Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Optimization of charging infrastructure planning for plug-in electric vehicles based on a dynamic programming model
Electric vehicles (EV) are a new mode of transportations that are replacing conventional vehicles. However, EVs face the problem of insufficient charging infrastructure which limits their drive range. Furthermore, the limited resources of countries are also a major problem faced by EVs in infrastructure planning and development. To overcome this problem, this paper proposes a model, comprising several techniques that allocate the limited resources optimally. Moreover, the model also identifies the location and number of stations required for maximizing the drive range of EVs. The methods used in the model are Activity Relationship Chart (ARC) for the recording of data, Dynamic Programming (DP) for optimal allocation of resources, and the center of gravity (COG) method to check the feasibility of the results obtained by DP. The model is applied to a case study of a motorway system in Pakistan to identify and optimally allocate charging stations along the route that connects the four major cities of Pakistan. The optimized allocation of limited resources using the proposed model simultaneously takes into account the flow, distance, resource limit, and range limit of EVs while building charging infrastructure plans.
Optimization of charging infrastructure planning for plug-in electric vehicles based on a dynamic programming model
Electric vehicles (EV) are a new mode of transportations that are replacing conventional vehicles. However, EVs face the problem of insufficient charging infrastructure which limits their drive range. Furthermore, the limited resources of countries are also a major problem faced by EVs in infrastructure planning and development. To overcome this problem, this paper proposes a model, comprising several techniques that allocate the limited resources optimally. Moreover, the model also identifies the location and number of stations required for maximizing the drive range of EVs. The methods used in the model are Activity Relationship Chart (ARC) for the recording of data, Dynamic Programming (DP) for optimal allocation of resources, and the center of gravity (COG) method to check the feasibility of the results obtained by DP. The model is applied to a case study of a motorway system in Pakistan to identify and optimally allocate charging stations along the route that connects the four major cities of Pakistan. The optimized allocation of limited resources using the proposed model simultaneously takes into account the flow, distance, resource limit, and range limit of EVs while building charging infrastructure plans.
Optimization of charging infrastructure planning for plug-in electric vehicles based on a dynamic programming model
Khan Babar, Abdul Haseeb (Autor:in) / Yousaf, Ali (Autor:in)
Transportation Planning and Technology ; 45 ; 59-75
02.01.2022
17 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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