Chapter Genetic Algorithm Optimization of an Energy Storage System Design and Fuzzy Logic Supervision for Battery Electric Vehicles

This chapter presents a methodology to optimize the capacity and power of the ultracapacitor (UC) energy storage device and also the fuzzy logic supervision strategy for a battery electric vehicle (BEV) equipped with electrochemical battery (EB). The aim of the optimization was to prolong the EB lif...

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Main Author: Breban, Stefan
Format: Online
Language:English
Published: InTechOpen 2021
Subjects:
Online Access:ONIX_20210602_10.5772/62587_274
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author Breban, Stefan
author_browse Breban, Stefan
author_facet Breban, Stefan
author_sort Breban, Stefan
collection Directory of Open Access Books
description This chapter presents a methodology to optimize the capacity and power of the ultracapacitor (UC) energy storage device and also the fuzzy logic supervision strategy for a battery electric vehicle (BEV) equipped with electrochemical battery (EB). The aim of the optimization was to prolong the EB life and consequently to permit financial economies for the end-user of the BEV. Eight variables were used in the optimization process: two variables that control the energy storage capacity and power of the UC device and six variables that change the membership functions of the fuzzy logic supervisor. The results of the optimization, using a genetic algorithm from MATLAB®, are showing an increase of the financial economy of 16%.
format Online
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institution Directory of Open Access Books
language eng
publishDate 2021
publishDateRange 2021
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spelling doab-20.500.12854ir-701832024-04-04T14:41:16Z Chapter Genetic Algorithm Optimization of an Energy Storage System Design and Fuzzy Logic Supervision for Battery Electric Vehicles Breban, Stefan Genetic algorithm optimization, battery electric vehicle, fuzzy logic, ultracapacitor, electrochemical battery thema EDItEUR::P Mathematics and Science::PB Mathematics::PBU Optimization This chapter presents a methodology to optimize the capacity and power of the ultracapacitor (UC) energy storage device and also the fuzzy logic supervision strategy for a battery electric vehicle (BEV) equipped with electrochemical battery (EB). The aim of the optimization was to prolong the EB life and consequently to permit financial economies for the end-user of the BEV. Eight variables were used in the optimization process: two variables that control the energy storage capacity and power of the UC device and six variables that change the membership functions of the fuzzy logic supervisor. The results of the optimization, using a genetic algorithm from MATLAB®, are showing an increase of the financial economy of 16%. 2021-02-10T12:58:18Z 2021-06-02T10:08:05Z 2016 chapter ONIX_20210602_10.5772/62587_274 https://library.oapen.org/handle/20.500.12657/49160 https://directory.doabooks.org/handle/20.500.12854/70183 eng open access image/jpeg image/jpeg n/a n/a https://library.oapen.org/bitstream/20.500.12657/49160/1/50204.pdf https://library.oapen.org/bitstream/20.500.12657/49160/1/50204.pdf InTechOpen 10.5772/62587 10.5772/62587 035ecc65-6737-43cf-a13a-6bdf67ce01f4 open access
spellingShingle Genetic algorithm optimization, battery electric vehicle, fuzzy logic, ultracapacitor, electrochemical battery
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBU Optimization
Breban, Stefan
Chapter Genetic Algorithm Optimization of an Energy Storage System Design and Fuzzy Logic Supervision for Battery Electric Vehicles
title Chapter Genetic Algorithm Optimization of an Energy Storage System Design and Fuzzy Logic Supervision for Battery Electric Vehicles
title_full Chapter Genetic Algorithm Optimization of an Energy Storage System Design and Fuzzy Logic Supervision for Battery Electric Vehicles
title_fullStr Chapter Genetic Algorithm Optimization of an Energy Storage System Design and Fuzzy Logic Supervision for Battery Electric Vehicles
title_full_unstemmed Chapter Genetic Algorithm Optimization of an Energy Storage System Design and Fuzzy Logic Supervision for Battery Electric Vehicles
title_short Chapter Genetic Algorithm Optimization of an Energy Storage System Design and Fuzzy Logic Supervision for Battery Electric Vehicles
title_sort chapter genetic algorithm optimization of an energy storage system design and fuzzy logic supervision for battery electric vehicles
topic Genetic algorithm optimization, battery electric vehicle, fuzzy logic, ultracapacitor, electrochemical battery
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBU Optimization
topic_facet Genetic algorithm optimization, battery electric vehicle, fuzzy logic, ultracapacitor, electrochemical battery
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBU Optimization
url ONIX_20210602_10.5772/62587_274
work_keys_str_mv AT brebanstefan chaptergeneticalgorithmoptimizationofanenergystoragesystemdesignandfuzzylogicsupervisionforbatteryelectricvehicles