Construction of a battery management system in electric vehicle

Due to their advantages of high energy density, relatively long life time and lack of memory effect, lithium ion (Li-ion) batteries are very popular and are widely used in electric vehicle (EV) applications. However, overcharging or over discharging them could bring loss in performance and result in...

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Main Author: Chen, Shao Jun
Other Authors: Goh Wang Ling
Format: Final Year Project
Language:English
Published: 2015
Subjects:
Online Access:http://hdl.handle.net/10356/64698
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-646982023-07-07T16:50:35Z Construction of a battery management system in electric vehicle Chen, Shao Jun Goh Wang Ling School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries DRNTU::Engineering::Electrical and electronic engineering::Electronic circuits Due to their advantages of high energy density, relatively long life time and lack of memory effect, lithium ion (Li-ion) batteries are very popular and are widely used in electric vehicle (EV) applications. However, overcharging or over discharging them could bring loss in performance and result in potentially dangerous situations. Therefore additional requirements on safety, reliability and modularity of battery management system (BMS) have to be considered. In order to achieve these requirements, the BMS needs to balance the state of charge (SOC) of each cell during battery operations based on the inputs such as the voltage, current and temperature of each cell. In this report, the working principle of a traditional BMS will be explained and evaluation of several different SOC estimation methods will be done so as to adopt the most accuracy and efficient SOC estimation. Methods to determine the state of health (SOH) and remaining useful life (RUL) of the battery will also be discussed. Different cell balancing techniques will also be evaluated and the most efficient cell balancing technique will be adopted. The BMS will be built by using Xilinx FPGA and soft processor cores from Xilinx, PicoBlaze, to provide control over the discrete electronic components for measuring voltage, current and temperature. It also will implement the SOC estimation and controlling the cell balancing circuits. The circuitry design on monitoring the voltage, current and temperature of the battery will be discussed in detailed. Accuracy of these parameters and the effectiveness of the cell balancing technique will be shown so as to ensure the reliability and effectivity of the BMS. Problem that arises from building the BMS will also be discussed and further recommendations for future work will be made. Bachelor of Engineering 2015-05-29T06:37:14Z 2015-05-29T06:37:14Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/64698 en Nanyang Technological University 72 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries
DRNTU::Engineering::Electrical and electronic engineering::Electronic circuits
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries
DRNTU::Engineering::Electrical and electronic engineering::Electronic circuits
Chen, Shao Jun
Construction of a battery management system in electric vehicle
description Due to their advantages of high energy density, relatively long life time and lack of memory effect, lithium ion (Li-ion) batteries are very popular and are widely used in electric vehicle (EV) applications. However, overcharging or over discharging them could bring loss in performance and result in potentially dangerous situations. Therefore additional requirements on safety, reliability and modularity of battery management system (BMS) have to be considered. In order to achieve these requirements, the BMS needs to balance the state of charge (SOC) of each cell during battery operations based on the inputs such as the voltage, current and temperature of each cell. In this report, the working principle of a traditional BMS will be explained and evaluation of several different SOC estimation methods will be done so as to adopt the most accuracy and efficient SOC estimation. Methods to determine the state of health (SOH) and remaining useful life (RUL) of the battery will also be discussed. Different cell balancing techniques will also be evaluated and the most efficient cell balancing technique will be adopted. The BMS will be built by using Xilinx FPGA and soft processor cores from Xilinx, PicoBlaze, to provide control over the discrete electronic components for measuring voltage, current and temperature. It also will implement the SOC estimation and controlling the cell balancing circuits. The circuitry design on monitoring the voltage, current and temperature of the battery will be discussed in detailed. Accuracy of these parameters and the effectiveness of the cell balancing technique will be shown so as to ensure the reliability and effectivity of the BMS. Problem that arises from building the BMS will also be discussed and further recommendations for future work will be made.
author2 Goh Wang Ling
author_facet Goh Wang Ling
Chen, Shao Jun
format Final Year Project
author Chen, Shao Jun
author_sort Chen, Shao Jun
title Construction of a battery management system in electric vehicle
title_short Construction of a battery management system in electric vehicle
title_full Construction of a battery management system in electric vehicle
title_fullStr Construction of a battery management system in electric vehicle
title_full_unstemmed Construction of a battery management system in electric vehicle
title_sort construction of a battery management system in electric vehicle
publishDate 2015
url http://hdl.handle.net/10356/64698
_version_ 1772828164990435328