Charging strategy selection for electric bus systems: A multi-criteria decision-making approach

被引:6
|
作者
Sadrani, Mohammad [1 ]
Najafi, Amirhossein [2 ]
Mirqasemi, Razieh [2 ]
Antoniou, Constantinos [1 ]
机构
[1] Tech Univ Munich, Chair Transportat Syst Engn, TUM Sch Engn & Design, D-80333 Munich, Germany
[2] Amirkabir Univ Technol, Dept Ind Engn, Tehran, Iran
关键词
Electric bus; Charging strategy; Multi-criteria decision making; Sustainable transport; Fuzzy best worst method; FUZZY TOPSIS METHODS; PUBLIC TRANSPORT; EDAS METHOD; AHP; ELECTRIFICATION; EMISSIONS; VEHICLES; HYBRID; MODEL;
D O I
10.1016/j.apenergy.2023.121415
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Selecting the best type of charging strategy, among a variety of options such as overnight (slow) charging and opportunity (fast) charging methods, is a crucial step in electrifying bus networks. This step has gained increased importance with the growing need for sustainable transportation solutions and the widespread adoption of electric buses (EBs) in public transport systems. This study develops a multi-criteria decision-making (MCDM) approach for selecting the best EB charging strategy, considering a comprehensive range of criteria, including economic, environmental, social, operational, and quality-of-service criteria. A thorough literature review and a survey of EB experts are conducted to identify key decision-making factors in this area. A Fuzzy Best-Worst Method (FBWM) is designed to determine the weight of criteria, and a Fuzzy Ranking of Alternatives through Functional mapping of criterion subintervals into a Single Interval (FRAFSI) method is designed to rank available charging strategies for EB systems in Munich, Germany. Results show that the most crucial consideration for decision-makers is the economic aspect, followed by operational and environmental factors. The infrastructure cost is the most crucial factor in the economic category, followed by battery cost and operational cost. The driving range is the most crucial factor in the operational category, followed by charging duration and energy monitoring. The experts' assessments indicate a preference for overnight charging over opportunity charging. The results of the FRAFSI are in line with other methods (fuzzy TOPSIS and fuzzy EDAS). Our findings offer valuable insights and guidance for transportation authorities and decision-makers in charge of selecting charging strategies for EBs.
引用
收藏
页数:20
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