ENERGY ESTIMATION OF NCA BATTERY BY CONSIDERING THE UNBALANCED CELLS AND BATTERY WORKING AREA

Electric vehicles begin to replace conventional fossil-fueled vehicles. Indonesian government begin to encourage the conversions to electric vehicles (EV). The most common source of energy of electric vehicles until this daya is the battery, especially on small scale electric vehicles like e-bikes....

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Main Author: Edison (NIM : 23315012), Frans
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/22203
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:22203
spelling id-itb.:222032017-10-02T11:23:48ZENERGY ESTIMATION OF NCA BATTERY BY CONSIDERING THE UNBALANCED CELLS AND BATTERY WORKING AREA Edison (NIM : 23315012), Frans Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/22203 Electric vehicles begin to replace conventional fossil-fueled vehicles. Indonesian government begin to encourage the conversions to electric vehicles (EV). The most common source of energy of electric vehicles until this daya is the battery, especially on small scale electric vehicles like e-bikes. As the main energy source, the battery should always be in good performance so the EV can operate optimally. One information that required by EV users is the remaining distance that the EV can be driven. To obtain this information, it is necessary to measure the remaining energy contained in the battery. <br /> <br /> This study aims to estimate the remaining energy of the battery in series arrangement while taking into account the imbalance between cells and the work area of the battery. The method that used are energy counting and support vector regression. Energy conting are performed by accumulating power coming out of the battery when discharging or entering the battery during charging. The power is accumulated over time and compared to its nominal energy to obtain state of energy (SOE) of the battery. This method requires an initial value as a reference for calculation for the next iteration. In the first stage, the energy counting are performed on a single cell, which is cycled with three variations of current rates from the initial state 100% fully charged, to obtain individual cell characteristics which unaffected by other cells that occur on cells arranged in series. The data from one cell is arangged into lookup table that expresses the relation between voltage, SOE, and current. The Lookup tables are used as training data for Support Vector Regression (SVR) to generate models for estimating cell’ SOE. <br /> <br /> Electric vehicles begin to replace conventional fossil-fueled vehicles. Indonesian government begin to encourage the conversions to electric vehicles (EV). The most common source of energy of electric vehicles until this daya is the battery, especially on small scale electric vehicles like e-bikes. As the main energy source, the battery should always be in good performance so the EV can operate optimally. One information that required by EV users is the remaining distance that the EV can be driven. To obtain this information, it is necessary to measure the remaining energy contained in the battery. <br /> <br /> This study aims to estimate the remaining energy of the battery in series arrangement while taking into account the imbalance between cells and the work area of the battery. The method that used are energy counting and support vector regression. Energy conting are performed by accumulating power coming out of the battery when discharging or entering the battery during charging. The power is accumulated over time and compared to its nominal energy to obtain state of energy (SOE) of the battery. This method requires an initial value as a reference for calculation for the next iteration. In the first stage, the energy counting are performed on a single cell, which is cycled with three variations of current rates from the initial state 100% fully charged, to obtain individual cell characteristics which unaffected by other cells that occur on cells arranged in series. The data from one cell is arangged into lookup table that expresses the relation between voltage, SOE, and current. The Lookup tables are used as training data for Support Vector Regression (SVR) to generate models for estimating cell’ SOE. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Electric vehicles begin to replace conventional fossil-fueled vehicles. Indonesian government begin to encourage the conversions to electric vehicles (EV). The most common source of energy of electric vehicles until this daya is the battery, especially on small scale electric vehicles like e-bikes. As the main energy source, the battery should always be in good performance so the EV can operate optimally. One information that required by EV users is the remaining distance that the EV can be driven. To obtain this information, it is necessary to measure the remaining energy contained in the battery. <br /> <br /> This study aims to estimate the remaining energy of the battery in series arrangement while taking into account the imbalance between cells and the work area of the battery. The method that used are energy counting and support vector regression. Energy conting are performed by accumulating power coming out of the battery when discharging or entering the battery during charging. The power is accumulated over time and compared to its nominal energy to obtain state of energy (SOE) of the battery. This method requires an initial value as a reference for calculation for the next iteration. In the first stage, the energy counting are performed on a single cell, which is cycled with three variations of current rates from the initial state 100% fully charged, to obtain individual cell characteristics which unaffected by other cells that occur on cells arranged in series. The data from one cell is arangged into lookup table that expresses the relation between voltage, SOE, and current. The Lookup tables are used as training data for Support Vector Regression (SVR) to generate models for estimating cell’ SOE. <br /> <br /> Electric vehicles begin to replace conventional fossil-fueled vehicles. Indonesian government begin to encourage the conversions to electric vehicles (EV). The most common source of energy of electric vehicles until this daya is the battery, especially on small scale electric vehicles like e-bikes. As the main energy source, the battery should always be in good performance so the EV can operate optimally. One information that required by EV users is the remaining distance that the EV can be driven. To obtain this information, it is necessary to measure the remaining energy contained in the battery. <br /> <br /> This study aims to estimate the remaining energy of the battery in series arrangement while taking into account the imbalance between cells and the work area of the battery. The method that used are energy counting and support vector regression. Energy conting are performed by accumulating power coming out of the battery when discharging or entering the battery during charging. The power is accumulated over time and compared to its nominal energy to obtain state of energy (SOE) of the battery. This method requires an initial value as a reference for calculation for the next iteration. In the first stage, the energy counting are performed on a single cell, which is cycled with three variations of current rates from the initial state 100% fully charged, to obtain individual cell characteristics which unaffected by other cells that occur on cells arranged in series. The data from one cell is arangged into lookup table that expresses the relation between voltage, SOE, and current. The Lookup tables are used as training data for Support Vector Regression (SVR) to generate models for estimating cell’ SOE.
format Theses
author Edison (NIM : 23315012), Frans
spellingShingle Edison (NIM : 23315012), Frans
ENERGY ESTIMATION OF NCA BATTERY BY CONSIDERING THE UNBALANCED CELLS AND BATTERY WORKING AREA
author_facet Edison (NIM : 23315012), Frans
author_sort Edison (NIM : 23315012), Frans
title ENERGY ESTIMATION OF NCA BATTERY BY CONSIDERING THE UNBALANCED CELLS AND BATTERY WORKING AREA
title_short ENERGY ESTIMATION OF NCA BATTERY BY CONSIDERING THE UNBALANCED CELLS AND BATTERY WORKING AREA
title_full ENERGY ESTIMATION OF NCA BATTERY BY CONSIDERING THE UNBALANCED CELLS AND BATTERY WORKING AREA
title_fullStr ENERGY ESTIMATION OF NCA BATTERY BY CONSIDERING THE UNBALANCED CELLS AND BATTERY WORKING AREA
title_full_unstemmed ENERGY ESTIMATION OF NCA BATTERY BY CONSIDERING THE UNBALANCED CELLS AND BATTERY WORKING AREA
title_sort energy estimation of nca battery by considering the unbalanced cells and battery working area
url https://digilib.itb.ac.id/gdl/view/22203
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