Review of the Estimation Methods of Energy Consumption for Battery Electric Buses

In the transportation sector, electric battery bus (EBB) deployment is considered to be a potential solution to reduce global warming because no greenhouse gas (GHG) emissions are directly produced by EBBs. In addition to the required charging infrastructure, estimating the energy consumption of bus...

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Autores principales:	Ali Saadon Al-Ogaili, Ali Q. Al-Shetwi, Hussein M. K. Al-Masri, Thanikanti Sudhakar Babu, Yap Hoon, Khaled Alzaareer, N. V. Phanendra Babu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	battery electric buses well-to-wheel (WTW) model energy consumption forecast transportation networks data analysis Technology T
Acceso en línea:	https://doaj.org/article/b7e75abc0c2e4c59a06309701dc0f347
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spelling	oai:doaj.org-article:b7e75abc0c2e4c59a06309701dc0f3472021-11-25T17:26:55ZReview of the Estimation Methods of Energy Consumption for Battery Electric Buses10.3390/en142275781996-1073https://doaj.org/article/b7e75abc0c2e4c59a06309701dc0f3472021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/22/7578https://doaj.org/toc/1996-1073In the transportation sector, electric battery bus (EBB) deployment is considered to be a potential solution to reduce global warming because no greenhouse gas (GHG) emissions are directly produced by EBBs. In addition to the required charging infrastructure, estimating the energy consumption of buses has become a crucial precondition for the deployment and planning of electric bus fleets. Policy and decision-makers may not have the specific tools needed to estimate the energy consumption of a particular bus network. Therefore, many state-of-the-art studies have proposed models to determine the energy demand of electric buses. However, these studies have not critically reviewed, classified and discussed the challenges of the approaches that are applied to estimate EBBs’ energy demands. Thus, this manuscript provides a detailed review of the forecasting models used to estimate the energy consumption of EBBs. Furthermore, this work fills the gap by classifying the models for estimating EBBs’ energy consumption into small-town depot and big-city depot networks. In brief, this review explains and discusses the models and formulations of networks associated with well-to-wheel (WTW) assessment, which can determine the total energy demand of a bus network. This work also reviews a survey of the most recent optimization methods that could be applied to achieve the optimal pattern parameters of EBB fleet systems, such as the bus battery capacity, charger rated power and the total number of installed chargers in the charging station. This paper highlights the issues and challenges, such as the impact of external factors, replicating real-world data, big data analytics, validity index, and bus routes’ topography, with recommendations on each issue. Also, the paper proposes a generic framework based on optimization algorithms, namely, artificial neural network (ANN) and particle swarm optimization (PSO), which will be significant for future development in implementing new energy consumption estimation approaches. Finally, the main findings of this manuscript further our understanding of the determinants that contribute to managing the energy demand of EBBs networks.Ali Saadon Al-OgailiAli Q. Al-ShetwiHussein M. K. Al-MasriThanikanti Sudhakar BabuYap HoonKhaled AlzaareerN. V. Phanendra BabuMDPI AGarticlebattery electric buseswell-to-wheel (WTW) modelenergy consumption forecasttransportation networksdata analysisTechnologyTENEnergies, Vol 14, Iss 7578, p 7578 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	battery electric buses well-to-wheel (WTW) model energy consumption forecast transportation networks data analysis Technology T
spellingShingle	battery electric buses well-to-wheel (WTW) model energy consumption forecast transportation networks data analysis Technology T Ali Saadon Al-Ogaili Ali Q. Al-Shetwi Hussein M. K. Al-Masri Thanikanti Sudhakar Babu Yap Hoon Khaled Alzaareer N. V. Phanendra Babu Review of the Estimation Methods of Energy Consumption for Battery Electric Buses
description	In the transportation sector, electric battery bus (EBB) deployment is considered to be a potential solution to reduce global warming because no greenhouse gas (GHG) emissions are directly produced by EBBs. In addition to the required charging infrastructure, estimating the energy consumption of buses has become a crucial precondition for the deployment and planning of electric bus fleets. Policy and decision-makers may not have the specific tools needed to estimate the energy consumption of a particular bus network. Therefore, many state-of-the-art studies have proposed models to determine the energy demand of electric buses. However, these studies have not critically reviewed, classified and discussed the challenges of the approaches that are applied to estimate EBBs’ energy demands. Thus, this manuscript provides a detailed review of the forecasting models used to estimate the energy consumption of EBBs. Furthermore, this work fills the gap by classifying the models for estimating EBBs’ energy consumption into small-town depot and big-city depot networks. In brief, this review explains and discusses the models and formulations of networks associated with well-to-wheel (WTW) assessment, which can determine the total energy demand of a bus network. This work also reviews a survey of the most recent optimization methods that could be applied to achieve the optimal pattern parameters of EBB fleet systems, such as the bus battery capacity, charger rated power and the total number of installed chargers in the charging station. This paper highlights the issues and challenges, such as the impact of external factors, replicating real-world data, big data analytics, validity index, and bus routes’ topography, with recommendations on each issue. Also, the paper proposes a generic framework based on optimization algorithms, namely, artificial neural network (ANN) and particle swarm optimization (PSO), which will be significant for future development in implementing new energy consumption estimation approaches. Finally, the main findings of this manuscript further our understanding of the determinants that contribute to managing the energy demand of EBBs networks.
format	article
author	Ali Saadon Al-Ogaili Ali Q. Al-Shetwi Hussein M. K. Al-Masri Thanikanti Sudhakar Babu Yap Hoon Khaled Alzaareer N. V. Phanendra Babu
author_facet	Ali Saadon Al-Ogaili Ali Q. Al-Shetwi Hussein M. K. Al-Masri Thanikanti Sudhakar Babu Yap Hoon Khaled Alzaareer N. V. Phanendra Babu
author_sort	Ali Saadon Al-Ogaili
title	Review of the Estimation Methods of Energy Consumption for Battery Electric Buses
title_short	Review of the Estimation Methods of Energy Consumption for Battery Electric Buses
title_full	Review of the Estimation Methods of Energy Consumption for Battery Electric Buses
title_fullStr	Review of the Estimation Methods of Energy Consumption for Battery Electric Buses
title_full_unstemmed	Review of the Estimation Methods of Energy Consumption for Battery Electric Buses
title_sort	review of the estimation methods of energy consumption for battery electric buses
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/b7e75abc0c2e4c59a06309701dc0f347
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_version_	1718412371041452032

Review of the Estimation Methods of Energy Consumption for Battery Electric Buses

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