A Study of Reduced Battery Degradation Through State-of-Charge Pre-Conditioning for Vehicle-to-Grid Operations

Transport electrification is a key enabler to reduce fossil fuel depletion and related carbon dioxide emissions. However, critical barriers exist in terms of battery costs and their expected life. Vehicle-to-grid technology can bring benefits to both the electrical power grid and electric vehicle ow...

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Autores principales: Truong M. N. Bui, Muhammad Sheikh, Truong Q. Dinh, Aniruddha Gupta, Dhammika W. Widanalage, James Marco
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Lenguaje:EN
Publicado: IEEE 2021
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spelling oai:doaj.org-article:fbd2c3e8c07a497db1ae087c642acde12021-12-01T00:00:58ZA Study of Reduced Battery Degradation Through State-of-Charge Pre-Conditioning for Vehicle-to-Grid Operations2169-353610.1109/ACCESS.2021.3128774https://doaj.org/article/fbd2c3e8c07a497db1ae087c642acde12021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9617644/https://doaj.org/toc/2169-3536Transport electrification is a key enabler to reduce fossil fuel depletion and related carbon dioxide emissions. However, critical barriers exist in terms of battery costs and their expected life. Vehicle-to-grid technology can bring benefits to both the electrical power grid and electric vehicle owners, while its practical implementation faces challenges due to the concerns over accelerated battery degradation. This paper presents a comprehensive study on reduced Lithium-ion battery degradation through state-of-charge pre-conditioning strategies that allow an electric vehicle to participate in vehicle-to-grid operations during periods in which the vehicle is parked. Energy capacity reduction of the electric vehicle battery are predicted using semi-empirical ageing models, which have been built and validated to capture the degradation behaviours of the battery with respect to both calendar and cycling ageing. Five charging strategies for battery state-of-charge pre-conditioning have been developed to evaluate the ability to mitigate battery ageing before commencing vehicle-to-grid operations. Simulation studies on battery degradation utilizing such charging mechanisms under two different operational profiles have been undertaken. The analytical results show that the proposed charging strategies do not accelerate battery degradation and are capable of mitigating the total ageing process from 7.3 – 26.7% for the first 100 days of operational life and gradually vary to 8.6 – 12.3% for one-year continual operation compared to the reference standard charging approach.Truong M. N. BuiMuhammad SheikhTruong Q. DinhAniruddha GuptaDhammika W. WidanalageJames MarcoIEEEarticleElectric vehiclesvehicle-to-gridbattery degradationLithium-ion batterySoC preconditioningsmart chargeElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 155871-155896 (2021)
institution DOAJ
collection DOAJ
language EN
topic Electric vehicles
vehicle-to-grid
battery degradation
Lithium-ion battery
SoC preconditioning
smart charge
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
spellingShingle Electric vehicles
vehicle-to-grid
battery degradation
Lithium-ion battery
SoC preconditioning
smart charge
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Truong M. N. Bui
Muhammad Sheikh
Truong Q. Dinh
Aniruddha Gupta
Dhammika W. Widanalage
James Marco
A Study of Reduced Battery Degradation Through State-of-Charge Pre-Conditioning for Vehicle-to-Grid Operations
description Transport electrification is a key enabler to reduce fossil fuel depletion and related carbon dioxide emissions. However, critical barriers exist in terms of battery costs and their expected life. Vehicle-to-grid technology can bring benefits to both the electrical power grid and electric vehicle owners, while its practical implementation faces challenges due to the concerns over accelerated battery degradation. This paper presents a comprehensive study on reduced Lithium-ion battery degradation through state-of-charge pre-conditioning strategies that allow an electric vehicle to participate in vehicle-to-grid operations during periods in which the vehicle is parked. Energy capacity reduction of the electric vehicle battery are predicted using semi-empirical ageing models, which have been built and validated to capture the degradation behaviours of the battery with respect to both calendar and cycling ageing. Five charging strategies for battery state-of-charge pre-conditioning have been developed to evaluate the ability to mitigate battery ageing before commencing vehicle-to-grid operations. Simulation studies on battery degradation utilizing such charging mechanisms under two different operational profiles have been undertaken. The analytical results show that the proposed charging strategies do not accelerate battery degradation and are capable of mitigating the total ageing process from 7.3 – 26.7% for the first 100 days of operational life and gradually vary to 8.6 – 12.3% for one-year continual operation compared to the reference standard charging approach.
format article
author Truong M. N. Bui
Muhammad Sheikh
Truong Q. Dinh
Aniruddha Gupta
Dhammika W. Widanalage
James Marco
author_facet Truong M. N. Bui
Muhammad Sheikh
Truong Q. Dinh
Aniruddha Gupta
Dhammika W. Widanalage
James Marco
author_sort Truong M. N. Bui
title A Study of Reduced Battery Degradation Through State-of-Charge Pre-Conditioning for Vehicle-to-Grid Operations
title_short A Study of Reduced Battery Degradation Through State-of-Charge Pre-Conditioning for Vehicle-to-Grid Operations
title_full A Study of Reduced Battery Degradation Through State-of-Charge Pre-Conditioning for Vehicle-to-Grid Operations
title_fullStr A Study of Reduced Battery Degradation Through State-of-Charge Pre-Conditioning for Vehicle-to-Grid Operations
title_full_unstemmed A Study of Reduced Battery Degradation Through State-of-Charge Pre-Conditioning for Vehicle-to-Grid Operations
title_sort study of reduced battery degradation through state-of-charge pre-conditioning for vehicle-to-grid operations
publisher IEEE
publishDate 2021
url https://doaj.org/article/fbd2c3e8c07a497db1ae087c642acde1
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