, business
Abstract

A power system planning must involve the Electricity demand forecasting (EDF) and Generation expansion planning (GEP) for better operation. The optimal plan should consider both qualitative and quantitative factors such as error, cost and reliability of the power system. In this study, EDF and GEP problem have been solved till the year 2030 for Tamil Nadu, an Indian state. The formulation of EDF problem has been modeled based on the input variables such as population, Gross State domestic product (GSDP) and per capita income, and has been solved using Genetic algorithm (GA), Artificial immune system (AIS) and Differential evolution (DE). While analyzing the results of EDF problem, DE provides optimal result with Minimum mean absolute percentage error (MAPE). Continually, short term (6-year) and long term (12-year) GEP problem have been solved using DE by considering minimization of cost and environmental effects as the main objectives. To achieve these objectives, Renewable Energy Sources (RES) have been integrated in different penetration levels such as 0–10%, 10–20%, 20–30%, 30–40%, and 40–50% on GEP problem and its impacts have been investigated. The results of DE have been validated with Dynamic Programing (DP). The outcomes of the study have assisted the power system planners while decision making in introducing Renewable Energy Sources (RES) on a real-world power system. more...

Published
2021
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7. Electricity Demand Forecasting Using Differential Evolution Algorithm for Tamil Nadu

Author

S. Amosedinakaran, A. Bhuvanesh, K. Mala, and P. Marishkumar

Subjects
Estimation, education.field_of_study, business.industry, Population, Per capita income, language.human_language, Weighting, Product (business), Mean absolute percentage error, Tamil, Statistics, language, Electricity, education, business, Mathematics
Abstract

This paper aims to apply the Differential evolution (DE) to forecast the electricity demand for Tamil Nadu based on population, Gross State Domestic Product (GSDP), and Per Capita Income (PCI). The linear and nonlinear models have been applied to forecast electricity demand. The actual data is partially used to attain the best values of the weighting parameters (years from 1980 to 2005) and the remaining data are used for testing the models (years from 2006 to 2017). Three scenarios have been considered (high, average, and low growth) to forecast the electricity demand for Tamil Nadu till the year 2030. Mean Absolute Percentage Error (MAPE) is the estimation key. The results have been validated with the National Electricity Plan (NEP) of India. more...

Published
2020
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8. Estimation of India's energy demand using artificial immune system

Author

S. Saravanan, S. Amosedinakaran, N. Bhoopal, and K. Karunanithi

Subjects
Estimation, education.field_of_study, Mean absolute percentage error, Artificial immune system, Computer science, Population, Econometrics, Per capita, Trend line, education, Gross domestic income, Gross domestic product
Abstract

This research study presents the prediction of energy demand for India using Artificial Immune System (AIS) based on the input variables such as population, per capita Gross Domestic Product (PC-GDP), per capita Gross Domestic Income (PC-GDI) used during the model development. The Artificial Immune System-Energy Demand (AIS-ED) model is developed based on the available past year data. Two forms of the AIS-ED models are developed and also three different scenarios such that high growth, low growth and trend line are used to predict future energy demand of India. Mean Absolute Percentage Error (MAPE) is validating the performance of the model. The obtained AIS-ED results are compared with the 18th Electricity Power Survey of India. more...

Published
2017
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9. India's electricity demand estimation using Genetic Algorithm

Author

S. Karman, S. Saravanan, S. Amosedinakaran, and C. Thangaraj

Subjects
Estimation, education.field_of_study, business.industry, Population, Trend line, Gross domestic product, Mean absolute percentage error, Economic indicator, Economics, Econometrics, Per capita, Electricity, business, education
Abstract

This study deals with estimation of electricity demand for India using Genetic Algorithm (GA) based on economic indicators. The economic indicators are population, per capita gross domestic product (GDP), import and export. The Genetic Algorithm-Electricity Demand (GA-ED) model is developed based on past data, and different scenarios (low, high growth and trend line) are used to predict electricity demand. Two forms of the GA-ED models are developed to estimate electricity demand. Mean Absolute Percentage Error (MAPE) is used as an evaluation criterion to choose the best-fit GA-ED model and it is used for future electricity demand prediction. The GA-ED results are compared with the prediction of 18th Electricity Power Survey of India. The GD-ED model estimates electricity demand until 2025. more...

Published
2014
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