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Fuzzy controller based boost PFC converter for EV application

The scarcity of fossil fuel and the increased pollution leads to the use of Electric Vehicles (EV) and Hybrid Electric Vehicles (HEV) instead of conventional Internal Combustion (IC) engine vehicles. In EVs and HEVs, a battery is used as the main power source, so that battery charger is treated as the core technology. Battery charger based on a unidirectional non-isolated boost power factor correction (PFC) converter for electric vehicles (EV) is introduced here. This non-isolated high gain boost PFC converter automatically balances the output voltages for an unbalanced load without the need for any additional control strategy or auxiliary circuit. For EV charging application one of the important factors is that the battery chargers should consume sinusoidal current with controlled power factor for contributing to the power quality in the future Smart Grids and high voltage gain for charging the battery. This converter can improve the power quality and can control the output voltage according to the demand of the battery. Due to these advantages, it can be used for electric vehicle charging application. Fuzzy control has been used for switching pulse generation in the converter. The topology has been simulated in MATLAB2014a and the various waveforms were analyzed. The control circuit was implemented using dsPIC30F2010. An experimental prototype of the converter was set up and the results were verified.

Published by: Sajilamol S, Elizabeth Paul, Mohitha Thomas

Author: Sajilamol S

Paper ID: V4I3-1626

Paper Status: published

Published: May 28, 2018

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Research Paper

Soft switching bidirectional DC-DC converter for energy storage systems

Bidirectional DC-DC converters are one of the most important parts of energy storage systems such as in plug-in hybrid electric vehicle (PHEV), the fuel-cell vehicle, renewable energy system, and uninterruptible power supply (UPS). Energy storage systems are used for storing energy and use it during fluctuations or supply outage. To improve its efficiency a soft-switching bidirectional DC-DC converter using a lossless active snubber is used. In this converter, Zero Voltage Switching (ZVS) of the main switches and Zero Current Switching (ZCS) of the auxiliary switches are always achieved by utilizing an active snubber which consists of auxiliary switches, diodes, an inductor, and a capacitor. In addition, by utilizing this active snubber, there is no reverse recovery problem induced by the poor dynamic performance of the MOSFETs body diode. Moreover, by adjusting according to loads, it is possible to achieve optimized overall efficiency throughout the whole loading range. This system is analyzed by the simulation in MATLAB/SIMULINK 2017. Hardware is implemented using dsPIC30f2010 microcontroller for 20W and 20 kHz and results are verified.

Published by: Sreelakshmi K S, Ninu Joy, Deena Mathew

Author: Sreelakshmi K S

Paper ID: V4I3-1618

Paper Status: published

Published: May 28, 2018

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Research Paper

Fuzzy logic based three-level boost converter with Quasi-Z source

For conventional boost converters, switching stress will be more at high gain, in order to alleviate this problem three level boost converters are used. The mismatched voltage levels between the dynamic lower voltage and the required constant higher voltage of the DC link bus of the inverter can be solved using flying-capacitor based three-level boost converter with a quasi-Z source (TLBqZ). The operating principle of wide range voltage-gain for this topology is according to the effective switching states of the converter and the multi-loop energy communication characteristic of the quasi-Z source. The dynamic self-balance principle of the flying capacitor voltage is utilized. An analysis is done on the performance of the converter with PI and fuzzy controller. The fuzzy logic controller is used for switching pulse generation in the converter, as it is more advantageous over PI controller. An H-bridge inverter is fed from the converter that connects to the AC loads. The simulation of the circuit is performed in MATLABR2014a and waveforms are analyzed. An experimental prototype of the converter is implemented using dsPIC30F2010 microcontroller and results are verified.

Published by: Anju Ramesh T, Dr. Siny Paul, Neema S

Author: Anju Ramesh T

Paper ID: V4I3-1619

Paper Status: published

Published: May 28, 2018

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Research Paper

Battery-ultracapacitor hybrid system for electric vehicles using new bidirectional quadratic DC-DC converter

Hybrid energy storage system is used with the objective of taking advantage of the best characteristics of each device, creating a system that is superior, than any of the devices used alone. Due to operational requirements of distributed generation systems, energy storage devices like batteries and super-capacitors, need bidirectional DC-DC converters to allow charge or discharge according to with the necessary conditions. A new battery-ultracapacitor hybrid energy storage system is proposed for electric vehicles. The main objectives of using ultra-capacitors in alongside batteries are: improving performance, increase the system efficiency and extend the battery life. In many applications, conventional bidirectional converters are inadequate since the specified range of input voltages and the specified range of output voltages call for an extremely large range of conversion ratios. A new bidirectional quadratic converter with high voltage gain in both step-down and step-up operation modes is used along with the ultra-capacitor. This converter is also characterized by a simple control technique since it is only necessary to control one power semiconductor for each mode. The additional power semiconductors remain always on or always off. In this project, an Ultra Capacitor is integrated with the battery in an Electric Vehicle using the new bidirectional quadratic buck-boost converter to improve the dynamic performance of the vehicle system and enhancing the battery life. The system model and the implemented control strategy has been simulated in MATLAB/SIMULINK software. The hardware of the proposed system is made. The control strategy is implemented using TMS320F28027.

Published by: Jithin K Mathews, Sija Gopinathan, Sera Mathew

Author: Jithin K Mathews

Paper ID: V4I3-1616

Paper Status: published

Published: May 28, 2018

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Research Paper

Statistical approach to study the lithostratigraphic sequence in the Proterozoic Kolhans

Lithofacies succession in the Proterozoic Kolhan Group has been studied statistically using modified Cross-Association Analysis, Markov chain model, and Entropy function. The lithofacies analysis based on the field descriptions and their vertical packaging has been done for assessing the sediment depositional framework and the environment of deposition. Six lithofacies arranged, in two genetic sequences, have been recognized within the succession. The result of Markov chain and cross-association analysis indicates that the deposition of the lithofacies is in the Markovian and non-cyclic process and represents asymmetric fining- upward. The chi-square test has been done to test for randomness in hypotheses for lithofacies transition at the confidence level of 95%. The entropy analysis has been done to evaluate the randomness of occurrence of lithofacies in a succession. Two types of entropies are related to every state; one is relevant to the Markov matrix expressing the upward transitions (entropy after deposition), and the other, relevant to the matrix expressing the downward transitions (entropy before deposition). The total energy regime calculated from the entropy analysis showing maximum randomness, suggests that changing pattern in the deposition has been a result of rapid to the steady flow. This results from a change in the depositional pattern from deltaic to lacustrine deposit and sediment bypassing that finally generated non-cyclicity in the sequence.

Published by: Rohini Das

Author: Rohini Das

Paper ID: V4I3-1632

Paper Status: published

Published: May 28, 2018

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Research Paper

Lung cancer detection system by fusion of CT and MRI images

Lung cancer is one of the common types of cancer in the world. It is hard to detect cancer and the affected level at an early stage. CT and MRI help us to detect this type of cancers at an early stage. Fusion of a CT and MRI images can be done for obtaining best results. However, in previous works, this method of diagnosis has not been carried out. In this proposed work combining of CT and MRI images can be done and the level of cancer in the lungs can be identified. Image fusion is used to identify the common features between the two images this can be used to improve the quality of the images for easy identification.

Published by: Gokulapriya V, M. Marikkannan

Author: Gokulapriya V

Paper ID: V4I3-1526

Paper Status: published

Published: May 28, 2018

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