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

Ali Saadon Al-Ogaili, Ali Q. Al-Shetwi, Hussein M. K. Al-Masri, Thanikanti Sudhakar Babu, Yap Hoon, Khaled Alzaareer and N. V. Phanendra Babu
Additional contact information
Ali Saadon Al-Ogaili: After Sale Department, HelioxCompany, De Waal 24, 5684 PH Best, The Netherlands
Ali Q. Al-Shetwi: Electrical Engineering Department, Fahad Bin Sultan University, Tabuk 47721, Saudi Arabia
Hussein M. K. Al-Masri: Department of Electrical Power Engineering, Yarmouk University, Irbid 21163, Jordan
Thanikanti Sudhakar Babu: Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad 500075, India
Yap Hoon: School of Engineering, Faculty of Innovation and Technology, Taylor’s University, Subang Jaya 47500, Selangor, Malaysia
Khaled Alzaareer: Electrical Engineering Department, Faculty of Engineering, Philadelphia University, Amman 19392, Jordan
N. V. Phanendra Babu: Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad 500075, India

Energies, 2021, vol. 14, issue 22, 1-28

Abstract: 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.

Keywords: battery electric buses; well-to-wheel (WTW) model; energy consumption forecast; transportation networks; data analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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